The Future of Jobs 3 the report features unique data from LinkedIn, Human ingenuity is at the root of all shared Coursera, ADP and FutureFit.AI, which have prosperity. As the frontier between the work provided innovative new metrics to shed light on tasks performed by humans and those performed one of the most important challenges of our time. by machines and algorithms shifts, we have a short window of opportunity to ensure that these We would like to express our appreciation to transformations lead to a new age of good work, Vesselina Ratcheva, Insights Lead; Guillaume good jobs and improved quality of life for all. In Hingel, Insights Lead; and Sophie Brown, Project the midst of the pandemic recession, this window Specialist for their dedication to this report. We is closing fast. Businesses, governments and would also like to thank Ida Jeng Christensen, workers must plan to work together to implement Eoin Ó Cathasaigh, Genesis Elhussein, Till a new vision for the global workforce. Leopold and SungAh Lee for their support of this project at the World Economic Forum.

The Future of Jobs 4

Executive Summary

The COVID-19 pandemic-induced lockdowns and destruction accelerates. Employers expect related global recession of 2020 have created a that by 2025, increasingly redundant roles will highly uncertain outlook for the labour market and decline from being 15.4% of the workforce accelerated the arrival of the future of work. The to 9% (6.4% decline), and that emerging Future of Jobs Report 2020 aims to shed light on: 1) professions will grow from 7.8% to 13.5% the pandemic-related disruptions thus far in 2020, (5.7% growth) of the total employee base contextualized within a longer history of economic of company respondents. Based on these cycles, and 2) the expected outlook for technology figures, we estimate that by 2025, 85 million adoption jobs and skills in the next five years. jobs may be displaced by a shift in the division Despite the currently high degree of uncertainty, the of labour between humans and machines, report uses a unique combination of qualitative and while 97 million new roles may emerge that quantitative intelligence to expand the knowledge are more adapted to the new division of labour base about the future of jobs and skills. It aggregates between humans, machines and algorithms. the views of business leaders—chief executives, chief strategy officers and chief human resources ­ Skills gaps continue to be high as in- officers­on the frontlines of decision-making demand skills across jobs change in regarding human capital with the latest data from the next five years. The top skills and skill public and private sources to create a clearer picture groups which employers see as rising in of both the current situation and the future outlook prominence in the lead up to 2025 include for jobs and skills. The report also provides in-depth groups such as critical thinking and analysis information for 15 industry sectors and 26 advanced as well as problem-solving, and skills in and emerging countries. self-management such as active learning, resilience, stress tolerance and flexibility. On The report’s key findings include: average, companies estimate that around 40% of workers will require reskilling of six months ­ The pace of technology adoption is expected or less and 94% of business leaders report that to remain unabated and may accelerate in they expect employees to pick up new skills on some areas. The adoption of cloud computing, the job, a sharp uptake from 65% in 2018. big data and e-commerce remain high priorities for business leaders, following a trend established ­ The future of work has already arrived for in previous years. However, there has also been a large majority of the online white-collar a significant rise in interest for encryption, non- workforce. Eighty-four percent of employers humanoid robots and artificial intelligence. are set to rapidly digitalize working processes, including a significant expansion of remote ­ Automation, in tandem with the COVID-19 work—with the potential to move 44% of their recession, is creating a double-disruption' workforce to operate remotely. To address scenario for workers. In addition to the concerns about productivity and well-being, current disruption from the pandemic-induced about one-third of all employers expect to also lockdowns and economic contraction, take steps to create a sense of community, technological adoption by companies will connection and belonging among employees transform tasks, jobs and skills by 2025. Forty- through digital tools, and to tackle the well-being three percent of businesses surveyed indicate challenges posed by the shift to remote work. that they are set to reduce their workforce due to technology integration, 41% plan to expand ­ In the absence of proactive efforts, their use of contractors for task-specialized inequality is likely to be exacerbated by work, and 34% plan to expand their workforce the dual impact of technology and the due to technology integration. By 2025, the pandemic recession. Jobs held by lower time spent on current tasks at work by humans wage workers, women and younger workers and machines will be equal. A significant share were more deeply impacted in the first phase of companies also expect to make changes of the economic contraction. Comparing the to locations, their value chains, and the size impact of the Global Financial Crisis of 2008 of their workforce due to factors beyond on individuals with lower education levels to technology in the next five years. the impact of the COVID-19 crisis, the impact today is far more significant and more likely to ­ Although the number of jobs destroyed will deepen existing inequalities. be surpassed by the number of jobs of tomorrow’ created, in contrast to previous ­ Online learning and training is on the rise years, job creation is slowing while job but looks different for those in employment

The Future of Jobs 5 and those who are unemployed. There lagging, with only 42% of employees taking up has been a four-fold increase in the numbers employer-supported reskilling and upskilling of individuals seeking out opportunities for opportunities. learning online through their own initiative, a five-fold increase in employer provision of ­ Companies need to invest in better metrics online learning opportunities to their workers of human and social capital through and a nine-fold enrolment increase for learners adoption of environmental, social and accessing online learning through government governance (ESG) metrics and matched programmes. Those in employment are with renewed measures of human capital placing larger emphasis on personal accounting. A significant number of business development courses, which have seen 88% leaders understand that reskilling employees, growth among that population. Those who are particularly in industry coalitions and in public- unemployed have placed greater emphasis private collaborations, is both cost-effective and on learning digital skills such as data analysis, has significant mid- to long-term dividends—not computer science and information technology. only for their enterprise but also for the benefit of society more broadly. Companies hope ­ The window of opportunity to reskill and to internally redeploy nearly 50% of workers upskill workers has become shorter in displaced by technological automation and the newly constrained labour market. This augmentation, as opposed to making wider use applies to workers who are likely to stay in their of layoffs and automation-based labour savings roles as well as those who risk losing their roles as a core workforce strategy. due to rising recession-related unemployment and can no longer expect to retrain at work. ­ The public sector needs to provide stronger For those workers set to remain in their roles, support for reskilling and upskilling for the share of core skills that will change in at-risk or displaced workers. Currently, the next five years is 40%, and 50% of all only 21% of businesses report being able employees will need reskilling (up 4%). to make use of public funds to support their employees through reskilling and upskilling. ­ Despite the current economic downturn, The public sector will need to create incentives the large majority of employers recognize for investments in the markets and jobs the value of human capital investment. of tomorrow; provide stronger safety nets An average of 66% of employers surveyed for displaced workers in the midst of job expect to get a return on investment in transitions; and to decisively tackle long- upskilling and reskilling within one year. delayed improvements to education and However, this time horizon risks being too training systems. Additionally, it will be long for many employers in the context of important for governments to consider the the current economic shock, and nearly 17% longer-term labour market implications of remain uncertain on having any return on their maintaining, withdrawing or partly continuing investment. On average, employers expect the strong COVID-19 crisis support they are to offer reskilling and upskilling to just over providing to support wages and maintain jobs 70% of their employees by 2025. However, in most advanced economies. employee engagement into those courses is

The Future of Jobs 6

Part 1 Tracking the Future

The Future of Jobs 7

1 The Labour Market Outlook in the Pandemic Economy

1.1 Introduction

Developing and enhancing human skills and in 2016 and 2018, this 2020 third edition of the capabilities through education, learning and Future of Jobs Report provides a global overview meaningful work are key drivers of economic of the ongoing technological augmentation of work, success, of individual well-being and societal emerging and disrupted jobs and skills, projected cohesion. The global shift to a future of work expansion of mass reskilling and upskilling across is defined by an ever-expanding cohort of new industries as well as new strategies for effective technologies, by new sectors and markets, workforce transitions at scale. by global economic systems that are more interconnected than in any other point in history, Over the past decade, a set of ground-breaking, and by information that travels fast and spreads emerging technologies have signalled the start of wide. Yet the past decade of technological the Fourth Industrial Revolution. To capture the advancement has also brought about the looming opportunities created by these technologies, many possibility of mass job displacement, untenable companies across the private sector have embarked skills shortages and a competing claim to the on a reorientation of their strategic direction. By unique nature of human intelligence now challenged 2025, the capabilities of machines and algorithms by artificial intelligence. The coming decade will will be more broadly employed than in previous require purposeful leadership to arrive at a future years, and the work hours performed by machines of work that fulfils human potential and creates will match the time spent working by human broadly shared prosperity. beings. The augmentation of work will disrupt the employment prospects of workers across a broad In 2020, economic globalization is stalling, social range of industries and geographies. New data from cohesion is being eroded by significant unrest and the Future of Jobs Survey suggests that on average political polarization, and an unfolding recession is 15% of a company’s workforce is at risk of disruption threatening the livelihoods of those at the lower end in the horizon up to 2025, and on average 6% of of the income spectrum. As a new global recession workers are expected to be fully displaced. brought on by the COVID-19 health pandemic impacts economies and labour markets, millions This report projects that in the mid-term, job of workers have experienced changes which have destruction will most likely be offset by job growth profoundly transformed their lives within and beyond in the ‘jobs of tomorrow’—the surging demand work, their well-being and their productivity. One for workers who can fill green economy jobs, roles of the defining features of these changes is their at the forefront of the data and AI economy, as asymmetric nature—impacting already disadvantaged well as new roles in engineering, cloud computing populations with greater ferocity and velocity. and product development. This set of emerging professions also reflects the continuing importance Over the course of half a decade the World of human interaction in the new economy, with Economic Forum has tracked the labour market increasing demand for care economy jobs; roles in impact of the Fourth Industrial Revolution, identifying marketing, sales and content production; as well as the potential scale of worker displacement alongside roles at the forefront of people and culture.1 Employers strategies for empowering job transitions from answering the Future of Jobs Survey are motivated declining to emerging roles. The fundamental rate to support workers who are displaced from their of progress towards greater technological incursion current roles, and plan to transition as many as 46% into the world of work has only accelerated over the of those workers from their current jobs into emerging two years since the 2018 edition of the report. Under opportunities. In addition, companies are looking to the influence of the current economic recession provide reskilling and upskilling opportunities to the the underlying trends toward the technological majority of their staff (73%) cognizant of the fact that, augmentation of work have accelerated. Building by 2025, 44% of the skills that employees will need to upon the Future of Jobs methodology developed perform their roles effectively will change.

The Future of Jobs 8 The sections that follow in this first chapter structures which can support such adaptation both of the Future of Jobs Report situate the 2020 across government and across business. COVID-19 economic recession in the context of past recessions, and in the context of the Fourth This edition of the Future of Jobs Report takes stock Industrial Revolution. They review the impact of this of the impact of two twin events—the onset of the health shock on the labour market, paying particular Fourth Industrial Revolution and of the COVID-19 attention to its asymmetric nature. Chapter 2 recession in the context of broader societal and outlines the latest evidence from the Future of Jobs economic inequities. It provides new insights into Survey, taking stock of the path of technological effective practices and policies for supporting worker adoption, the scale and depth of the job transitions transitions towards a more equitable and prosperous and the learning provision that is in place and future of work. In economies riddled with inequalities planned in the horizon up to 2024. Finally, Chapter and sluggish adaptation to the demands of the 3 reviews the public and private sector policies and new world of work, there is an ever-larger need for practices that can support a proactive adaptation a `Great Reset’, which can herald opportunities for to these unfolding trends. In particular, the chapter economic prosperity and societal progress through outlines the mechanisms for job transitions, the good jobs. imperatives of creating a learning organization and

1.2 Short-term shocks and long-term trends

Over centuries, technological, social and political In late 2019, the gradual onset of the future of transformations have shaped economies and the work—due in large part to automation, technology capacity of individuals to make a living. The first and and globalization—appeared to pose the greatest second Industrial Revolutions displaced trades that risk to labour market stability. The first half of had thrived on older technologies and gave rise to 2020 has seen an additional, significant and new machines, new ways of work and new demand unexpected disruption to labour markets, with for skill sets that could harness the power of steam, immediate knock-on effects on the livelihoods of coal and factory production. The transformation individuals and the household incomes of families. of production has consequently given rise to new The COVID-19 pandemic appears to be deepening professions and new ways of working that eventually existing inequalities across labour markets, to have paved the path to greater prosperity despite initial job reversed the gain in employment made since the displacement among individuals. Although in 2018 we Global Financial Crisis in 2007­2008, and to have proposed that the labour market impact of the Fourth accelerated the arrival of the future of work. The Industrial Revolution can be managed while maintaining changes heralded by the COVID-19 pandemic stable levels of employment, the current 2020 global have compounded the long-term changes already recession has created a `new normal’ in which short- triggered by the Fourth Industrial Revolution, which term and long-term disruptions are intertwined. has, consequently, increased in velocity and depth.

A significant volume of research has been published In reaction to the risk to life caused by the spread on the future of work since the World Economic of the COVID-19 virus, governments have legislated Forum published it first edition. To date, the full or partial closures of business operations, conclusions drawn from that body of literature causing a sharp shock to economies, societies appear to offer both hope and caution. The twin and labour markets. Many businesses have closed forces of technology and globalisation have brought their physical office locations and have faced profound transformations to labour markets and limitations in doing business face-to-face. Figure 2 in the near term.2 Few analysts propose that shows the trajectory of those closures. Beginning technological disruption will lead to shrinking in mid-March and by mid-April, nearly 55% of opportunities in the aggregate,3 and many of the economies (about 100 countries) had enacted insights gathered point to the emergence of new workplace closures which affected all but essential job opportunities. Across countries and supply businesses.6 During May and June, economies chains, research has evidenced rising demand resumed some in-person business operations—yet for employment in nonroutine analytics jobs limitations to the physical operation of business accompanied by significant automation of routine continue, geographic mobility between countries manual jobs.4 Empirically, these changes can be persist and the consumption patterns of individuals observed in data tracking employment trends in the have been dramatically altered. By late June 2020, United States between 2007­2018. The evidence about 5% of countries globally still mandated a full indicates that nearly 2.6 million jobs were displaced closure of in-person business operations, and only over a span of a decade.5 Figure 1 presents the about 23% of countries were fully back to open.7 types of roles that are being displaced—namely In addition, irrespective of legislated measures, Computer Operators, Administrative Assistants, individuals have shifted to working remotely and Filing Clerks, Data Entry Keyers, Payroll Clerks and enacting physical distancing.8 other such roles which depend on technologies and work processes which are fast becoming obsolete.

The Future of Jobs 9 FIGURE 1 Employment trends for jobs in the United States at high risk of automation, 2007­2018

-80 -70 -60 -50 -40 -30 -20 -10 Computer Operators Executive Secretaries and Executive Administrative Assistants Word Processors and Typists Switchboard Operators, Including Answering Service Machine Feeders and Offbearers Telemarketers File Clerks Postal Service Mail Sorters, Processors, and Processing Machine Operators Brickmasons and Blockmasons Data Entry Keyers Bill and Account Collectors Mail Clerks and Mail Machine Operators, Except Postal Service Order Clerks Legal Secretaries Information and Record Clerks, All Other Sewing Machine Operators Helpers­Installation, Maintenance, and Repair Workers Payroll and Timekeeping Clerks Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic Drywall and Ceiling Tile Installers

0

Employment change 2007-2018 (%)

Ding, et al, 2020.

Collectively, the life-preserving measures to stop the four global recessions which have throughout spread of the COVID-19 virus have led to a sharp history impacted employment levels in significant contraction of economic activity, a marked decline ways. The figure shows that during periods of in capital expenditure among several industries relative labour market stability unemployment facing decline in demand for their products and stands at near or around 5% while during periods services, and put new pressures on enterprises of major disruption unemployment peaks at or and sectors. Not all companies have been equally exceeds 10%. During the financial crisis of 2010, affected. Some businesses have the resources to unemployment peaked at 8.5% only to drop weather the uncertainty, but others do not. Among to an average of 5% across OECD economies those faltering are companies that typically don’t in late 2019.9 According to the International hold large cash reserves such as SMEs (small- Labour Organization (ILO), during the first half to-medium enterprises) or businesses in sectors of 2020 real unemployment figures jumped to such as Restaurants and Hospitality. Some types an average of 6.6% in quarter 2 of 2020. The of business operations can be resumed remotely, OECD predicts that those figures could peak at but others, such as those in the Tourism or Retail 12.6% by the end of 2020 and still could stand sectors that depend on in-person contact or travel, at 8.9% by end 2021.10 This scenarios assumes have sustained greater damage (Figure 9 on page 17 that the economies analysed experience two demonstrates some of those effects). waves of infection from the COVID-19 virus accompanied by an associated slow-down of The current health pandemic has led to an economic activity. It remains unclear whether immediate and sudden spike in unemployment current unemployment figures have peaked or across several key economies—displacing whether job losses will deepen over time. New workers from their current roles. Since the end analysis conducted by the IMF has estimated of the Global Financial Crisis in 2007­2008, that 97.3 million individuals, or roughly 15% of economies across the globe had witnessed the workforce in the 35 countries included in a steady decrease of unemployment. Figure the analysis, are classified as being at high risk 3 presents the historical time series of of being furloughed or made redundant in the unemployment across a selection of countries current context.11 and regions. Annotated across the figure are the

The Future of Jobs 10 FIGURE 2 Countries enacting workplace closures, February­September 2020

27 Jan 2020 01 Feb 2020

01 Mar 2020

01 Apr 2020

01 May 2020

01 Jun 2020

01 Jul 2020

01 Aug 2020

01 Sep 2020

Source 28 Sep 2020 Hale, et al, 2020. 0

20 40 60 80 100 The Future of Jobs 11 Share of countries (%)

Fully open Partial closures All but essential work closed Countries have taken different approaches to tackling estimates such schemes have in recent months the pandemic, in the established provision of social subsidized the wages of close to 60 million workers.12 protection to displaced workers and in newly enacted While initially more temporary in nature, the persistence temporary government schemes targeted at job of limits to economic activity caused by COVID-19 has retention. This has created varied trajectories of led to an extension of several job retention schemes labour market disruption and recovery. For instance, up to the end of 2021 in an effort to prevent sudden several economies, such as Germany and Italy, spikes in unemployment.13 While such measures have have established large-scale temporary job retention meant that unemployment figures in those economies schemes including wage support measures (commonly have stayed relatively stable, it is yet to be seen if these called furlough schemes). According to the latest trends hold after they are lifted.

FIGURE 3 Unemployment rate, selected countries and regions, 1960­2020

35

Uneymployment rate (%) 20

1975 1982 1991 2009

5

0 1970 1980 1990 2000 2010 2020 1960 OECD countries Mexico Korea, Rep. South Africa USA EA17 Germany Canada Japan Italy United Kingdom France

Source Notes

OECD Economic Outlook: Statistics and Projections, and Kose, Forecasts for Q3 2020 produced by the OECD assuming two waves of M. Ayhan, et al. 2020. COVID-19, namely a “double hit” scenario. EA17 = Belgium, Germany, Estonia, Ireland, Greece, Spain, France, Italy, Cyprus, Luxembourg, Malta, Netherlands, Austria, Portugal, Slovenia, Slovakia, and Finland.

Comparing figures for quarter 2 of 2020 to the unemployment rate rose from 3.5% in February 2020 same quarter in 2019, unemployment in Australia to peak at 14.7% in April 2020. The unemployment increased by 1.5 percentage points; in Brazil that rate for the United States has now dropped to stand same figure was 1.6; in Canada, 6; in Chile, 5.5; closer to 10%. In contrast, during the Global Financial Columbia, 9; and United States, 8.5. The relevant Crisis in 2009 the unemployment rate in the United statistics for countries such as the United Kingdom, States rose from 4.7% in December 2007 to nearly Germany, Japan, France and Italy show greater 10% by June 2009.14 In two months the COVID-19 resilience. The Country Profiles in Part 2 of this report pandemic has destroyed more jobs than the Great present key labour market indicators showcasing the Recession did in two years. As the United States has latest annual, monthly and quarterly figures for the lifted restrictions on the physical movement of people, economies covered in this report, including the figures some workers have been recalled into employment listed above. It is evident that the United States and while others have seen temporary redundancies Canada experienced a significant disruption on an become permanent job displacement (some of this unprecedented scale. Employment figures for the data can be observed in Figure 11 on page 19). United States illustrated in Figure 4 show that the

The Future of Jobs 12 FIGURE 4 Unemployment rate in the United States, seasonally adjusted, 1967­2020

12

Uneymployment rate (%) 9

6

3 1970 1980 1990 2000 2010 2020 1967

Date

Source Notes United States Bureau of Labor Statistics. Unemployment Rate, also defined as the U-3 measure of labor underutilization, retrieved from FRED, Federal Reserve Bank of St. Louis

It appears increasingly likely that changes to reluctance to invest in new personnel. This means business practice brought about by this pandemic that workers displaced from the labour market have are likely to further entrench wholly new ways of fewer opportunities to return to work as businesses working, and that the second half of 2020 will not reduce their workforce. This trend can be observed see a return back to normal' but will instead see a through data from the professionals on the LinkedIn return to the new normal’. platform, which allows the LinkedIn Economic Graph team to track changes in hiring rates for seven key Early evidence from the World Economic Forum’s economies—Australia, China, France, Italy, Singapore, Future of Jobs Survey presented in Figure 5 the United Kingdom and the United States. Those suggests that, in addition to the labour market hiring rates are featured in Figure 6. They show that in displacement caused by this health shock, China, for instance, hiring contracted to a low of -47% employers are set to accelerate their job automation year-on-year rate at the end of February. In France and augmentation agenda, raising the possibility and Italy, the contraction was more pronounced, of a jobless recovery. Among the business reaching -70% and -64.5%, respectively, in mid-April. leaders surveyed, just over 80% report that they Those low figures were approached by the United are accelerating the automation of their work Kingdom and Australia, where contractions reached processes and expanding their use of remote work. a relatively more robust -40%. Since then, hiring rates A significant 50% also indicate that they are set to have gradually rebounded, with most of the seven key accelerate the automation of jobs in their companies. economies tracked by these metrics trending towards In addition, more than one-quarter of employers a 0% year-on-year change. By 1 July, China, France expect to temporarily reduce their workforce, and the United States had seen the most recovery in and one in five expect to permanently do so. The comparative hiring rates, at -6% or -7%. By the end of International Labour Organization (ILO) projects that September the countries with the strongest recovery by the second quarter of 2020, the equivalent of 195 in hiring were China (22%), Brazil (13%), Singapore million workers will have been displaced and as jobs (8%) and France (5%). In those economies it appears are transformed at a greater speed.15 that hiring is now compensating for the months in which new personnel were not engaged, indicating While many workers moved into unemployment some stabilization of the labour market. during the period of mid-March to the end of July hiring rates also remained low, reflecting business

The Future of Jobs 13 FIGURE 5 Planned business adaptation in response to COVID-19

Accelerate the digitalization of work processes 84 (e.g. use of digital tools, video conferencing) 83

Provide more opportunities to work remotely 50 42 Accelerate automation of tasks 35 34 Accelerate the digitalization of upskilling/reskilling 30 (e.g. education technology providers) 28

Accelerate the implementation of upskilling/reskilling programmes Accelerate ongoing organizational transformations (e.g. restructuring)

Permanently reduce workforce 13 Temporarily increase workforce 5

No specific measures implemented 4

Permanently increase workforce 1 40 60 80 100 0

Share of employers surveyed (%)

FIGURE 6 Hiring rate trends in selected countries, February­October 2020, year-on-year changes

80

Hiring rate, year-on-year (%) 40

0

-40

-80 01 Mar 01 Apr 01 May 01 Jun 01 Jul 01 Ago 01 Sep 25 Sep 12 Feb

Australia Brazil China France Italy Singapore United Kingdom United States

The Future of Jobs 14 FIGURE 7 Hiring rate trends in selected countries, by industry, April-September 2020, year-on-year changes

Industry Country/Economy April May June July August 25 September (month) (month) (month) (month) (month) (14-day rolling All

• 41% -39% -13% -11% 4% average)

Australia -34% -41% -23% -19% -3% Brazil -51% -46% -21% -8% -2% - 4% China -11% -11% 2% -8% 10% -11% France -67% -40% 3% -3% 24% 3% Italy -57% -48% -22% -13% 2% 11% Singapore -25% -39% 3% -9% 4% 3% United Kingdom -42% -45% -27% -19% -4% -11% -40% -39% -19% -11% 0% -5% United States - 61% -53% -27% -22% -5% -11% Consumer Goods -44% -50% -24% -21% -11% -11% -75% -50% -13% -12% 8% -14% Australia -76% -62% -35% -27% -8% -12% -56% -55% -40% -31% -11% -3% France -53% -48% -21% -16% -2% -31% -42% -38% -21% -13% 3% -8% Italy -19% -37% -27% -28% -1% -14% -72% -41% 1% -8% 12% -7% United Kingdom -48% -41% -31% -3% 7% -7% -39% -37% -34% -23% -13% 6% United States -33% -34% -14% -3% 9% -9% -23% -22% 6% 1% 23% -18% Finance -12% -26% -1% 6% 19% -6% -54% -19% 37% 10% 40% 8% Australia -29% -27% 2% 0% 26% 14% 10% -4% 1% -5% 18% 17% France -28% -33% -11% -6% 14% 1% -53% -45% -20% -18% 3% 7% Italy -34% -31% -18% -12% 3% 0% -71% -39% -1% -14% 20% -6% United Kingdom -61% -54% -34% -18% -4% 5% -51% -55% -38% -32% -4% -8% United States -47% -47% -12% -13% 3% -16% -79% -74% -43% -32% -20% -4% Health Care -77% -77% -51% -44% -43% -8% -82% -70% -15% -8% 11% -28% Australia -87% -78% -40% -28% -15% -50% -73% -77% -63% -50% -23% -5% France -75% -69% -44% -32% -28% n/a -53% -47% -15% -5% 13% -26% Italy -38% -44% -18% -6% 9% -31% -68% -38% 21% 9% 41% 4% United Kingdom -73% -58% -27% 7% 10% 5% -42% -48% -28% -22% 1% 20% United States -46% -48% -24% -13% 6% -1% Manufacturing -38% -36% -15% -22% -3% 2% -27% -37% -24% -23% -4% -8% Australia -61% -35% -7% -24% 0% -14% -43% -44% -24% -16% -2% -12% France -31% -39% -6% -27% -6% -20% -28% -26% -14% -22% -2% -10% Italy -16% -12%

Recreation & Travel

Retail United States

Software & IT Services

Source Note The darker the colour, the lower/higher the rate. LinkedIn Economic Graph. The Future of Jobs 15 Values in brown indicate where the hiring rate is lower than in 2019, while values in green indicate where the rate is higher than 2019. This tentative rebound is not equally distributed across In sum, unemployment and hiring rates suggest industries. Figure 7 shows the year-on-year change in a significant number of individuals were displaced hiring rates throughout April, May, June, July, August, across labour markets over the month of April 2020. and most of September for seven key industries and While those figures have stopped trending in a the seven economies tracked by LinkedIn. Among the negative direction in the period up to July 2020, this notable findings are those indicating a persistent hiring recovery remains tentative, with unequal geographic slump in Recreation and Travel, Consumer Goods and industry patterns. Longer persistence of these and Manufacturing. Also striking is that the Software trends is likely to entrench labour market scarring, and IT sector, which is not shedding jobs at the same lead to an overall reduction in employment and rate as other industries, is also not hiring at the same entrench worker displacement. rate as this time last year. The same observation also holds for the Finance Industry. It is perhaps not surprising that the Health and Healthcare industry has maintained the closest to comparable hiring rates to this time last year.

1.3 The remote and hybrid workforce

As a result of the twin forces of the Fourth Industrial given economy has been approximated at 38% of revolution and the COVID-19 recession, day-to-day jobs in high-income countries, 25% in upper-middle digitalization has leapt forward, with a large-scale income economies, 17% in lower-middle income shift to remote working and e-commerce, driving a economies and 13% in low-income economies.17 When surge in work-from-home arrangements and a new adjusted to account for disparities in internet access by marketplace for remote work. However, it has also economy, the same figures decrease to 33.6% of jobs brought about significant well-being challenges as in high income economies, 17.8% of jobs in upper- workers have struggled to adapt to new ways of middle income economies, 10% of jobs in lower-middle work over a short period of time. income economies, and just 4% of jobs in low income economies.18 Figure 8 plots the estimated share of In the COVID-19 context, workers have been workers unable to work remotely against the GDP per segmented into three categories: 1) essential capita for each country. According to such estimates workers' such as delivery personnel, carers and around 60% of workers in high-income countries such health workers, food shop workers, agricultural as the United States and Switzerland are unable to fully workers and manufacturers of medical goods; 2) work from home. This figure rises to more than 80-90% remote workers’ who can work remotely and are for economies such as Egypt and Bangladesh. likely to keep their jobs; and 3) `displaced workers’ who have been displaced from their jobs in the Sectoral differences underpin the estimates shared short term and potentially in the future, and who fall above. A larger share of roles in the Finance disproportionately into the sectors most negatively and Insurance and Information and Professional affected by the pandemic—Hospitality, Retail, Services sectors can be performed remotely, Service work as well as Travel and Tourism. while Accommodation and Food Services, Agriculture, Retail, Construction, Transportation and All three types of workers are facing a wholesale shift Warehousing offer fewer opportunities for remote in working practices, which now require new types of work.19 Figure 9 presents one estimate of the resilience and entail a reskilling or upskilling agenda. associated risk to employment across different sub- For essential workers, physical safety remains a industries: 47% of workers in the Accommodation paramount concern. Displaced workers are facing and Food Services sector, 15% in Wholesale significant job uncertainty, and a short-term or and Retail Trade and 15% of the workforce in permanent need to shift roles. Remote workers are Transportation are at risk of unemployment. faced with potential well-being and mental health challenges due to extensive changes to working Despite the limitations listed above, demand from practices as well as new areas of exclusion such as employers for remote-based work is increasing access to digital connectivity, living circumstances rapidly across economies. Insights from the and the additional care responsibilities faced by Glassdoor online platform show that access to parents or those looking after elderly relatives.16 working from home has nearly doubled since 2011, from 28% to 54% of workers mentioning that they New evidence from Chief Human Resource Officers had the opportunity to work from home.20 The completing the Forum’s Future of Jobs 2020 Survey industries with the largest opportunity to work from indicates that, on average, 44% of workers are able home are the Information Technology and Insurance to work remotely during the COVID-19 crisis while industries, with 74% of workers in those industries 24% of workers are unable to perform their current reporting having access to remote working. But there role. This estimate indicates an aspiration to expand are also industries such as Finance, Legal work and the availability of remote work. The current theoretical Business Services, which could, in theory, perform share of jobs that can be performed remotely in any more remote work.

The Future of Jobs 16 FIGURE 8 Estimated share of workers unable to work from home, by per capita GDP

100 Bangladesh

80 Brazil

Workers unable to work from home (%) Germany

Egypt United States

60 Argentina

Russian Federation Switzerland

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 0

GDP per capita (USD)

Dingel & Neuman, World Bank Home Based Work (HBW) index, World Bank’s World Development Indicators database.

FIGURE 9 Estimated share of workers at risk of unemployment, by sub-industry

Accommodation and Food Services 47% Wholesale and Retail Trade Transportation 15% Construction 15% 15% Health Care and Social Assistance Professional Services, Administrative and Support 15%

Government and Public Sector 14% Mining Agriculture 9%

Utilities 8%

7%

4%

0 20 40 60 80 100

At risk Not at risk

Brussevich, et al, 2020.

The Future of Jobs 17 Data shared by the LinkedIn Economic reflect a number of factors: 1) the switch to remote Graph team demonstrates that, in addition to work is occurring during a period of additional established patterns of working from home and stress and concern caused by the risk to life and the theoretical potential for at-home work, there health of the COVID-19 virus; 2) those caring after is actually an emerging marketplace for remote young children are faced with additional pressures— work­as evidenced by both strong demand from needing to take on more unpaid care work due to jobseekers21 as well as an increasing demand the intermittence of school and nursery arrangement; from employers for jobs that are based remotely.22 3) while companies with established remote work The index of job searches and job postings practices are accustomed to a range of approaches displayed in Figure 10 show that the amount of to maintaining a sense of community, of active workers looking for remote job opportunities has collaboration and ensuring a flow of communication, nearly doubled, while the number of job postings newly remote companies are still establishing these (controlling for shifts in hiring rates) has gradually ways of communicating and coordinating in the new, increased—with peaks of a two-fold increase in post-pandemic world of work. mid-April and a three-fold increase in mid-June.23 In addition, workers in those industries surveyed for The Future of Jobs Survey indicates that company the LinkedIn Workforce Confidence Index believe adaptation to the newly remote and hybrid there is potential to expand the use of remote work workplace is already underway. Ensuring employee beyond what it has been historically to match the well-being is among the key measures undertaken theoretical potential of working from home.24 by business leaders looking to effectively shift to remote work. In particular, 34% of leaders report The pandemic has shown that a new hybrid way that they are taking steps to create a sense of of working is possible at greater scale than imaged community among employees online and looking to in previous years, yet business leaders remain tackle the well-being challenges posed by the shift uncertain about the productivity outcomes of the to remote work. shift to remote or hybrid work. Overall, 78% of business leaders expect some negative impact of the current way of working on worker productivity, with 22% expecting a strong negative impact and only 15% believing that it will have no impact or a positive impact on productivity. Such scepticism is likely to

FIGURE 10 The new marketplace for remote work

A. Changes to job-seeking behaviour, February-June 2020 B. Changes to job-posting behaviour, February-June 2020

300 300

Index of job searches, % (relative to 11 Feb)250 250 Index of job postings, % (relative to 11 Feb) 200 200

150 150

100 100

50 50

0 10 Mar 07 Apr 05 May 02 Jun 30 Jun 0 05 Apr 03 May 07 Jun 28 Jun 11 Feb 11 Feb 08 Mar

The Future of Jobs 18 1.4 Impact on equality

The individuals and communities most affected out of employment and become displaced workers,29 by the unprecedented changes brought about by 14% of workers were initially displaced and then COVID-19 are likely to be those which are already recalled by their companies, and just 5% made most disadvantaged—living in neighbourhoods with successful transitions elsewhere in the labour market poor infrastructure, who have poor employment (Figure 11). The data shows variations by gender, prospects and whose income does not equip age and wage level. As revealed in Figure 12, them with a comfortable living standard, healthcare women make up a smaller share of both those who coverage or savings.25 Furthermore, across several were retained by companies and of those who are countries, the pandemic is set to broaden. An recalled. Displaced workers are in fact on average estimated 88 to 115 million people could fall more female, younger and have a lower wage. back into extreme poverty in 2020 as a result of this recession.26 The following wide array of The metrics shared by ADPRI also reveal the effect of characteristics typically pose a risk of social and this disruption by industry and wage level. Figure 13 economic exclusion among these populations: age A details the industries which are most affected by and generation; gender and gender expression; the current disruption; in particular, workers in Arts, sexual orientation; mental and physical abilities; level Entertainment, and Recreation, and Accommodation of health; race, ethnicity and religion; in-country and Food Services. Significant numbers of workers geographic location, such as rural and urban. These have also been displaced from the Retail sector as characteristics are typically reflected in outcomes well as from the Real Estate, Rental and Leasing such as levels of education, employment type, sector. In addition to this measure of attrition, Figure income level and socio-economic status.27 13 B presents an overview of the workers who transitioned in and out of jobs during the same In some countries those affected have been period; in effect, the re-allocation of workers by disproportionately women, for whom the ILO reports industry sector. The data shows that, on average, higher unemployment rates. This is the case in the workers who did transition moved towards sectors United States, Germany and Australia. In the United which provide essential services such as Retail States between December and April 2020, women’s and Health, as well as sectors which have been unemployment rose by 11% while the same figure less disrupted, such as Financial Services and for men was 9%. In Germany those figures were Construction. Across these transitions, workers 1.6% and 0.8%, respectively. New sources of data were also able to increase their wages. By contrast, can add more granularity to these trends. ADP struggling sectors such as Arts, Entertainment and Research Institute (ADPRI) has been able to track Recreation as well as Accommodation and Food the impact of COVID-19 on the United States labour Services gained fewer workers than they lost in market in near real time.28 The data shows that, the February to May period—and workers who within the observable shifts of workers’ employment transitioned to those sectors appear to have taken a over the period of February to May, 25% of workers pay cut, suggesting necessity rather than desirability left or were asked to leave their current role. Of those dictated the change. 25%, 82% of workers tracked by APDRI dropped

FIGURE 11 Outcomes for workers who lost their jobs in the United States, February­May 2020, by gender

Transitioned Transitioned Transitioned 5% 5% 5%

Recalled A. Overall Recalled Recalled C. Men workers workers workers Displaced 14% 12% 15% workers B. Women The Future of Jobs 19 Displaced Displaced workers workers 82% 83%

FIGURE 12 Retained, recalled, transitioned and displaced workers in the United States, by gender and by category of affected worker

Retained workers 45% 55% Male - age: 43, wage ($): 32 Female - age: 42, wage ($): 26 56% Male - age: 44, wage ($): 52 50% Male - age: 37, wage ($): 24 Recalled workers 44% 49% Male - age: 39, wage ($): 22 Female - age: 40, wage ($): 32

Workers transitioned to new company

Female - age: 36, wage ($): 20 50%

Displaced workers 51% Female - age: 38, wage ($): 18

Female Male

Figures 13 C and 13 D present the wage and age basic education as 7.5%. The latest available figures dynamics of workers in the United States who were by economy are listed in the Country Profiles in Part retained, recalled, displaced or transitioned. The 2 of the report. It must be noted that such figures markers in brown denote displaced workers; in are still too rarely collected and that more timely gold, those who transitioned to new opportunities; unemployment figures remain unreliable. This trend in light blue, those who were recalled; and in dark can be further confirmed by focusing on country- blue, those who were retained. Those recalled into level data with strong availability. Figure 14 presents the labour market have the highest average wage of unemployment levels among workers in the United the four cohorts, and those who are displaced have States by education level over time. It shows that the lowest average wage. In Retail, those who were the unemployment rate among those with less than displaced earn on average a low $17.80 an hour secondary education peaked at 21.2% in April, and while those recalled are earning $27.00 an hour. In stills stands at 12.6% as of the end of August. On Information and Media, those displaced earn $28.70 the other hand, unemployment levels among workers an hour while those recalled earn $61.20 an hour. who hold at least a tertiary degree spiked at 8.4% in April and stands at 5.3% as of the end of August. In addition, retained and recalled workers are, on Comparing the impact of the Global Financial Crisis average older, aged 40 and above, while displaced of 2008 on individuals with lower education levels to workers are more typically in their mid-to-late thirties the impact of the COVID-19 crisis, it is clear that the or have just turned 40. For example, in Education impact today is far more significant and more likely to Services, those displaced are on average aged 35, deepen existing inequalities. while those retained at nearing 43. In Retail and in Accommodation and Food Services these average ages are distorted by the relative youth of both sectors. In Retail, the average age for a displaced worker is 34, while those retained are nearing 40. Across the board, younger workers (those in their 30s) are more likely to have transitioned to new roles during these uncertain times.

Across established labour market indicators, unemployment figures for those with basic education are typically higher than for those who have completed a tertiary education degree. Current ILO figures list unemployment levels among those with an advanced degree as 6.5% and among those with

The Future of Jobs 20 FIGURE 13 Retained, transitioned, recalled and displaced workers in the United States, 1/2 by industry, age and hourly wage

A. Affected workers by sub-industry

0 20 40 60 80 100

Retained Recalled Transitioned Displaced

B. Worker transitions into sub-industries, by relative volume of transitions and wage change accepted

Financial Services and Insurance (wage change: 19%) 41% Retail (wage change: 3%) 26% Government and Public Sector (wage change: 14%) 26% Health and Healthcare (wage change: 6%) Construction (wage change: 16%) 15% Information and Media (wage change:13%) 13% Manufacturing (wage change: 10%) Transportation and Warehousing (wage change: 8%) 0% Professional, Scientific and Technical Services (wage change: 14%) -4% Wholesale Trade (wage change: 6%) -5% Office and Facilities Support Services (wage change: 14%) -5% -7% Education Services (wage change: 1%) -7% Real Estate, Rental and Leasing (wage change: 7%) -11% -16% Other Services (wage change: 4%) Management of Companies and Enterprises (wage change: 9%) -28% -31% Accomodation and Food Services (wage change -6%) -39% Arts, Entertainment and Recreation (wage change: -6%)

-60 -40 -20 0 20 40 60

Change between those transitioning in and out of industries (%)

Note

The wage change value shows the difference of starting and ending wage as a share of the starting wage. It is calculated from data showing transitions from one industry to another as the unweighted median wage change of transitions from all other industries into the destination industry.

The Future of Jobs 21 FIGURE 13 Retained, transitioned, recalled and displaced workers in the United States, 2/2 by industry, age and hourly wage

C. Affected workers by sub-industry and age

30 32 34 36 38 40 42 44 46 48 50

Average age of workers

Retained Recalled Transitioned Displaced

D. Affected workers by industry and wage

10 20 30 40 50 60 70 80 90 100

Average hourly wage (USD)

Retained Recalled Transitioned Displaced

The Future of Jobs 22 FIGURE 14 Unemployment rate in the United States by educational attainment, seasonally adjusted, 2000­2020

Unemployment rate (%) 15

5

0 2005 2010 2015 2020 2001 Secondary non-tertiary education Tertiary education Less than secondary education Short-cycle tertiary education

Source Note United States Bureau of Labor Statistics. Short-cycle tertiary education provides professional knowledge, skills and competencies. Typically, programmes are practically based and occupationally-specific.

Finally, such turbulent labour markets provide young professionals have targeted for their job additional challenges to young professionals transitions after entering the world of work in one of navigating their entry into working life. The FutureFit the six industries most affected by the COVID-19 AI global data map combines job automation pandemic. Figure 17 illustrates those next-step and growth forecasts, real-time labour market possible opportunities, which include new roles in information, learner resumes and the professional the Healthcare, Financial Services, Not-for-Profit and profiles of individuals. As such, it can track the Information, Technology and Services industries— historic job trajectories of professionals through roles such as Credit Analysts, Bank Tellers and different roles and industries,30 and in this instance Public Relations Coordinators in the Not-for-Profit the transition of young professionals who are sector, Certified Nursing Assistants in Healthcare, in their first decade of working life in the United and Account Executives in the Information States observed between 2008 and 2019.31 The Technology and Services sector. data in Figure 15 A reveals that, historically, the Retail, Restaurants, Hospitality, and the Food & This willingness to transition to new job Beverage sectors, as well some parts of Higher opportunities, matched with new reskilling and Education, have been among the top 20 starter- upskilling capabilities, can help place young sectors for young people. However, as Figure 15 B professionals back on track, helping them find routes indicates, these industries maintain a high attrition from affected to new, growing opportunities. While rate as workers tend to be transient. Thirty-seven the data shared above suggests that businesses percent of young professionals who work in Retail and individuals have taken on significant initiative use the industry as a stepping-stone to another to adapt to the current labour market, economic career and have historically moved onto another scarring and persistent damage to the labour market industry beyond the six affected sectors. The have the potential to limit the scale of opportunities same figure is at 32% for those in the Restaurant available to workers. However, governments have at sector. As roles in these sectors are temporarily their disposal a range of tools that can alleviate the or permanently displaced, those at the start of impact on workers as economies recover. their careers will need to re-route and leapfrog into aspirational opportunities to work in high quality, well-remunerated jobs.

Figure 16 presents FutureFit AI data that documents past labour market transitions of young professionals over a decade. It shows the kinds of industries

The Future of Jobs 23 FIGURE 15 Relationship between youth job transitions and affected industries

A. Youth first jobs, by sub-industry

Higher Education

Hospital & Health Care

Military

Non-Profit Organization Management Education Management

Information Technology and Services Government Administration Food & Beverages Entertainment Marketing and Advertising Banking

0 2 4 6 8 10 12 14 16 18 20

B. Youth transcience through affected sub-industries

Higher Education 39% Retail 37% 36% Entertainment 35% Food & Beverages 32% 32%

0 20 40 60 80 100

Stay in sub-industry Transition to one of the six affected industries Transition out of the six affected industries

FutureFit AI, produced for the World Economic Forum’s New

In previous recessions, the long-term impact on The early indicators shared in this section signal earnings among young people resulted in persistent that without adequate intervention, gains towards earnings declines lasting up to 10 years, as young bridging societal inequalities might be reversed professionals started to work for lower-paying and wages further polarized. While data for the employers, then partly recover through a gradual United States cannot be generalized to the world, process of mobility toward better firms. We have the availability of such granular insights in this one also seen young professionals start to work in economy serves as a stark reminder of the potential occupations that do not match their education impact of these disruptions on equality within and levels.32 As we consider the ways to revive the across all economies. labour market, such insights can point to ways in which data-driven re-employment can support not only re-entry into one’s original industry or to an adjacent one, but also provide accelerated transitions to the ultimate career designation aspired to by young professionals.

The Future of Jobs 24 FIGURE 16 Primary possible transitions for affected young professionals

Destination sub-industry

Source Apparel & Broadcast Education Financial Hospital & Non-Profit Information Marketing and Real sub-industry Fashion Media Management Services Health Care Organization Technology Advertising Estate Management and Services Entertainment - 4% 5% - Food & - 4% - 4% - 5% -

Beverages - - 4% 5% 6% 5% 3% - - Higher - 4%

• • 4% 4% 9% 6% 4% -

Education 5% - Hospitality - - 7% 7% 5% - 4% -

• 3% 5% 8% 6% 3% -
• 4% 6% 8% 4% - -

Source Note

FutureFit AI, produced for the World Economic Forum’s New Values refer to share of workers transitioning from source sub- Metrics CoLab. industry to destination sub-industry.

FIGURE 17 In-focus transitions for affected young workers

Higher Education Registered Nurse Hospital and Health Care Restaurants Bank Teller Information Technology Retail and Services Software Engineer Education Management Food & Beverages Personal Banker Non-Profit Organization Entertainment Account Executive Management Hospitality Financial Representative Financial Analyst The Future of Jobs 25 Customer Service Representative Certified Nursing Assistant Substitute Teacher

Consultant Sales Associate Medical Assistant Pharmacy Technician

Teacher Nursing Assistant

Social Worker Tutor

Applications Analyst Web Developer

size = share of transitions

FutureFit AI, produced for the World Economic Forum’s New

2 Forecasts for Labour Market Evolution in 2020-2025

Over the past five years, the World Economic the following chapter tracks technological adoption Forum has tracked the arrival of the future of work, among firms alongside changing job requirements identifying the potential scale of worker displacement and skills demand. These qualitative survey due to technological automation and augmentation responses are further complemented by granular alongside effective strategies for empowering job data from new sources derived from privately-held transitions from declining to emerging jobs. At the data that tracks key jobs and skills trends. Together, core of the report and its analysis is the Future of these two types of sources provide a comprehensive Jobs survey, a unique tool which assess the short- overview of the unfolding labour market trends as and long-term trends and impact of technological well as an opportunity to plan and strategize towards adoption on labour markets. The data outlined in a better future of work.

The Future of Jobs 26 2.1 Technological adoption

The past two years have seen a clear These new technologies are set to drive future acceleration in the adoption of new technologies growth across industries, as well as to increase among the companies surveyed. Figure 18 the demand for new job roles and skill sets. presents a selection of technologies organized Such positive effects may be counter-balanced according to companies’ likelihood to adopt by workforce disruptions. A substantial amount them by 2025. Cloud computing, big data and of literature has indicated that technological e-commerce remain high priorities, following a adoption will impact workers’ jobs by displacing trend established in previous years. However, some tasks performed by humans into the realm there has also been a significant rise in interest of work performed by machines. The extent of in encryption, reflecting the new vulnerabilities disruption will vary depending on a worker’s of our digital age, and a significant increase in occupation and skill set.33 the number of firms expecting to adopt non- humanoid robots and artificial intelligence, with Data from the Forum’s Future of Jobs Survey both technologies slowly becoming a mainstay of shows that companies expect to re-structure work across industries. their workforce in response to new technologies (Figure 20). In particular, the companies surveyed These patterns of technological adoption vary indicate that they are also looking to transform according to industry. As demonstrated in Figure the composition of their value chain (55%), 19, Artificial intelligence is finding the most broad introduce further automation, reduce the current adaptation among the Digital Information and workforce (43%) or expand their workforce as a Communications, Financial Services, Healthcare, result of deeper technological integration (34%), and Transportation industries. Big data, the and expand their use of contractors for task- Internet of Things and Non-Humanoid Robotics specialized work (41%). are seeing strong adoption in Mining and Metals, while the Government and the Public Sector industry shows a distinctive focus on encryption.

FIGURE 18 Technologies likely to be adopted by 2025 (by share of companies surveyed)

Cloud computing (17%) 20 40 60 80 100 Big data analytics (2%) Internet of things and connected devices (9%) Encryption and cybersecurity (29%) Artificial intelligence (inc. ML and NLP) (8%) Text, image and voice processing (-) E-commerce and digital trade (2%) Robots, non-humanoid (e.g industrial automation, drones) (10%) Augmented and virtual reality (1%) Distributed ledger technology (e.g. blockchain) (11%) 3D and 4D printing and modelling (10%) Power storage and generation (-) New materials (e.g. nanotubes, graphene) (-12%)

Biotechnology (8%) Robots, humanoid (11%) Quantum computing (-5%)

0

Share of company surveyed (%)

2025 2018 Difference

The Future of Jobs 27 The reallocation of current tasks between human machines at work will be at parity based on and machine is already in motion. Figure 21 today’s tasks. Algorithms and machines will be presents the share of current tasks at work primarily focused on the tasks of information performed by human vs. machine in 2020 and and data processing and retrieval, administrative forecasted for 2025 according to the estimates tasks and some aspects of traditional manual and planning of senior executives today. One labour. The tasks where humans are expected of the central findings of the Future of Jobs to retain their comparative advantage include 2018 Report continues to hold—by 2025 the managing, advising, decision-making, reasoning, average estimated time spent by humans and communicating and interacting.

FIGURE 19 Technologies likely to be adopted by 2025, by share of companies surveyed, selected sectors

Technology/Sector AGRI AUTO CON DIGICIT EDU ENG FS GOV HE MANF MIM OILG PS TRANS (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%)

3D and 4D printing 54 67 39 39 69 69 27 45 65 69 48 79 40 60

and modelling

Artificial intelligence

(e.g. machine 62 76 73 95 76 81 90 65 89 71 76 71 76 88 learning, neural

Augmented and 17 53 58 73 70 75 62 56 67 54 57 71 57 62 virtual reality

Big data analytics 86 88 91 95 95 76 91 85 89 81 90 86 86 94

Biotechnology 50 18 48 40 46 47 46 38 65 31 16 36 28 23

Cloud computing 75 80 82 95 95 88 98 95 84 92 87 86 88 94

Distributed ledger

technology (e.g. 31 40 41 72 61 50 73 40 72 41 50 46 53 38

blockchain)

E-commerce and 80 75 85 82 72 71 90 67 78 82 62 62 70 87 digital trade

Encryption and cyber 47 88 85 95 86 88 95 95 84 72 83 71 78 75

security

Internet of things and 88 82 94 92 62 94 88 79 95 84 90 93 74 76

connected devices

New materials 15 46 22 36 67 65 36 33 47 51 37 36 27 27 (e.g. nanotubes,

graphene)

Power storage and 75 64 59 38 27 88 55 33 31 62 57 69 45 46 generation

Quantum computing 18 21 17 51 25 41 44 36 38 21 29 25 19 38

Robots, humanoid 42 50 38 44 47 24 47 31 47 41 15 17 25 21

Robots, non-

humanoid (industrial 54 60 52 61 59 65 53 50 56 79 90 79 35 69 automation, drones,

etc.)

Text, image and 50 59 82 90 89 88 88 89 88 64 76 87 79 65 voice processing

Source Note AGRI = Agriculture, Food and Beverage; AUTO = Automotive; CON = Consumer; DIGICIT = Digital Communications and Information Technology; EDU = Education; ENG = Energy Utilities & Technologies; FS = Financial Services; GOV = Government and Public Sector; HE = Health and Healthcare; MANF = Manufacturing; MIM = Mining and Metals; OILG = Oil and Gas; PS = Professional Services; TRANS = Transportation and Storage.

The Future of Jobs 28 FIGURE 20 Companies’ expected changes to the workforce by 2025 (by share of companies surveyed)

Modify the composition of one’s value chain 55.1 Reduce current workforce due to technological integration 43.2 41.8 or automation 38.3 Expand use of contractors doing task-specialized work 34.5 32.4 Modify the locations where the organization operates 15 Expand current workforce due to technological integration 10 20 30 40 50 60 or automation Expand current workforce Share of company surveyed (%) Reduce current workforce

0

FIGURE 21 Share of tasks performed by humans vs machines, 2020 and 2025 (expected), by share of companies surveyed

Information and data processing Looking for and receiving job-related information

0 20 40 60 80 100

Share of task hours (%)

Machine 2020 Human 2020 Machine 2025 Human 2025

Human-machine frontier 2025

2.2 Emerging and declining jobs

Extrapolating from the figures shared in the Future to the new division of labour between humans, of Jobs Survey 2020, employers expect that by machines and algorithms, across the 15 industries 2025, increasingly redundant roles will decline from and 26 economies covered by the report. being 15.4% of the workforce to 9% (6.4% decline), and that emerging professions will grow from 7.8% The 2020 version of the Future of Jobs Survey to 13.5% (5.7% growth) of the total employee also reveals similarities across industries when base of company respondents. Based on these looking at increasingly strategic and increasingly figures, we estimate that by 2025, 85 million jobs redundant job roles. Similar to the 2018 survey, may be displaced by a shift in the division of labour the leading positions in growing demand are roles between humans and machines, while 97 million such as Data Analysts and Scientists, AI and new roles may emerge that are more adapted Machine Learning Specialists, Robotics Engineers,

The Future of Jobs 29 Software and Application developers as well as Accounting and Bookkeeping and Payroll Clerks, Digital Transformation Specialists. However, job Accountant and Auditors, Assembly and Factory roles such as Process Automation Specialists, Workers, as well as Business Services and Information Security Analysts and Internet of Things Administrative Managers. Specialists are newly emerging among a cohort of roles which are seeing growing demand from Such job disruption is counter-balanced by job employers. The emergence of these roles reflects the creation in new fields, the `jobs of tomorrow’. Over acceleration of automation as well as the resurgence the coming decade, a non-negligible share of newly of cybersecurity risks. created jobs will be in wholly new occupations, or existing occupations undergoing significant In addition, as presented in the Industry Profiles in transformations in terms of their content and skills Part 2 of this report, a set of roles are distinctively requirements. The World Economic Forum’s Jobs emerging within specific industries. This includes of Tomorrow report, authored in partnership with Materials Engineers in the Automotive Sector, data scientists at partner companies LinkedIn and Ecommerce and Social Media Specialists in the Coursera, presented for the first time a way to Consumer sector, Renewable Energy Engineers in measure and track the emergence of a set of new the Energy Sector, FinTech Engineers in Financial jobs across the economy using real-time labour Services, Biologists and Geneticists in Health and market data.35 The data from this collaboration Healthcare as well as Remote Sensing Scientists identified 99 jobs that are consistently growing in and Technicians in Mining and Metals. The nature of demand across 20 economies. Those jobs were these roles reflects the trajectory towards areas of then organized into distinct professional clusters innovation and growth across multiple industries. according to their skills similarity.

At the opposite end of the scale, the roles which This resulting set of emerging professions reflects are set to be increasingly redundant by 2025 remain the adoption of new technologies and increasing largely consistent with the job roles identified in demand for new products and services, which are 2018 and across a range of research papers on the driving greater demand for green economy jobs, automation of jobs.34 These include roles which are roles at the forefront of the data and AI economy, being displaced by new technologies: Data Entry as well as new roles in engineering, cloud computing Clerks, Administrative and Executive Secretaries, and product development. In addition, the emerging

FIGURE 22 Top 20 job roles in increasing and decreasing demand across industries

Increasing demand Decreasing demand

1 Data Analysts and Scientists 1 Data Entry Clerks

2 AI and Machine Learning Specialists 2 Administrative and Executive Secretaries

3 Big Data Specialists 3 Accounting, Bookkeeping and Payroll Clerks

4 Digital Marketing and Strategy Specialists 4 Accountants and Auditors

5 Process Automation Specialists 5 Assembly and Factory Workers

6 Business Development Professionals 6 Business Services and Administration Managers

7 Digital Transformation Specialists 7 Client Information and Customer Service Workers

8 Information Security Analysts 8 General and Operations Managers

9 Software and Applications Developers 9 Mechanics and Machinery Repairers

10 Internet of Things Specialists 10 Material-Recording and Stock-Keeping Clerks

11 Project Managers 11 Financial Analysts

12 Business Services and Administration Managers 12 Postal Service Clerks

13 Database and Network Professionals 13 Sales Rep., Wholesale and Manuf., Tech. and Sci.Products

14 Robotics Engineers 14 Relationship Managers

15 Strategic Advisors 15 Bank Tellers and Related Clerks

16 Management and Organization Analysts 16 Door-To-Door Sales, News and Street Vendors

17 FinTech Engineers 17 Electronics and Telecoms Installers and Repairers

18 Mechanics and Machinery Repairers 18 Human Resources Specialists

19 Organizational Development Specialists 19 Training and Development Specialists

20 Risk Management Specialists 20 Construction Laborers

The Future of Jobs 30 professions showcase the continuing importance these so-called jobs of tomorrow' present greater of human interaction in the new economy through opportunities for workers looking to fully switch their roles in the care economy; in marketing, sales and job family and therefore present more options to content production; as well as roles where a facility reimagine one's professional trajectory, while other or aptitude for understanding and being comfortable emerging professions remain more fully bounded. working with different types of people from different As presented in Figure 24 C only 19% and 26% backgrounds is critical. Figure 23 displays the set of job transitions into Engineering and People and of roles which correspond to each professional Culture, respectively, come from outside the job cluster, organized according to the scale of each family in which those roles are today. In contrast, opportunity.36 Due to constraints related to data 72% of Data and AI bound transitions originate from availability, the Care and Green Jobs cluster are not a different job family and 68% of transitions into currently covered by the following analysis. emerging jobs within Sales. As illustrated in Figure 25 emerging job clusters are typically staffed by In this report we present a unique extension of this workers starting in a set of distinctive job families, analysis which examines key learnings gleaned from but the diversity of those source job families varies job transitions into those emerging clusters using by emerging profession. While emerging roles in LinkedIn data gathered over the past five years. Product Development draw professionals from For this analysis the LinkedIn data science team a range of job families, emerging roles in People analysed the job transitions of professionals who and Culture job cluster typically transition from the moved into emerging jobs over the period of 2015 to Human Resources job family. The emerging Cloud 2020. The researchers analysed when professionals Computing job cluster is primarily populated by transitioned into any new role as well as when they professionals transitioning from IT and Engineering. transitioned to a wholly new occupation--here called pivots’. To understand the skill profile of Finally, a number of jobs of tomorrow present each occupation, analysts first identified a list of greater opportunities to pivot into professions with the most representative skills associated with an a significant change in skills profile. In Figure24 B it occupation, based on LinkedIn’s Skills Genome is possible to observe that transitions into People Metric which calculates the most representative' and Culture and into Engineering have typically been skills across roles, using the TF-IDF method. To ones with high skills similarity while Marketing and examine the extent to which certain skills groups of Content Development have been more permissive of interest are associated with a particular occupation, low skills similarity. Among the emerging professions a skill penetration’ figure is calculated. This indicates outlined in this report, transitions into Data and AI the share of individual skills associated with that allow for the largest variation in skills profile between occupation that belong to a given skill group. To source and destination job title. understand the skill profile of each occupation, analysts calculated the skill penetration' score for Figure 25 demonstrates that the newer emerging each skill associated with an occupation. That is, the professions such as Data and AI, Product skill penetration’ figure indicates the individuals from Development and Cloud Computing present more that occupation who list the specific skill as a share opportunities to break into these frontier fields, and of all individuals employed in that occupation. that, in fact, such transitions do not require a full skills match between the source and destination The aggregate skills similarity between two occupation. However, some job clusters of tomorrow occupations is then calculated as the cosine remain more closed' and tend to recruit staff with similarity of those two occupations. In addition, for a very specific skill set. It is not possible to observe each skill group, a skills gap measure is calculated whether those limitations are necessary or simply by expressing the skill penetration of the established practice. It may be the case that such destination job as a share of the same indicator in siloed’ professional clusters can be reinvigorated the source job. by experimentation with relaxing the constraints for entry into some emerging jobs alongside appropriate The evidence indicates that some emerging reskilling and upskilling. job clusters present significant opportunities for transitions into growing jobs (jobs in increasing demand) through effective career pivots. As demonstrated in Figure24 A, among the transitions into Data and AI professions, 50% of the shifts made are from non-emerging roles. That figure is much higher at 75% in Sales, 72% in content roles and 67% of Engineering roles. One could say that such field are easier to break into, while those such as Data and AI and People and Culture present more challenges. These figures suggest that some level of labour force reallocation is already underway.

By analysing these career pivots—instances where professionals transition to wholly new occupations—it becomes apparent that some of

The Future of Jobs 31 FIGURE 23 Emerging roles clustered into the jobs of tomorrow

Care Economy Green Economy

Cloud Computing Marketing

1 Site Reliability Engineer 1 Growth Hacker 2 Platform Engineer 2 Growth Manager 3 Cloud Engineer 3 Digital Marketing Specialist 3 DevOps Engineer 4 Digital Specialist 5 Cloud Consultant 5 Ecommerce Specialist 6 DevOps Manager 6 Commerce Manager 6 Head Of Digital Content Production 8 Digital Marketing Consultant 9 Digital Marketing Manager 1 Social Media Assistant 10 Chief Marketing Officer 2 Social Media Coordinator 3 Content Specialist People and Culture 4 Content Producer 5 Content Writer 1 Information Technology Recruiter 6 Creative Copywriter 2 Human Resources Partner 3 Talent Acquisition Specialist Data and AI 4 Business Partner 5 Human Resources Business Partner 1 Artificial Intelligence Specialist 2 Data Scientist Product Development 3 Data Engineer 4 Big Data Developer 1 Product Owner 5 Data Analyst 2 Quality Assurance Tester 6 Analytics Specialist 3 Agile Coach 7 Data Consultant 4 Software Quality Assurance Engineer 8 Insights Analyst 5 Product Analyst 9 Business Intelligence Developer 6 Quality Assurance Engineer 10 Analytics Consultant 6 Scrum Master 8 Digital Product Manager Engineering 9 Delivery Lead

1 Python Developer Sales 2 Full Stack Engineer 2 Javascript Developer 1 Customer Success Specialist 4 Back End Developer 2 Sales Development Representative 5 Frontend Engineer 3 Commercial Sales Representative 5 Software Developer Dotnet 4 Business Development Representative 7 Development Specialist 5 Customer Specialist 8 Technology Analyst 6 Partnerships Specialist 7 Chief Commercial Officer 8 Head Of Partnerships 9 Enterprise Account Executive 10 Business Development Specialist 11 Chief Strategy Officer 12 Head Of Business Development

Rank Niche Mass

The Future of Jobs 32 FIGURE 24 Transitions and pivots into the jobs of tomorrow, selected countries

A. Transition by occupation and job cluster of source occupation

Product Development People and Culture

Content Production

0 20 40 60 80 100

Same occupation Same emerging job cluster Any emerging cluster Any occupation outside emerging cluster

B. Job pivots by skills similarity with source occupation

Cloud Computing 2% 76% 22% Data and AI 7% 43% 50% 20% Product Development 0 21% Sales 21% 56% 59% 22% 22% 60% 57% 22% Content Production 43% 19% Marketing 35% 42% 37% 12% People and Culture 100 Engineering 25%

27%

20 40 60 80

High similarity Medium similarity Low similarity

C. Job pivots by job family of source occupation

Product Development 28% 72% Data and AI 28% 72% 32% 68% Content Production 47% 53% Marketing 55% 50% People and Culture 45%

Engineering 74% 26% 0 81% 19% 20 60 80 100

No change in job family Change in job family

Source Note Data derived from the following countries Job transitions refers to any job transition while job pivots Argentina, Australia, Brazil, Canada, France, Germany, India, refers to individuals moving away from their current occupation. Ireland, Italy, Mexico, Netherlands, New Zealand, Saudi Job Families are groups of occupations based upon work Arabia, Singapore, South Africa, Spain, Sweden, United Arab performed, skills, education, training, and credentials. Emirates, United Kingdom and United States.

The Future of Jobs 33 FIGURE 25 Transitions into the jobs of the future

Source job family

Marketing Destination job of tomorrow Information Technology Cloud Computing Human Resources People and Culture Sales Product Development Media and Communication Content Business Development Research The Future of Jobs 34

Program and Project Management Operations

Quality Assurance Support

Administrative Product Management Arts and Design

Finance Community and Social Services

Consulting Accounting Real Estate Purchasing

Legal Healthcare Services Military and Protective Services

Entrepreneurship

2.3 Emerging and declining skills

FIGURE 26 The ability of global companies to harness the Skill shortages are more acute in emerging growth potential of new technological adoption is professions. Asked to rate the ease of finding skilled hindered by skills shortages. Figure 26 shows that employees across a range of new, strategic roles, skills gaps in the local labour market and inability business leaders consistently cite difficulties when to attract the right talent remain among the leading hiring for Data Analysts and Scientists, AI and barriers to the adoption of new technologies. This Machine Learning Specialists as well as Software finding is consistent across 20 of the 26 countries and Application Developers, among other emerging covered by the Country Profiles presented in Part roles. While an exact skills match is not a prerequisite 2 of the report. In the absence of ready talent, to making a job transition, the long-term productivity employers surveyed through the Future of Jobs of employees is determined by their mastery of key Survey report that, on average, they provide access competencies. This section of the report takes stock to reskilling and upskilling to 62% of their workforce, of the types of skills that are currently in demand and that by 2025 they will expand that provision to a as well as the efforts underway to fill that demand further 11% of their workforce. However, employee through appropriate reskilling and upskilling. engagement into those courses is lagging, with only 42% of employees taking up employer-supported reskilling and upskilling opportunities.

Perceived barriers to the adoption of new technologies

Skills gaps in the local labour market 46.7 55.4 Inability to attract specialized talent 41.4 60 38.9 Skills gaps among organization’s leadership 33 Insufficient understanding of opportunities 32.3 26.3 Lack of flexibility of the regulatory framework 17.9 5.3 20 30 40 50 Lack of flexibility in hiring and firing 10 Lack of interest among leadership Other 0

Since its 2016 edition, this report has tracked This report reveals in further granular detail the types the cross-functional skills which are in increasing of insights that can guide job transitions through to demand. Figure 27 shows the top skills and skill appropriate reskilling and upskilling. Figures 29 and groups which employers see as rising in prominence 30 demonstrate those metrics. Figure 29 presents the in the lead up to 2025. These include groups such set of high-growth, emerging roles that are currently as critical thinking and analysis as well as problem- covered by the Data and AI job cluster, and the typical solving, which have stayed at the top of the agenda skills gap between source and destination professions with year-on-year consistency. Newly emerging this when workers have moved into those roles over the year are skills in self-management such as active past five years. Figure 30 presents the typical learning learning, resilience, stress tolerance and flexibility. curriculum of Coursera learners who are targeting a In addition, the data available through metrics transition into Data and AI and the distance from the partnerships with LinkedIn and Coursera allow us optimal level of mastery in the relevant job cluster, to track with unprecedented granularity the types of and quantifies the days of learning needed for the specialized skills needed for the jobs of tomorrow. average worker to gain that level of mastery. Figures Figure 28 demonstrates the set of skills which are 29 and 30 together demonstrate that it is common in demand across multiple emerging professions. for individuals moving into Data and AI to lack key Among these `cross-cutting’ skills are specialized data science skills—but that individuals seeking to skills in Product Marketing, Digital Marketing and transition into such roles will be able to work towards Human Computer Interaction. the right skill set through mastery of skills such as statistical programming within a recommended time frame, in this case, 76 days of learning.

The Future of Jobs 35 FIGURE 27 Perceived skills and skills groups with growing demand by 2025, by share of companies surveyed

A. Relative importance of different skill groups

Critical thinking and analysis Problem-solving

Self-management Working with people Management and communication of activities Technology use and development

Core literacies Physical abilities

0 20 40 60 80 100

Decreasing Stable Increasing

B. Top 15 skills for 2025

1 Analytical thinking and innovation 9 Resilience, stress tolerance and flexibility

2 Active learning and learning strategies 10 Reasoning, problem-solving and ideation

3 Complex problem-solving 11 Emotional intelligence

4 Critical thinking and analysis 12 Troubleshooting and user experience

5 Creativity, originality and initiative 13 Service orientation

6 Leadership and social influence 14 Systems analysis and evaluation

7 Technology use, monitoring and control 15 Persuasion and negotiation

8 Technology design and programming

In addition to skills that are directly jobs-relevant, such as mindfulness, meditation, gratitude and during the COVID-19 context of 2020, data from kindness are among the top 10 focus areas of those the online learning provider Coursera has been in employment in contrast to the more technical able to identify an increasing emphasis within skills which were in-focus in 2019. In contrast, those learner reskilling and upskilling efforts on personal who are unemployed have continued to emphasize development and self-management skills. This skills which are of relevance to emerging jobs in echoes earlier findings on the importance of well- Engineering, Cloud Computing, Data and AI.37 being when managing in the remote and hybrid work: demand for new skills acquisition has When it comes to employers providing workers with bifurcated. Figure 31 A illustrates the changing training opportunities for reskilling and upskilling, in demand for training by employment status, contrast to previous years, employers are expecting comparing the April-to-June period this year with the to lean more fully on informal as opposed to formal same period last year. This data reveals a significant learning. In the Future of Jobs Survey, 94% of increase in demand for personal development business leaders report that they expect employees courses, as well as for courses in health, and a to pick up new skills on the job, a sharp uptake from clear distinction between those who are currently 65% in 2018. An organization’s learning curricula is in employment and those who are unemployed. expected to blend different approaches—drawing Those in employment are placing larger emphasis on internal and external expertise, on new education on personal development courses, which have seen technology tools and using both formal and informal 88% growth among that population. Those who methods of skills acquisition. are unemployed have placed greater emphasis on learning digital skills such as data analysis, computer science and information technology. These trends can be observed in more granular detail in Figures 31 B and C. In particular, self-management skills

The Future of Jobs 36 FIGURE 28 Top cross-cutting, specialized skills of the future

Specialized skill Emerging job clusters 1. Product Marketing 2. Digital Marketing Data and AI, People and Culture, Marketing, Product Development, Sales (5) 3. Software Development Life Cycle (SDLC) Content, Data and AI, Marketing, Product Development, Sales (5) 4. Business Management Cloud Computing, Data and AI, Engineering, Marketing, Product Development (5) 5. Advertising People and Culture, Marketing, Product Development, Sales (4) 6. Human Computer Interaction Content, Data and AI, Marketing, Sales (4) 7. Development Tools Content, Engineering, Marketing, Product Development (4) 8. Data Storage Technologies Cloud Computing, Data and AI, Engineering, Product Development (4) 9. Computer Networking Cloud Computing, Data and AI, Engineering, Product Development (4) 10. Web Development Cloud Computing, Data and AI, Engineering, Sales (4) 11. Management Consulting Cloud Computing, Content, Engineering, Marketing (4) 12. Entrepreneurship Data and AI, People and Culture, Product Development (3) 13. Artificial Intelligence People and Culture, Marketing, Sales (3) 14. Data Science Cloud Computing, Data and AI, Engineering (3) 15. Retail Sales Data and AI, Marketing, Product Development (3) 16. Technical Support People and Culture, Marketing, Sales (3) 17. Social Media Cloud Computing, Product Development, Sales (3) 18. Graphic Design Content, Marketing, Sales (3) 19. Information Management Content, Engineering, Marketing (3) Content, Data and AI, Marketing (3) LinkedIn Economic Graph. Note Cross-cutting skills are those skills that are applicable and easily transferable across many occupations and roles.

FIGURE 29 Data and AI jobs of tomorrow, top roles and typical skills in past transitions

A. Opportunities within professional cluster B. Typical skills gaps across successful job transitions

Rank Scale of Job Rank Skill Skill gap of workers opportunity transitioning into 1 Artificial Intelligence 1 Data Science this job cluster Mass Specialist 2 Data Storage Technologies (0 is full gap, 2 Data Scientist 3 Artificial Intelligence 1 is no gap) 3 Mass Data Engineer 4 Development Tools 4 Mass Big Data Developer 5 Computer Networking 0.19 5 Niche Data Analyst 6 Management Consulting 0.41 6 Mass Analytics Specialist 7 Scientific Computing 0.10 7 Mass Data Consultant 8 Product Marketing 0.73 8 Niche Insights Analyst 9 Natural Language Processing 0.78 9 Niche Business Intelligence 10 Digital Marketing 0.85 10 Developer 11 Advertising 0.41 Niche Analytics Consultant 12 Cloud Computing 1.00 13 Customer Experience 0.11 Mass 14 Signal Processing 1.00 15 Information Management 1.00 Source 16 Software Development Life Cycle (SDLC) 0.27 LinkedIn Economic Graph. 1.00 0.15 Note 0.93 The gap measure has been capped at 1.00. 1.00

The Future of Jobs 37 FIGURE 30 Data and AI jobs of tomorrow, typical learning agenda and time to achieve mastery in key skills

A. Typical learning agenda B. Top 10 skills by required level of mastery and time to achieve that mastery

Rank Skill Rank Skill Expected Typical Average 1 Data Analysis mastery score mastery gap days to 2 Computer Programming 1 Statistical Programming master skill 3 General Statistics 2 Communication (0 to 6, best) 54% 4 Leadership And Management 3 Leadership and Management 5.50 34% 72 5 Regression 4 Data Management 4.36 66% 80 6 Machine Learning 5 Marketing 3.61 45% 39 7 Big Data 6 Finance 3.61 55% 84 8 Python Programming 7 Sales 3.57 46% 43 8 Computer Programming 3.56 84% 67 Source 9 Business Analysis 3.43 41% 13 Coursera. 10 Machine Learning 3.43 65% 76 3.24 54% 34 3.06 86

Note transition to the occupation as a share of the score among those already in the occupation. Mastery score is the score attained by those in the top 80% on an assessment for that skill. Mastery gap is measured as a percentage representing the score among those looking to

According to data from the Future of Jobs Survey, of online learning. In fact, there has been a four-fold formal upskilling appears to be more closely increase in the numbers of individuals seeking out focused on technology use and design skills, while opportunities for learning online through their own emotional intelligence skills are less frequently initiative, a five-fold increase in employer provision targeted in that formal reskilling provision. Data from of online learning opportunities to their workers and Coursera showing the focus areas of workforce an even more extensive nine-fold enrolment increase recovery programmes and employer-led reskilling for learners accessing online learning through and upskilling activities confirms that finding. In- government programmes. focus courses are primarily those in technical skills alongside a cohort of managerial skills in strategy Through focused efforts, individuals could acquire and leadership. one of Coursera’s top 10 mastery skills in emerging professions across People and Culture, Content On average, respondents to the Future of Jobs Writing, Sales and Marketing in one to two months. Survey estimate that around 40% of workers will Learners could expand their skills in Product require reskilling of six months or less. That figure is Development and Data and AI in two to three higher for workers in the Consumer industry and in months; and if they wish to fully re-pivot to Cloud the Health and Healthcare industry, where employers and Engineering, learners could make headway are likely to expect to lean on short-cycle reskilling. into that key skill set through a 4-5 month learning The share of workers who can be reskilled within programme.38 Such figures suggest that although six months is lower in the Financial Services and learning a new skill set is increasingly accessible the Energy sectors, where employers expect that through new digital technologies, to consolidate workers will need more time-intensive reskilling. new learning individuals will need access to the time These patterns are explored more deeply in the and funding to pursue such new career trajectories. Industry Profiles in Part 2. LinkedIn data presented in section 2.2 indicates that although many individuals can move into emerging According to Future of Jobs Survey data, employers roles with low or mid skills similarity, a low-fit initial expect to lean primarily on internal capacity to transition will still require eventual upskilling and deliver training: 39% of training will be delivered by reskilling to ensure long term productivity. an internal department. However, that training will be supplemented by online learning platforms (16% of training) and by external consultants (11% of training). The trend towards the use of digital online reskilling has accelerated during the restrictions on in-person learning since the onset of the COVID-19 pandemic. New data from the online learning platform Coursera for April, May and June of 2020 (quarter 2) signals a substantial expansion in the use

The Future of Jobs 38 FIGURE 31 Distribution of course enrolment and growth of interest, by course specialism, employment status and year

A. Changes to in-focus course specialism by employment status

Distribution of enrolled, April, May and June (Q2) Year-on-year change, Q2 2019 to 2020

Rank Course Specialism All All Employed Employed Unemployed Unemployed All Employed Unemployed 2020 2019 2020 2019 2020 2019 2020 Business 21% 22% 16% 19% 5% 7% 17% 1 Computer Science 18% 19% 17% 11% 23% 21% -8% -34% -7% 2 Health 18% 16% 8% 14% 6% 8% 48% 81% 44% 3 Data Science 13% 22% 12% 28% 18% -37% -44% -35% 4 Personal Development 9% 13% 6% 12% 3% 5% 42% 88% 67% 5 Language Learning 20% 4% 6% 4% 6% 46% 55% 45% 6 Arts and Humanities 9% 5% 7% 4% 5% 12% 32% 4% 7 Physical Science and 6% 7% Engineering 5% 7% 8 Social Sciences 6% Information Technology 6% 5% 5% 6% 6% 7% 3% 11% 9 Math and Logic 6% 10 5% 5% 5% 4% 3% -27% -4% -17% 11 6% 4% 4% 5% 4% 5% 7% 1% -23% 49% 1% 1% 1% 2% 1% -23% -15% -16%

B. Top 10 in-focus skills of those in employment C. Top 10 skills for those who are unemployed

Rank 2019 2020 Rank 2019 2020

1 Python Programming Writing 1 Python Programming Python Programming 2 Artificial Neural Networks Strategy 2 Artificial Neural Networks Algorithms 3 Algorithms Python Programming 3 Algorithms Writing 4 Regression Mindfulness 4 Regression Strategy 5 Strategy Meditation 5 Deep Learning Artificial Neural Networks 6 Deep Learning Gratitude 6 Strategy Regression 7 Writing Kindness 7 Supply Chain Grammar 8 Supply Chain Listening 8 Writing Deep Learning 9 Cloud Computing Algorithms 9 General Statistics General Statistics 10 General Statistics Grammar 10 Te n s o r f l ow Problem-Solving

Source Note

Coursera, produced for the World Economic Forum’s New Values in brown indicate where the hiring rate is lower than in 2019, while values in Metrics CoLab. green indicate where the rate is higher than 2019. The darker the colour, the lower/ higher the rate.

The Future of Jobs 39

3 Public and Private Sector Pathways to Reviving Labour Markets

The challenges facing labour markets today are effective systems for upgrading individual’s significant but not insurmountable. To jointly lead skills and capabilities in line with emerging skills economies and societies to greater prosperity, the demand—in essence, expanding access and public and private sector will need to tackle the delivery of mid-career reskilling and upskilling factors that lead to the misallocation and waste through private and public sector investment of human capabilities and potential. For over half and to ensure that such efforts by workers are a century, economic thinkers have been able rewarded with adequate job opportunities. To to track the benefits of expanding human skills realize the value of such investments, businesses and capabilities to economic prosperity.39 One and governments will need to accompany such of the most valuable assets of any economy or efforts with policies and practices that ensure company is its human capital­the skills, capabilities that workers are able to prosper on the basis of and innovation of its citizens. Distortions that merit rather than the misallocation of talent due undercut individuals’ skills development and their to social strata or characteristics such as race or ability to find a job that matches their current and gender, strengthening the connection between potential capabilities erode the factors of economic personal income and productivity, and expanding productivity, innovation and growth that are derived safety nets to alleviate economic strain during from harnessing human skills and capabilities.40 periods of transition.

To harness human potential towards greater prosperity and inclusion, leaders will need to shift talent from areas of decline to areas of growth in the economy. They will be called on to create

3.1 From temporary public policy relief to long-term solutions

As illustrated throughout this report, the COVID-19 Governments and central banks have implemented pandemic has laid bare the lack of mechanisms fiscal and monetary packages of unique breadth to support workers through mid-career transitions and depth to counterbalance the economic impact and to ensure worker well-being and livelihoods of the pandemic as well as to protect workers amidst disruptions. What is needed is fundamental and households. According to recent estimates reform—or, more accurately, a revolution in the by the IMF (International Monetary Fund), close way education and training systems operate, and to $11 trillion has been deployed through direct in how they interact with labour market policies and fiscal impulse and liquidity measures aimed at business approaches to training workers with new supporting households and businesses through skills. This section reviews the current public policy the crisis.41 As illustrated by Figure 32, the fiscal ecosystem for ensuring adequate social protection, measures implemented by G20 countries in 2020 including new temporary measures put in place since are larger than those taken during and just after the onset of COVID-19. Global Financial Criss in 2007­2008.42 However, the breadth and scale of those policies remain out Reacting to the current social and economic of reach for most developing economies, which crisis, countries across the globe have announced have implemented less than half the number of packages of emergency fiscal and monetary measures implemented in developed economies. measures of unprecedented scope, and the This continues to be a concern given that many pandemic has led to the temporary adoption of developing economies still lack well-established measures enhancing social safety nets for workers health systems in addition to social safety nets. and households in a number of economies.

The Future of Jobs 40 In the immediate term it is possible to analyse coverage of social protection schemes using this the types of measures adopted and prioritized by specific mechanism. However, the majority of the different economies, while a longer-term horizon cash transfer measures implemented are time-bound will allow a broader analysis of their overall efficacy. and temporary and might not be the appropriate Data from the ILO presented in Figure 33 shows tool to provide the long-term economic relief that more than 1,000 different policy measures have necessary to vulnerable households. As illustrated been implemented in more than 200 countries since in Figure 34, such mechanisms typically lasted one the onset of the pandemic. They vary in focus and to three months, with only 16% of the programmes by instrument utilized. The majority of the measures implemented as a result of the pandemic lasting observed span a range of agile policy solutions longer than three months.43 Going forward, an which have the capacity to protect the most innovative approach to addressing the uncertain vulnerable workers directly. While some instruments nature of recessions could be to introduce cash depend on in-kind services maintaining health, stimulus payments which would be “automatically nutrition and having access to shelter, others focus triggered” by a deterioration in economic conditions, on income stability, such as the widespread use of preventing administrative lag and indecision.44 one-off cash transfers and allowances to subsidize household expenses, as well as a temporary extension and expansion of benefits to workers such as unemployment leave.

The timeliness and adaptability of cash transfer mechanisms have made them a critical tool to be deployed in the volatile context caused by COVID-19, which is why a number of governments across the world have expanded the provision and

FIGURE 32 Comparing the size of selected economies’ 2009-2020 fiscal stimulus packages, as share of economy GDP

Japan

Brazil

South Africa

China

Korea Argentina

Saudi Arabia

Russia

0 2 4 6 8 10 12 14

Fiscal stimulus as a % of GDP (%)

2020 value Decreased compared to 2009 Increased compared to 2009

Source Note

Policy Tracker 12 June 2020, International Monetary Values include ‘above-the-line’ measures but exclude ‘below- Fund (IMF); International Institute of Labour Studies; and the-line measures’ (equity injections, loans, asset purchase or Transatlantic Institute. debt assumptions, or guarantees).

The Future of Jobs 41 FIGURE 33 Social protection measures introduced by governments, by type of instrument and function

A. Function

Special allowance or grant 15.5 Income and job protection 13.3 12.5 Several functions 11.3 Unemployment leave 9.8 Health and healthcare 9.4 Housing and access to basic services 9.2 7.8 Food and nutrition 6.2 Children and families 3.5

Pension 0.7 Sick leave 0.5 Access to education 0.2 Maternity and parental leave Employment injury compensation

0 5 10 15 20

Share of in-country measures (%)

B. Instrument 14.9 14.7 Introducing benefits for poor or vulnerable populations Introducing benefits for workers or their dependants 9.4 7.9 Introducing subsidies to, deferring or reducing the cost of necessities 7.2 Increasing benefit level 6.7 5.7 Introducing subsidies to wages 5.6 Extending coverage of existing benefits 5.4 Deferring, reducing or waiving special contribution 3.9 Improving delivery mechanisms and capacity Increasing resources or budgetary allocation 5 10 15 20 Relaxing or suspending elegibility criteria or conditionality

0

Share of in-country measures (%)

Source Note

International Labour Organization (ILO) Social Protection The values represent the distribution of 1,218 measures Monitor, July 2020. introduced across 203 countries.

Another set of key policies has been focused on While these temporary measures provide a lifeline to preserving the retention of staff by businesses workers during this unprecedented crisis and ahead through wage compensation schemes as well as of a future recovery, the need for an urgent response tax or payment deferrals. Figure 35 presents the should be transformed into an impulse to enhance unprecedented use of job-retention schemes across permanent social protection mechanisms. New data several countries—notably New Zealand, France, from the OECD shows the projected employment Switzerland and the United Kingdom—affecting growth of a number of economies in 2019­2020 close to 60 million workers across OECD countries.45 if countries experience a potential second wave of While these measures have been broadly welcomed COVID-19 infections. Figure 36 plots that possible and have been effective at buffering unemployment, new reality against the Social Resilience pillar of such schemes obscure the possible true impact of the World Economic Forum’s Global Social Mobility COVID-19 on the labour market. It is only as wage Index. The pillar score summarizes in one measure support and replacement mechanisms begin to the level of social protection available in an economy expire that some of the damage to the labour market alongside the presence of inclusive institutions. will be revealed.

The Future of Jobs 42 FIGURE 34 Duration of cash-transfer programmes in months

3 months 1 month 1-2 months 52% 20% 14%

3-6 months 12 months 14% 2%

#$ %&’

Gentilini, et al, 2020.

FIGURE 35 Participation in job-retention schemes

New Zealand 20 40 60 80

Austria Portugal Luxembourg Netherlands Belgium

Ireland Czech Republic

Spain Sweden Denmark Norway Finland

Latvia

0

Share of dependent employees (%)

OECD Economic Outlook June 2020, based on national sources.

The Future of Jobs 43 Countries that score high have well-developed score. They include Ireland, the United Kingdom and social safety nets and protection as well as high Spain. Countries in the bottom-right quadrant can levels of public service efficiency. Countries in the expect to see high labour market disruption and also bottom-left quadrant of Figure 36 have low social have a low social resilience score. Those countries resilience scores and at the same time are projected include Colombia, Turkey and the United States. to experience lower economic disruption under this In summary, scenarios such as these suggest that scenario. Countries in that quadrant include Mexico some economies will experience a `double-hit’ and the Republic of Korea. Those in the top-right scenario—relatively low coverage of social protection quadrant can expect to see high disruption to mechanisms in place to protect workers heavily employment but also have a high social resilience displaced from the labour market.

FIGURE 36 Projected impact of COVID-19 on employment growth against an index of social resiliance, OECD countries

Social Resilience score from the Global Social Mobility Index 2020 100

Austria Finland Denmark

90 Belgium Sweden

Germany France Netherlands

80 Japan Norway Ireland Slovenia Australia Switzerland Canada Spain

70 Czech Republic Iceland Poland Portugal New Zealand Latvia Estonia

Lithuania Slovak Republic United States

60 Greece Korea, Rep. Italy Israel

50 Mexico Hungary Colombia

20 -3 -6 -9 -12 -15 0

Employment growth (2019-2020 % change based on COVID-19 “double-hit” forecasts)

Source Note

OECD Economic Outlook 2020, OECD, and Social Mobility Forecasts for Q4 2020 produced by the OECD assuming two Index, World Economic Forum. waves of COVID-19, namely a “double hit” scenario.

The political will to expand social protection has wage. The economic strain on families subsisting often been deadlocked, driven by concerns about on low wages is not conducive to maximizing long- the long-term impact on labour market participation, term human potential and leaves workers vulnerable the efficiency of current tools and the capacity of to disruptions. Legislating against bias on the basis government to deliver these public services with the of gender, race or other characteristics protects the adequate efficiency at scale. Given the large-scale connection between employment, wages and the disruption to workers from both the pandemic-driven skills and capabilities of workers—guaranteeing recession and the accelerated pace of technology that the talents of all parts of the population are adoption, the question cannot be if' but should be used and can drive further growth and prosperity how’ to expand some of these essential protections. in the economy.

Research shows that wages have, for some time, Past research has shown that long-term been misaligned from productivity and that wage displacement from the labour market has a level can be as much determined by the structure persistent, negative effect on workers.47 When social of local labour markets or disadvantaged by race protection mechanisms are lacking, individuals or gender as they are by workers receiving a in the midst of a career transition are forced to reasonable return on their skills and productivity.46 maintain a dual focus—on the one hand trying to When it comes to preserving worker’s ability to preserve their quality of life and keep poverty and save, governments can cap the erosion of wages, potential destitution at bay, and on the other hand ensuring that all workers are able to gain a living attempting to successfully transition to a new role.

The Future of Jobs 44 For those with historically low wages, it is much A number of countries have in recent years more likely that basic needs such as health, developed innovative funding mechanisms to nutrition and access to shelter become paramount finance reskilling of workers. Singapore recently and overwhelming concerns during such complemented its pioneering Skills Future Initiative periods detract from productive and successful through the deployment of Enhanced Training transitions to new roles. An individual’s capacity Support Package (ETSP)48 to support workers to manage this labour market transition can thus and organizations in sustaining investment in be undermined, leading to rushed and potentially reskilling and upskilling during COVID-19. The sub-par redeployment and re-employment. package includes a significant increase in funding for Absentee Payroll Support and Course Fee While some social protection policies are remedial Support among industries severely hit by the and short term, not all support can be temporary pandemic. At the end of 2019, France created an in nature. When it comes to long-term sick leave, individual skills account with an integrated mobile disability leave or long-term unemployment, social application dedicated to vocational training and protection becomes a fundamental pillar of the lifelong learning. Under the “moncompteformation. support for its citizens on an ongoing basis. For gouv.fr” (“MySkillsAccount”) scheme, 28 million the purposes of this report we have focused on eligible full- and part-time workers will receive 500 supporting the bounceback of those who are or annually directly into their skills account to spend on will be unemployed in the short term due to the upskilling and continuous learning, with low-skilled recession and technological change. To expand workers and those with special needs receiving safety nets in the medium to long term, societies up to 800 annually, capped at a total of 5,000 will need to rebalance current public spending and and 8,000, respectively. The Danish Ministry of consider expanding fiscal room through effective and Employment has introduced a number of measures appropriate taxation. aimed at providing additional opportunities for upskilling and job-focused education aimed at Governments can proactively shape the workers furloughed following as a consequence preconditions for effective labour market transitions of the economic impact of the pandemic. First, and worker productivity by strengthening the link both skilled and unskilled workers who pursue a between skills, wages and employment. This can vocational education are being provided with 110% be achieved through policies that fund reskilling of their usual unemployment benefits. Additionally, and upskilling of workers who are mid-way through the Danish government expanded the scope of its their career and will need further skills to secure current apprenticeship scheme, at the same time employment in the future of work, policies which as prolonging its job rotation scheme, making it ensure that workers are able to create cash reserves possible for more unskilled workers to have access during periods of employment, and policies which to upskilling and reskilling opportunities. legislate against bias in hiring, firing and setting wages. Reskilling and upskilling policies that have been utilized to date span the conditionality of unemployment benefits on taking up new re- skilling and up-skilling, providing wage subsidies to companies which extend reskilling and upskilling to workers, providing online learning accounts to citizens, and starting to fund online learning in addition to university degrees, TVET and school tuition.

3.2 From deploying human resources to leveraging human potential

As changes to work accelerate, employers are of workers. Without such pivots skills shortages bearing witness to a fundamental shift away will remain endemic and a scarcity of adequately from the linear transitions made by workers skilled individuals to fill the jobs of tomorrow will in previous points of history from school, into lead to a persistent productivity lag. specialized training, into work and then along a progressive career ladder, defined by increasing The route to unlocking the value of human responsibility within an established occupation potential in tandem with profitability is to employ structure. In today’s labour market, workers a `good jobs strategy’, halting the erosion of pivot between professions with significantly wages, making work meaningful and purposeful, different skill sets, and navigate mid-career job expanding employees’ sense of growth and transitions accompanied by substantial reskilling achievement, promoting and developing talent and upskilling. Those pivots are as important to on the basis of merit and proactively designing the success of firms as they are to the prosperity against racial, gender or other biases.49

The Future of Jobs 45 Fundamental to this strategy are two inter- Companies without the tools to account for the connected, ambitious priorities which, between value of skills and capabilities lack oversight of them, have the power to pave the way to a better, the depreciation or appreciation of one of their more productive and more rewarding future of key intangible assets—the capabilities of their work: 1) increasing company oversight of strategic workforce. Without that oversight, setting the right people metrics; 2) effective job transitions from investment strategy for reskilling and upskilling declining to emerging roles through well-funded becomes a challenging feat. A recent World reskilling and upskilling mechanisms. Economic Forum report, authored in collaboration with Willis Towers Watson, Human Capital as There is an emerging consensus among an Asset: An accounting framework for the companies that long-term value is most new world of work, identifies additional areas of effectively created by serving the interests of all measurement that can start to quantify the value stakeholders. Companies that hold themselves of human capital within an organization.52 In the accountable will be both more viable and outlined framework are the labour market value of valuable in the long-term. To do so, companies the aggregate talent in an organization, the value need a series of new metrics which can, at the added through additional reskilling and upskilling Board and C-suite level, make visible the impact into job-relevant skills and the depreciation of companies have on key desirable outcomes to those assets through gradual skills redundancy governance, planet, people and prosperity.50 and a decrease in workforce engagement. The approaches to undertaking this quantification are In collaboration with the International Business in their infancy and there is need for further efforts Council (IBC) the World Economic Forum has to expand such efforts. defined a set of key metrics which can track how businesses are creating broader, long-term Frameworks to track the value of human capital value through an investment in human and social in company balance sheets, to determine a re- capital. People are at the heart of all organizations investment strategy for human capital through as investors, workers, customers, suppliers, redeployment, reskilling and upskilling, as well distributors and contractors. The well-being, as to account for return on investment remain productivity and prosperity of individuals is at the nascent. It is therefore not surprising that few core of all successful economies and firms. Human Future of Jobs Survey respondents expected a ingenuity is at the core of companies’ competitive return on investment from reskilling and upskilling advantage and no firm can prosper for long if it workers within the first three months after proves damaging to the social fabric around it. In employees complete reskilling, and that 17% of the framework outlined within the paper Measuring businesses remain unsure about the return on Stakeholder Capitalism, the Forum in collaboration investment from reskilling. Survey responses also with the IBC have identified a set of key measures indicate that companies continue to struggle that track: the representation of employees by to quantify the scale of reskilling and upskilling age group, gender, ethnic and racial category and investment that their companies currently make. other markers of diversity; the pay equity between those different groups; the wage levels paid within The Future of Jobs Survey signals that companies the organization as a ratio to local minimum wage hope to internally redeploy 50% of workers and the ratio of CEO pay to median employee displaced by technological automation and pay; hours of training undertaken by employees; augmentation, but cross-cutting solutions and and average training investment by company. efficiencies for funding job transitions remain In addition to these core measures the report under-explored. Amidst the accelerated arrival outlines basic standards of good work such as of the automation and augmentation of work, ensuring health and safety, as well as eliminating as well as the job destruction brought about child and forced labour.51 by COVID-19, businesses require a fast, agile and coherent workforce investment strategy. In To complement such key oversight metrics, collaboration with the leaders engaged with the businesses can benefit from more granular New Economy and Society work at the World operational metrics which quantify the human Economic Forum we have been able to identify capital—the skills and capabilities of employees— a set of key elements of a successful workforce within an organization. Currently, business investment strategy. They include identifying leaders lack the tools to adequately illustrate, workers who are being displaced from their roles; diagnose and strategize for talent capacity. establishing appropriate internal committees to While businesses and economies have extensive manage the displacement; funding reskilling and systems to account for monetary assets at their upskilling either wholly out of company budgets disposals, there is a lag in establishing the value of or by tapping into government funding; motivating human skills and capabilities. The losses incurred employee engagement in this process; and by talent attrition as well as the gains of acquiring tracking the long-term success of such transitions. individuals with exceptional skills or of developing talent pools through strong reskilling and upskilling programmes remain unrecorded and unobserved.

The Future of Jobs 46 FIGURE 37 Investment into employee reskilling and upskilling

A. Perceived time period to receive return on investment

Within 1 Within 3­6 months More than 1 year month 24% 17.6%

2.3% Difficult to assess 16.6% Within 1­3 months

10.8%

Within 6­12 months 28.7%

B. Source of funding 10 20 30 40 50 60 70 80

Centralized budget Budget per department Use free learning to minimize cost

Budget per worker Tap into government funding Share costs with other companies in your industry Share costs with other companies outside your industry

0

Company leaders can ensure the success of report has shown that a number of emerging workforce strategies by directing the transition of roles are already staffed by individuals who first employees with empathy, within the rule of law, in transition into those positions and then `grow line with company values and culture, by ensuring into’ the full skill set required. As an overarching outcomes are equitable, and by directing learning principle, business leaders need to place equity to effective resources and meaningful curricula. and diversity at the heart of their talent ecosystem, A range of motivating factors can fuel reskilling ensuring that employees believe in their capacity and upskilling uptake—connected broadly to to prosper based on merit. employees’ sense of purpose, meaning, growth and achievement. Employers can signal the Expanding effective workforce strategies requires market value of new online-first credentials by strong capabilities in real time, as well as opening up role opportunities to new cohorts of dynamic mapping of the types of opportunities workers who have completed mid-career reskilling that remain available to workers displaced by and upskilling. Employers can make broader the COVID-19 pandemic and the fast pace of use of hiring on the basis of potential rather than automation. A set of technology companies current skill sets and match potential-based hiring which are broadly classed as EdTech and with relevant training. The data featured in this reskilling services companies can support the

The Future of Jobs 47 process of redeploying workers into the jobs of credentials. In one example, Telecommunication tomorrow.53 Such companies utilize advanced company AT&T has worked with Udacity to data and AI capabilities matched with user create 50 training programmes designed to interfaces that guide workers and managers prepare individuals for the technical careers through to discovering possible pathways into of the future which are distinctively relevant to new job roles. The data featured in sections AT&Ts future workforce and digital strategies.55 2.2 and 2.3 already indicates the types of In particular, these strategies include courses insights that can be accessed through such focused on skills in web and mobile development, services—dynamically matching opportunities data science and machine learning. To date to workers, identifying possible job destinations AT&T has spent over $200 million per year to and singling out bridging skill sets. Companies design this internal training curriculum, known with such capabilities can become part of a as T University, and has already achieved over new infrastructure for the future of work which 4,200 career pivots with 70% of jobs filled powers worker transitions from displaced to internally by those that were reskilled. In a similar emerging roles. The efforts of matching workers effort, Shell launched an online education effort to possible opportunities can be complemented titled the Shell.ai Development Program, which by the delivery of reskilling and upskilling at scale focuses on teaching artificial intelligence skills to through educational technology services. its employees.56 Both programmes have created customized versions of Udacity’s Nanodegree Finally, the necessary reskilling and upskilling programs to reskill and upskill employees with demands substantial attention and broad-base hard-to-source, in-demand skill sets. systemic solutions to funding the job transitions which the current labour market context requires An additional example is provided by Coursera at an unprecedented pace and scale. As for Government.57 At the start of the COVID-19 demonstrated in Figure 37, the Future of Jobs pandemic, a number of countries experienced survey shows that 66% of businesses believe a surge in unemployment. Governments in over they can see return on investment within a year 100 countries provided access to the platform to of funding reskilling for the average employee. It citizens looking to gain new skills and credentials remains concerning, however, that the survey also to re-enter the workforce. The programmes reveals that only 21% of businesses report being connected graduates directly with local companies able to make use of public funds, and merely who agreed to accept those credentials as 12% and 8% collaborate across companies and the basis of hiring decisions. Since April, this within industries, respectively. Previous estimates programme has reached 650,000 unemployed have shown that businesses can independently workers who enrolled in over 2.5 million courses reskill some employees with positive return on that provide the skills needed for fast-growing jobs investment; however, the employees who are most in IT, healthcare and business. In one example, disrupted and with the largest need of reskilling Costa Rica’s government has worked with local are likely to need a larger investment.54 employers across the country to identify current job openings and skill demand and tailored the This report calls for renewed efforts to understand programme offering to that local demand. Similar the division of spend on reskilling and upskilling structures of collaboration have been established workers between business and the public sector. A across local government in the United States, typical return on investment framework considers specifically across a network of job centres. the costs on the side of both businesses and governments under various scenarios—such as the extent of training costs, the cost of employees taking time out of work, and the need to pay unemployment benefits. On the benefits of reskilling and upskilling workers, a calculation takes into account avoided severance and hiring costs borne by business, the avoided lag in productivity when onboarding new employees and the additional productivity of employees who feel supported and are thriving. Additional benefits to governments include the income tax dividends of citizens who are employed as opposed to out of work.

A number of companies have in recent years experimented with a range of approaches to reskilling and upskilling. The role of business in such a programme can be to directly drive such efforts and define the approach to reskilling and upskilling. In other cases, businesses can be in a supporting role, agreeing to redefine their approach to hiring and accept candidates who have been reskilled through new types of

The Future of Jobs 48

Conclusion

The ongoing disruption to labour markets from To address the substantial challenges facing the the Fourth Industrial Revolution has been further labour market today, governments must pursue complicated—and in some cases accelerated—by a holistic approach, creating active linkages and the onset of the pandemic-related recession of 2020. coordination between education providers, skills, workers and employers, and ensuring effective The most relevant question to businesses, collaboration between employment agencies, regional governments and individuals is not to what extent governments and national governments. automation and augmentation of human labour will affect current employment numbers, but under Such efforts can be strengthened by what conditions the global labour market can be multistakeholder collaboration between companies supported towards a new equilibrium in the division looking to support their workforce; governments of labour between human workers, robots and willing to fund reskilling and the localization of algorithms. The technological disruptions which were mid-career education programmes; professional in their infancy in previous editions of the Future of services firms and technology firms that can Jobs Report are currently accelerated and amplified map potential job transitions or provide reskilling alongside the COVID-19 recession as evidenced services; labour unions aware of the impact of by findings from the 2020 Future of Jobs Survey. those transitions on the well-being of workers; and While it remains difficult to establish the long-term community organizations that can give visibility to consequences of the pandemic on the demand for the efficacy of new legislation and provide early products and services in severely affected industries, feedback on its design. supporting workers during this transition will protect one of the key assets of any company and country— its human capital.

In this new context, for the first time in recent years, job creation is starting to lag behind job destruction—and this factor is poised to affect disadvantaged workers with particular ferocity. Businesses are set to accelerate the digitalization of work processes, learning, expansion of remote work, as well as the automation of tasks within an organization. This report identifies one result of the pandemic as an increasing urgency to address the disruption underway both by supporting and retraining displaced workers and by monitoring the emergence of new opportunities in the labour market.

As unemployment figures rise, it is of increasing urgency to expand social protection, including support for retraining to displaced and at-risk workers as they navigate the paths towards new opportunities in the labour market and towards the `jobs of tomorrow’. Addressing the current challenges posed by COVID-19, in tandem with the disruption posed by technological change, requires renewed public service innovation for the benefit of affected workers everywhere. It also demands that leaders embrace stakeholder capitalism and pay closer attention to the long-dividends of investing in human and social capital. The current moment provides an opportunity for leaders in business, government, and public policy to focus common efforts on improving the access and delivery of reskilling and upskilling, motivating redeployment and reemployment, as well as signalling the market value of learning that can be delivered through education technology at scale.

The Future of Jobs 49 Notes

1. World Economic Forum, 2020a.

2. Baldwin, 2019.

3. Acemoglu, et al, 2020.

4. World Economic Forum, 2018, DeVries, et al, 2020, and Frey and Osborne, 2013.

5. Ding and Saenz Molina, 2020.

6. Hale, et al, 2020.

7. Ibid.

8. YouGov, 2020.

9. OECD, 2020a.

10. OECD, 2020a.

11. Ibid.

12. OECD, 2020b.

13. Delfs and Colitt, 2020, and Migliaccio, et al, 2020.

14. Ravn and Sterk, 2017, and Farber, 2011.

15. ILO, 2020.

16. COVID Inequality Project, https://sites.google.com/view/covidinequality/.

17. Author’s calculations based on data in Dingel, et al, 2020.

18. De Vries, et al, 2020.

19. Author’s calculations based on data in Dingel, et al, 2020.

20. Zhao, 2020.

21. Job-seekers searching for roles on the LinkedIn platform using built-in remote job

filters, normalized against changes to all job searches.

22. The share of job postings, which use number of keywords (i.e. `remote work’,

`work from home’, home office’) in 10 different languages, as well as built-in

remote job filters.

23. LinkedIn analysed data from job search behaviour and job postings of full-time

roles and its changes due to COVID-19 during the period of 11 February to 1

July. Analysts utilized the `remote work’ filter and a set of searchable key words

such as remote work', work from home’, `homeoffice’ in 10 different languages.

The index is the start of the analysis period, 11 July. Results are normalized for

platform growth as well as in the case of job searchers against the volume of job

searches. The daily figures represent a seven-day smoothed proportion.

24. Kimbrough, 2020.

25. Mongey, et al, 2020.

26. World Bank, 2020.

The Future of Jobs 50 27. Cook, et al, 2019.

28. ADP provides human capital management services to significant numbers of

US companies. Its data can therefore act as a reliable proxy for changes to the

American labour market.

29. Workers are considered to have dropped out of employment if they disappear

from the ADP database. While some of those variations can reflect worker

movements to companies which do not use ADP’s services, the scale of that

effect is not typically as large; therefore, on the basis of past trends we can

deduce that what we are reporting are reach changes to employment.

30. Data from FutureFit AI combines over 50 data sources on workforce demand and

supply, translating a range of taxonomies of jobs and skills. Supply-side sources

include over 350 million talent profiles listing 30,000 skills clusters, 80,000 job

titles, hundreds of industries, thousands of learning opportunities and millions of

companies worldwide. The data set used comes from worker profile information

sourced from resumes and online professional profiles. It also includes key

data points for the analysis—such as employers, start and end dates, job role,

industries and employment sequence, among others.

31. This metric covers approximately 300,000 young professionals in the United

States, defined here as those who have graduated with an upper secondary

or tertiary (undergraduate) degree no earlier than 2008, and have held 15 or

less positions and have not been in the labour market for longer than 20 years.

These professionals have, on average, eight years of work experience after or

during a student’s first degree. The average work experience tenure following

graduation is 6.7 years. The overwhelming majority of this sample are in their

first working decade.

32. Agopsowicz, 2019.

33. See, for example: Arntz, Melanie, Terry Gregory and Ulrich Zierahn, The risk of

automation for jobs in OECD countries: a comparative analysis, OECD Social,

Employment and Migration Working Papers No 189, Organization for Economic

Cooperation and Development (OECD), 2016; McKinsey Global Institute, A

Future That Works: Automation, Employment, and Productivity, McKinsey Global

Institute (MGI), 2017; PwC, Will robots really steal our jobs? An international

analysis of the potential long term impact of automation, 2018. For a range

of relevant additional considerations, see: van der Zande, Jochem, et al., The

Substitution of Labor: From technological feasibility to other factors influencing

job automation, Innovative Internet: Report 5, Stockholm School of Economics

Institute for Research, 2018.

34. Ding and Saenz Molina, 2020.

35. World Economic Forum, 2020a.

36. For more details on how the clusters are computed please refer to World

Economic Forum, 2020a.

37. For an in-depth analysis of emerging jobs please see World Economic

Forum, 2020a.

38. According to Coursera data from individuals completing reskilling and upskilling

on its platform, working towards a new skill in Cloud Computing could take on

average 106 full calendrical days; in Content, 24 days; in Data and AI professions,

60; in Engineering, 77 days; in Marketing, 39; People and Culture, 36; Sales. 37;

and in Product Development professions, 44. We take the average month to have

21 working days.

39. Sweetland, 1996.

40. Hsieh, et al., 2019.

41. IMF, 2020.

The Future of Jobs 51 42. Atlantic Council, 2020.

43. Gentilini, et al, 2020.

44. Economic Security Project, 2020.

45. OECD, 2020b.

46. Cahuc, et al, 2006, and Carroll, et al, 2016.

47. Deelen, 2018.

48. “Skills Future Enhanced Training Support Package”, https://www.

enterprisejobskills.sg/content/upgrade-skills/enhanced-training-support-

for-SME.html.

49. Ton, 2014, and https://goodjobsinstitute.org/good-jobs-scorecard/.

50. For more details on the overall framework please see Word Economic

Forum, 2020b.

51. For the complete report, see https://www.weforum.org/reports/measuring-

stakeholder-capitalism-towards-common-metrics-and-consistent-reporting-of-

sustainable-value-creation.

52. For the complete report, see https://www.weforum.org/reports/human-capital-

as-an-asset-an-accounting-framework-to-reset-the-value-of-talent-in-the-new-

world-of-work.

53. World Economic Forum, 2020c.

54. World Economic Forum, 2019.

55. For details, see https://blog.udacity.com/2018/09/udacity-and-att-join-forces-to-

train-workers-for-the-jobs-of-tomorrow.html.

56. For details, see https://www.shell.com/energy-and-innovation/digitalisation/

digital-technologies/shell-ai/shell-ai-residency-programme.html.

57. For details, see https://www.coursera.org/government.

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The Future of Jobs 54

Part 2 and Industry

Part 2 of the report presents data findings through both an industry and country lens, with the aim of providing specific practical information to decision-makers and experts from academia, business, government and civil society. Complementing the cross- industry and cross-country analysis of results in Part 1, this section provides deeper granularity for a given industry and country through dedicated Industry Profiles and Country Profiles. Profiles are intended to provide interested companies and policy- makers with the opportunity to benchmark their organization against the range of expectations prevalent in their industry and/or country. This User’s Guide provides an overview of the information contained in the various Industry Profiles and Country Profiles and its appropriate interpretation.

The Future of Jobs 55

User’s Guide

How to Read the Country and Industry Profiles

Country Profile 1/2 Working Age Population

United Arab Emirates 8,112,786

1 Education & skills worst best Jobs & work worst best

Digital skills among active population* 71.7% Labour force participation 0.9% 85.2% WEIGHTED AVERAGE 2019-2020 2019 32.5%

Attainment of basic education 82.9% Vulnerable employment

2018 2020

Business relevance of basic education* 65.3% Working cond. impact of gig economy*

WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education 51.8% Unemployment rate

2018 2019

Business relevance of tertiary education* 71% Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* 70.5% Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. 3.3% Unemployment rate change

2017 —

Unempl. rate among workers with basic educ. 0.8% Unemployment rate change, women

2017 —

Share of youth not in empl., educ. or training 11.4% Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of COVID- Share of companies surveyed Provide more opportunities to work remotely Internet of things and connected devices 89% 2 89.6% Cloud computing 84% 3 Accelerate the digitalization of work processes (e.g. use of digital tools, video E-commerce and digital trade conferencing)

77.1% 84%

47.9% 84%

45.8% 81%

39.6% 77%

Emerging and redundant jobs roles Artificial intelligence (e.g. machine learning, 76% neural networks, NLP) 65% Role identified as being in high demand or increasingly redundant within their Power storage and generation 57% organization, ordered by frequency 56% 4 EMERGING 1. Data Analysts and Scientists

2. Digital Marketing and Strategy Specialists

3. Business Development Professionals

4. AI and Machine Learning Specialists Emerging skills

5. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered by 6. Process Automation Specialists

6. Organisational Development Specialists 1. Analytical thinking and innovation 5

7. General and Operations Managers 2. Complex problem-solving

8. Database and Network Professionals 3. Critical thinking and analysis

9. Big Data Specialists 4. Active learning and learning strategies

REDUNDANT 5. Leadership and social influence

1. Administrative and Executive Secretaries 6. Technology use, monitoring and control

2. Data Entry Clerks 7. Creativity, originality and initiative

3. Accounting, Bookkeeping and Payroll Clerks 8. Service orientation

4. Postal Service Clerks 9. Resilience, stress tolerance and flexibility

5. Business Services and Administration Managers 10. Emotional intelligence

6. Mechanics and Machinery Repairers 11. Technology design and programming

7. Accountants and Auditors 12. Troubleshooting and user experience

8. Material-Recording and Stock-Keeping Clerks 13. Quality control and safety awareness

9. Client Information and Customer Service Workers 14. Systems analysis and evaluation

10. Cashiers and Ticket Clerks 15. Persuasion and negotiation

The Future of Jobs 56

Current skills in focus of existing reskilling/upskilling Average reskilling needs 6 Share of workforce of companies surveyed within this data 7 Share of companies surveyed identifying this skill as being in focus across their reskilling or upskilling programs

1. Active learning and learning strategies Less than 1 month 3 to 6 months 30.6% 18.6%

2. Critical thinking and analysis

3. Creativity, originality and initiative 6 to 12 months

1 to 3 months Over 1 year 21.4% 16.4%

Responses to shifting skill needs

Expect existing employees to pick up skills on 98%

Retrain existing employees 86%

Hire new permanent staff with skills relevant to 84% new technologies 50%

8 Look to automate the work Projected use of training providers

Outsource some business functions to external Share of companies surveyed

Hire new temporary staff with skills relevant to 49% 44.3% Internal learning and development 9

Strategic redundancies of staff who lack the skills 48%

20.4% External online training

15.5% Private training providers 8.2% Public training providers 6.5% Private educational institutions 5.1% Public educational institutions

The Future of Jobs 57 1. Hard data contextual a 0-100 score called `progress score’, where 100 indicators: Education & skills/ corresponds to the best possible frontier and 0 to Jobs & work the worst possible frontier.

This section aims to provide the reader with the Period: 2019­2020 weighted average or most latest available data from contextual indicators on recent period available. education, skills, jobs and work. To allow for an Source: World Economic Forum, Executive Opinion understanding of the indicators of different nature Survey 2020. and magnitude, the contextual indicators not expressed as a percentage have been normalized Attainment of advanced education: on a 0 to 100 scale, providing a `progress score’ for Percentage of the population aged 25 and over with each indicator. a tertiary education (includes ISCED 5-8).

The total working age population is displayed in Period: 2018 or latest available data (accessed the top right corner of the page. The working-age September 2020). population is the number of people aged 25 and Source: UNESCO Institute for Statistics, Education over. In addition to using a minimum age threshold, Indicators. certain countries also apply a maximum age limit.

Period: 2019 or latest available data (accessed Business relevance of tertiary education: September 2020). Score computed based on the average response of Source:ILOstat, International Labour Organization. companies operating in this country to the Executive Opinion Survey question “In your country, to what Education & skills extent do university graduates possess the skills needed by businesses?” [1 = not all; 7 = to a great Digital skills among active population: extent]. Results converted to a 0-100 score called Score computed based on the average response of progress score, where 100 corresponds to the best companies operating in this country to the Executive possible frontier and 0 to the worst possible frontier. Opinion Survey question "In your country, to what extent does the active population possess sufficient Period: 2019­2020 weighted average or most digital skills (e.g. computer skills, basic coding, digital recent period available. reading)?" [1 = not all; 7 = to a great extent]. Results Source: World Economic Forum, Executive Opinion converted to a 0-100 score called progress score’, Survey 2020. where 100 corresponds to the best possible frontier and 0 to the worst possible frontier.

Period: 2019­2020 weighted average or most Supply of business relevant skills: recent period available. Score computed based on the average response Source: World Economic Forum, Executive Opinion of companies operating in this country to the Survey 2020. Executive Opinion Survey question “In your country, to what extent can companies find people with Attainment of basic education: the skills required to fill their vacancies?” [1 = not Percentage of the population aged 25 and over with at all; 7 = to a great extent]. Results converted to at least a secondary education (includes ISCED 2-4). a 0-100 score called `progress score’, where 100 This data is cumulative, which means that those with corresponds to the best possible frontier and 0 to tertiary education are counted in the figures. the worst possible frontier.

Period: 2018 or latest available data (accessed Period: 2019­2020 weighted average or most September 2020). recent period available. Source: UNESCO, Institute for Statistics, Education Source: World Economic Forum, Executive Opinion Indicators. Survey 2020.

Business relevance of basic education: Unemployment rate among workers with basic Score computed based on the average response education: of companies operating in this country to the The unemployment rate among workers with Executive Opinion Survey question “In your country, basic education is the number of persons who to what extent do secondary-education graduates are unemployed as a percentage of the total possess the skills needed by businesses?” [1 = number of employed and unemployed persons not all; 7 = to a great extent]. Results converted to (i.e. the labour force). Data by level of education is provided on the highest level of education completed (includes ISCED 2-4).

The Future of Jobs 58 Period: 2019 or latest available data (accessed September 2020). September 2020). Source: ILOstat, International Labour Organization. Source: ILOstat, International Labour Organization.

Unemployment rate among workers with Erosion of working conditions impacted by gig advanced education: economy: The unemployment rate among workers with Score computed based on the average response advanced education is the number of persons who of companies operating in this country to the are unemployed as a percentage of the total number Executive Opinion Survey question “In your of employed and unemployed persons (i.e. the country, what is the impact of the online gig labour force). Data by level of education is provided economy on working conditions (e.g., working on the highest level of education completed. time, remuneration, stability)?” [1= Significantly (includes ISCED 5-8). worsen working conditions; 7= Significantly improves working conditions]. Results converted to Period: 2019 or latest available data (accessed a 0-100 score called `progress score’, where 100 September 2020). corresponds to the best possible frontier and 0 to Source: ILOstat, International Labour Organization. the worst possible frontier.

Share of youth not in employment, education or Period: 2019­2020 weighted average or most training: recent period available. This is the share of youth not in employment, Source: World Economic Forum, Executive Opinion education or training (NEET). Values represented are Survey 2020. ILO modelled estimates. Unemployment rate (latest annual), latest Please note that imputed observations are not based available quarterly), (latest monthly) : on national data, are subject to high uncertainty The latest annual unemployment rate is calculated and should not be used for country comparisons by expressing the number of unemployed persons or rankings. This indicator refers to the proportion as a percentage of the total number of persons in of youth who are not in employment and not in the labour force. The labour force (formerly known education or training. For statistical purposes, youth as the economically active population) is the sum of are defined as persons between the ages of 15 and the number of persons employed and the number 24 years. For more information, refer to the indicator of persons unemployed. Thus, the measurement of description and the ILO estimates and projections the unemployment rate requires the measurement methodological note. of both employment and unemployment. The unemployed comprise all persons of working age Period: November 2019. who were: a) without work during the reference Source: ILOstat, International Labour Organization. period, i.e. were not in paid employment or self- employment; b) currently available for work, i.e. were Jobs & work available for paid employment or self-employment during the reference period; and c) seeking work, Labour force participation: i.e. had taken specific steps in a specified recent The labour force participation rate is the proportion period to seek paid employment or self-employment. of the working-age population actively engaged Future starters, that is, persons who did not look for in the labour market. The share of the population work but have a future labour market stake (made either in employment or looking for employment as a arrangements for a future job start) are also counted percentage of the total working age population. as unemployed, as well as participants in skills training or retraining schemes within employment Period: 2019 or latest available data (accessed promotion programmes, who on that basis, were September 2020). “not in employment”, not “currently available” and did Source: ILOstat, International Labour Organization. not “seek employment” because they had a job offer to start within a short subsequent period generally not greater than three months and persons “not in employment” who carried out activities to migrate abroad in order to work for pay or profit but who were still waiting for the opportunity to leave.

Vulnerable employment: Period: Latest available data for each period Vulnerable employment is defined as contributing (accessed September 2020). family workers and own-account workers as a Source: ILOstat, International Labour Organization. percentage of total employment.

Period: 2020 or latest available data (accessed

The Future of Jobs 59 Unemployment rate (2019-2020 Q2 change, the O*NET labour market information system (see (2019-2020 Q2 change by gender) Appendix A: Report Methodology for details). These values represent the change in unemployment rate from 2019 year-end to Q2 2020, using the Period: 2020. figures sourced above. We also featured these Source: World Economic Forum, Future of Jobs figures above broken down by gender. Survey 2020.

Period: Latest available data for each period 5. Emerging skills: (accessed September 2020). Source: ILOstat, International Labour Organization.

2. Impact of COVID-19 on The table provides the list of skills the country companies strategies: respondents have selected as being increasingly important within their organization. It is based on the This bar chart shows the top five measures responses to the following question “Keeping in mind organizations are planning on implementing in the tasks that will be performed by the key roles in response to the current COVID-19 outbreak as your organization, in the next four years would you a share of survey respondents from companies expect an increase or decrease in the use of the operating in the country. It is based on the following skills by individuals?” from the Future of responses to the following question “In response Jobs Survey. The skills are ranked by frequency and to the current outbreak, which of the following ranked from 1 to 15. The full list of skills is based measures has your company implemented or is on the O*NET classification and available in the planning to implement across the Organization?” appendix section of this report. from the Future of Jobs Survey. Period: 2020. Source: World Economic Forum, Future of Jobs Source: World Economic Forum, Future of Jobs Survey 2020.

3. Technology adoption: 6. Current skills in focus of

This bar chart represents the share of survey The table provides the list of skills that are the focus respondents from companies operating in the of existing company reskilling/upskilling programmes country who indicated that, by 2025, their company for companies based in the country. It is based on the was “likely” or “very likely” (on a 5-point scale) to responses to the following question “Keeping in mind have adopted the stated technology as part of its your current strategic direction, select the top 10 skill growth strategy. For a more detailed discussion of clusters that you are currently focusing your reskilling/ each technology, please refer to the “Technological upskilling efforts on?” from the Future of Jobs Survey. adoption” section in chapter 2 of the report. The skills are ranked from 1 to 15, with 1 being the skill for which most organizations offer training. The full Period: 2020. list of skills is based on the O*NET classification and Source: World Economic Forum, Future of Jobs available in the appendix section of this report.

4. Emerging and redundant job 7. Average reskilling needs: roles: The treemap shows the estimated time needed This table provides an overview of job roles expected to reskill each share of the workforce that needs to see an increase and decrease in demand across reskilling within the country. It is based on the the country over the 2020­2025 period. The responses to the following question “Bearing in mind individual job roles listed are for illustrative purposes the evolving skill demand, how long do you expect and report the job roles most frequently cited by the reskilling/upskilling of your employees to take?” survey respondents from companies operating in the country. Categorization of job roles is adapted from

The Future of Jobs 60

from the Future of Jobs Survey. Respondents were 9. Projected use of training asked to provide as share of their workforce for each providers: duration of reskilling/upskilling. The chart shows the projected proportion of the use Period: 2020. of different training providers for the future training Source: World Economic Forum, Future of Jobs programmes of companies based in the country. It is Survey 2020. based on the responses to the following question “In your future retraining programme, what proportion 8. Response to shifting skill needs: of training provision will come from the options mentioned below?” from the Future of Jobs Survey. The bar chart shows the top strategies organizations will undertake to address the shifting skills demand Period: 2020. as a share of survey responses from companies Source: World Economic Forum, Future of Jobs operating in the country. It is based on the Survey 2020. responses to the following multiple-choice question “How likely is your organization to undertake the following strategies to address the shifting skills demand?” from the Future of Jobs Survey.

The Future of Jobs 61

Industry Profile 1/2

1 Expected redeployment Average skills instability success rate of displaced among workforce workers

Average share of workers at risk of 41.3% 43.6% displacement

2 Technology adoption in industry Emerging skills 3

Share of companies surveyed Skills identified as being in high demand within their organization, ordered by

Cloud computing 89% 1. Technology use, monitoring and control Internet of things and connected devices 85% 2. Critical thinking and analysis Robots, non-humanoid (industrial automation, 83% drones, etc.) 76% 3. Active learning and learning strategies E-commerce and digital trade 74% 74% 4. Leadership and social influence Big data analytics 68% 62% 5. Analytical thinking and innovation Artificial intelligence (e.g. machine learning, neural 7. Complex problem-solving Text, image and voice processing 8. Service orientation

Power storage and generation 9. Resilience, stress tolerance and flexibility

10. Technology design and programming

11. Troubleshooting and user experience

Emerging and redundant jobs roles

Role identified as being in high demand or increasingly redundant within their

Impact of COVID-19 on companies’ strategy organization, ordered by frequency 5

4 Share of companies surveyed looking to adopt this strategy as a result of COVID- EMERGING 1. Business Development Professionals

Provide more opportunities to work remotely 2. Software and Applications Developers

76.9% 3. Sales Representatives, Wholesale and Manufacturing, Technic…

Accelerate the digitalization of work processes (e.g. use of digital tools, video 4. Robotics Engineers

conferencing) 5. Internet of Things Specialists 73.1%

Accelerate automation of tasks 6. Data Analysts and Scientists Accelerate ongoing organisational transformations (e.g. restructuring) 57.7% 7. Project Managers 38.5% 8. Power Production Plant Operators

9. Assembly and Factory Workers

10. AI and Machine Learning Specialists

11. Assembly and Factory Workers

12. Relationship Managers

13. Sales Representatives, Wholesale and Manufacturing, Technic…

14. Administrative and Executive Secretaries

15. Accounting, Bookkeeping and Payroll Clerks

The Future of Jobs 62

6 Barriers to adoption of new technologies Expected impact on workforce 7

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 67.7% Modify the composition of the value chain Skills gaps among organization’s leadership 54.8% Inability to attract specialized talent 67.7% Shortage of investment capital 45.2% Insufficient understanding of opportunities 41.9% Expand its use of contractors doing task-specialized work Lack of flexibility of the regulatory framework 38.7% Lack of flexibility in hiring and firing 25.8% 48.4% Lack of interest among leadership 19.4% Other 9.7% Reduce its current workforce due to technological integration or automation 6.5% 45.2%

Share of companies surveyed identifying this skill as being in focus across their reskilling or upskilling programs

1. Technology use, monitoring and control

Augmentation of key job tasks by 2024 3. Complex problem-solving 9

4. Technology installation and maintenance

Machine share Human share 5. Critical thinking and analysis

8 6. Technology design and programming

Information and data processing 8. Service orientation

38.3% 9. Management of financial, material resources

Performing physical and manual work activities 10. Leadership and social influence

Looking for and receiving job-related information Average reskilling needs

All tasks DURATION OF RESKILLING

48.5% Less than 1 month 3 to 6 months 26.8% 16.6%

Administering 10

Performing complex and technical activities 6 to 12 months

59% 1 to 3 months

Reasoning and decision-making Over 1 year

The Future of Jobs 63 1. Average share of displaced important within their organization. It is based on the workers / Expected redeployment responses to the following question “Keeping in mind success rate of displaced workers the tasks that will be performed by the key roles in / Average skills instability among your organization, in the next four years would you workforce expect an increase or decrease in the use of the following skills by individuals?” from the Future of The share of workers at risk of displacement was Jobs Survey. The skills are ranked by frequency and calculated by computing the mean response of ranked from 1 to 15. The full list of skills is based surveyed employers operating in this industry to the on the O*NET classification and available in the Future of Jobs Survey question: “What proportion appendix section of this report. of your global workforce do these employees which are likely to become increasingly redundant in your Period: 2020. organization represent in the next four years?” Source: World Economic Forum, Future of Jobs

The expected redeployment success rate was 4. Impact of Covid-19 on calculated by computing the mean response companies’ strategy: from surveyed employers from this industry to the Future of Jobs Survey question “What percentage This bar chart shows the top 5 measures of employees with increasingly redundant skillsets organizations are planning on implementing in do you expect to successfully redeploy within your response to the current COVID-19 outbreak as organization after they have completed their reskilling a share of survey respondents from the industry. programme?” It is based on the responses to the following question “In response to the current outbreak, The average skills instability among the workforce which of the following measures has your company was calculated by computing the mean response implemented or is planning to implement across the from surveyed employers from this industry to the Organization?” from the Future of Jobs Survey. Future of Jobs Survey question “Keeping in mind the tasks that will be performed by your employees, in Period: 2020. the next four years what proportion of the core skills Source: World Economic Forum, Future of Jobs required to perform their roles well will be different”. Survey 2020.

2. Technology adoption in 5. Emerging and redundant job industry: roles:

This bar chart represents the share of survey This table provides an overview of job roles expected respondents from companies operating in the to experience an increase and decrease in demand industry who indicated that, by 2025, their within this industry over the 2020­2025 period. The company was “likely” or “very likely” (on a 5-point individual job roles listed are for illustrative purposes scale) to have adopted the stated technology as and report the job roles most frequently cited by part of its growth strategy by 2025. For a more survey respondents from companies operating in the detailed discussion of each technology, please industry. Categorization of job roles is adapted from refer to the “Technology adoption” section in the O*NET labour market information system (please chapter 2 of the report. see Appendix A: Report Methodology for details).

Period: 2020. Period: 2020. Source: World Economic Forum, Future of Jobs Source: World Economic Forum, Future of Jobs Survey 2020. Survey 2020.

3. Emerging skills: 6. Barriers to adoption of new technologies: The table provides the list of skills the industry respondents have selected as being increasingly This bar chart shows the most common barriers companies face when adopting new technologies.

The Future of Jobs 64 It is based on the responses to the following upskilling efforts on?” from the Future of Jobs multiple-choice question “What are the top Survey. The skills are ranked from 1 to 10 by economic and social barriers your organization frequency of responses by companies surveyed experiences when introducing new technologies?” from this industry, with 1 being the skill for which from the Future of Jobs Survey. This bar is ranked most organzations offer training. The full list of skills by frequency of responses by companies surveyed is based on the O*NET classification and available in from this industry. the appendix section of this report.

Period: 2020. Period: 2020. Source: World Economic Forum, Future of Jobs Source: World Economic Forum, Future of Jobs Survey 2020. Survey 2020.

7. Expected impact on workforce: 10. Average reskilling needs:

This bar chart shows the expected impact of the The treemap shows the estimated time needed current growth strategy of companies operating to reskill each share of the workforce that needs in this industry on their workforce in the next four reskilling within the industry. It is based on the years. It is based on the responses to the following responses to the following question “Bearing in mind multiple-choice question “To deliver on your the evolving skill demand, how long do you expect organization’s current growth strategy in the next the reskilling/upskilling of your employees to take?” four years, your organization would need to?” from from the Future of Jobs Survey. Respondents were the Future of Jobs Survey. asked to provide as share of their workforce for each duration of reskilling/upskilling. Source: World Economic Forum, Future of Jobs Period: 2020. Survey 2020. Source: World Economic Forum, Future of Jobs

8. Augmentation of key job tasks by 2024:

The bar chart depicts the share of time that will be performed by humans compared to machines by 2024 for each task. It is based on the responses to the following question “Currently, what proportion of time spent doing tasks in your organization is spent by your employees performing the work?” from the Future of Jobs Survey. This stacked bar chart is ranked by share of time spent doing tasks by machines.

9. Current skills in focus of

The table provides the list of skills that are the focus of existing industry company reskilling/upskilling programmes. It is based on the responses to the following question “Keeping in mind your current strategic direction, select the top 10 skill clusters that you are currently focusing your reskilling/

The Future of Jobs 65

The Future of Jobs 66 Country Profile 1/2 Working Age Population

Argentina 17,640,048

Education & skills worst best Jobs & work worst best

Digital skills among active population* 50.1% Labour force participation 65.7% 57.2% 21.9% WEIGHTED AVERAGE 2019-2020 45.9% 2019 48.7% Attainment of basic education 20% Vulnerable employment 66.2% 7.4% 2018 2020 54% Business relevance of basic education* 3.4% Working cond. impact of gig economy*

WEIGHTED AVERAGE 2019-2020 9.6% 2020 Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 95% Cloud computing 90% 87.5% Artificial intelligence (e.g. machine learning, 89% neural networks, NLP) 80% Accelerate the digitalization of work processes (e.g. use of digital tools, video Big data analytics 75% 72% conferencing) Internet of things and connected devices 70% 87.5% 68% E-commerce and digital trade 67% Accelerate automation of tasks 65% 56.2% Robots, non-humanoid (industrial automation, Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Augmented and virtual reality

providers) 3D and 4D printing and modelling

EMERGING AI and Machine Learning Specialists Emerging skills Robotics Engineers 1. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered 2. Software and Applications Developers by frequency 4. FinTech Engineers 1. Creativity, originality and initiative 6. Business Services and Administration Managers 2. Complex problem-solving 7. Renewable Energy Engineers 8. Digital Marketing and Strategy Specialists 3. Analytical thinking and innovation 10. 4. Reasoning, problem-solving and ideation

REDUNDANT 5. Active learning and learning strategies

1. Data Entry Clerks 6. Technology use, monitoring and control

2. Accounting, Bookkeeping and Payroll Clerks 7. Quality control and safety awareness

3. Electronics and Telecommunications Installers and Repairers 8. Emotional intelligence

4. Assembly and Factory Workers 9. Resilience, stress tolerance and flexibility

5. Administrative and Executive Secretaries 10. Persuasion and negotiation

6. Shop Salespersons 11. Critical thinking and analysis

7. Sales and Marketing Professionals 12. Coordination and time management

8. Relationship Managers 13. Technology installation and maintenance

9. Material-Recording and Stock-Keeping Clerks 14. Technology design and programming

10. Bank Tellers and Related Clerks 15. Troubleshooting and user experience

The Future of Jobs 67

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Active learning and learning strategies Less than 1 month 3 to 6 months 33.3% 18.4%

2. Creativity, originality and initiative

3. Troubleshooting and user experience

4. Analytical thinking and innovation

5. Reasoning, problem-solving and ideation

6. Quality control and safety awareness 6 to 12 months 8. Persuasion and negotiation Over 1 year 18.4% 9. Management of personnel

7. Leadership and social influence

Responses to shifting skill needs 1 to 3 months 88% Projected use of training providers Retrain existing employees 88% 75% Share of companies surveyed Expect existing employees to pick up skills on 69% the job 69% 26.1% Internal learning and development Hire new permanent staff with skills relevant to 69% new technologies 38% 23.1% Private training providers

17.5% Public educational institutions 15.9% Private educational institutions

The Future of Jobs 68 Country Profile 1/2 Working Age Population

Australia 17,332,023

Education & skills worst best Jobs & work worst best

Digital skills among active population* 65.5% Labour force participation 65.6% 93.4% 10.6% WEIGHTED AVERAGE 2019-2020 2019 59.7% 46.8% Attainment of basic education 43.3% Vulnerable employment 2018 68.4% 2020 59.7% 5.4% Business relevance of basic education* Working cond. impact of gig economy* 5.6% WEIGHTED AVERAGE 2019-2020 2020 1.5% 1.3% Attainment of advanced education Unemployment rate 2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 AUGUST 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

— 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

— 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video neural networks, NLP) 97% Internet of things and connected devices 94% conferencing) 91% 92.3% Cloud computing 91% Provide more opportunities to work remotely Big data analytics 79% Robots, non-humanoid (industrial automation, 79% 80.8% drones, etc.) 69% Text, image and voice processing 68% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 58% 65.4% Augmented and virtual reality

Accelerate automation of tasks E-commerce and digital trade

61.5% 3D and 4D printing and modelling

EMERGING AI and Machine Learning Specialists Emerging skills 1. Information Security Analysts Skills identified as being in high demand within their organization, ordered 2. Big Data Specialists by frequency 3. Process Automation Specialists 4. Digital Transformation Specialists 1. Analytical thinking and innovation 5. Remote Sensing Scientists and Technologists 6. Organizational Development Specialists 2. Active learning and learning strategies 7. Mechanical Engineers 8. Internet of Things Specialists 3. Critical thinking and analysis 10. 4. Leadership and social influence

REDUNDANT 5. Technology use, monitoring and control

1. Data Entry Clerks 6. Emotional intelligence

2. Administrative and Executive Secretaries 7. Complex problem-solving

3. Accounting, Bookkeeping and Payroll Clerks 8. Resilience, stress tolerance and flexibility

4. Business Services and Administration Managers 9. Creativity, originality and initiative

5. General and Operations Managers 10. Technology design and programming

6. Assembly and Factory Workers 11. Systems analysis and evaluation

7. Credit and Loans Officers 12. Service orientation

8. Client Information and Customer Service Workers 13. Reasoning, problem-solving and ideation

9. Accountants and Auditors 14. Quality control and safety awareness

10. Cashiers and Ticket Clerks 15. Troubleshooting and user experience

The Future of Jobs 69

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 27.7% 15.6%

2. Technology use, monitoring and control

3. Reasoning, problem-solving and ideation 6 to 12 months 12.4% 8. Complex problem-solving Over 1 year 18.5%

4. Emotional intelligence 1 to 3 months 25.8%

Responses to shifting skill needs 97% Projected use of training providers Share of companies surveyed 86% Share of companies surveyed Retrain existing employees 66% 44.6% Internal learning and development Expect existing employees to pick up skills on 48%

15.3% Private training providers 15% Public educational institutions 7.8% Public training providers 3.4% Private educational institutions

The Future of Jobs 70 Country Profile 1/2 Working Age Population

Brazil 136,154,622

Education & skills worst best Jobs & work worst best

Digital skills among active population* 36.9% Labour force participation 64.2% 60% 27.9% WEIGHTED AVERAGE 2019-2020 32.1% 2019 16.5% 44.7% Attainment of basic education Vulnerable employment 45.1% 8.7% 2018 42.2% 2020 6% 11.9% Business relevance of basic education* 9.3% Working cond. impact of gig economy* 23.6% 1.6% WEIGHTED AVERAGE 2019-2020 2020 1.4% Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 97% Big data analytics 97% conferencing) 94% 92% Encryption and cyber security 94% Artificial intelligence (e.g. machine learning, 91% Provide more opportunities to work remotely neural networks, NLP) 84% Internet of things and connected devices 84% 88% 78% Text, image and voice processing 74% Accelerate automation of tasks 71% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Robots, non-humanoid (industrial automation, providers) Distributed ledger technology (e.g. blockchain)

EMERGING AI and Machine Learning Specialists Emerging skills 1. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered 2. Digital Transformation Specialists by frequency 4. Management and Organisation Analysts 1. Active learning and learning strategies 6. Project Managers 2. Analytical thinking and innovation 8. Business Services and Administration Managers 3. Creativity, originality and initiative 10. 4. Leadership and social influence

REDUNDANT 5. Emotional intelligence

1. Accounting, Bookkeeping and Payroll Clerks 6. Critical thinking and analysis

2. Data Entry Clerks 7. Complex problem-solving

3. Assembly and Factory Workers 8. Resilience, stress tolerance and flexibility

4. Administrative and Executive Secretaries 9. Technology design and programming

5. Mechanics and Machinery Repairers 10. Service orientation

6. Material-Recording and Stock-Keeping Clerks 11. Reasoning, problem-solving and ideation

7. Client Information and Customer Service Workers 12. Troubleshooting and user experience

8. Bank Tellers and Related Clerks 13. Technology use, monitoring and control

9. Accountants and Auditors 14. Systems analysis and evaluation

10. Business Services and Administration Managers 15. Persuasion and negotiation

The Future of Jobs 71

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Leadership and social influence Less than 1 month 3 to 6 months 21.4% 20.9%

2. Reasoning, problem-solving and ideation 6 to 12 months 8. Management of personnel Over 1 year 21% 9. Creativity, originality and initiative

3. Resilience, stress tolerance and flexibility 1 to 3 months 19.6%

Responses to shifting skill needs 97% Projected use of training providers Share of companies surveyed 87% Share of companies surveyed 84% Look to automate the work 68% 36.9% Internal learning and development Retrain existing employees 55%

22.6% External online training

19.9% Private training providers

8.6% Private educational institutions 6.7% Public educational institutions 5.3% Public training providers

The Future of Jobs 72 Country Profile 1/2 Working Age Population

Canada 26,359,853

Education & skills worst best Jobs & work worst best

Digital skills among active population* 67.9% Labour force participation 65.9% 10.7% WEIGHTED AVERAGE 2019-2020 61.2% 2019 49.7% 36.1% Attainment of basic education Vulnerable employment 71.1% 4.8% — 68.4% 2020 4.2% 10.5% Business relevance of basic education* 8% Working cond. impact of gig economy* 8.9% WEIGHTED AVERAGE 2019-2020 2020 6% 6.4% Attainment of advanced education Unemployment rate 5.5% 2016 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 AUGUST 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Cloud computing 91% Internet of things and connected devices 91% conferencing) Big data analytics 88% 89.5% Text, image and voice processing 84% E-commerce and digital trade 81% Provide more opportunities to work remotely Distributed ledger technology (e.g. blockchain) 79% Augmented and virtual reality 72% 78.9% Robots, non-humanoid (industrial automation, 72% drones, etc.) 68% Accelerate automation of tasks 3D and 4D printing and modelling 60%

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

EMERGING AI and Machine Learning Specialists Emerging skills 1. Process Automation Specialists Skills identified as being in high demand within their organization, ordered 2. Information Security Analysts by frequency 4. Internet of Things Specialists 1. Analytical thinking and innovation 5. Big Data Specialists 6. Mathematicians, Actuaries and Statisticians 2. Active learning and learning strategies 8. Digital Transformation Specialists 3. Technology design and programming 10. 4. Critical thinking and analysis

REDUNDANT 5. Complex problem-solving

1. Data Entry Clerks 6. Leadership and social influence

2. Accounting, Bookkeeping and Payroll Clerks 7. Emotional intelligence

3. Business Services and Administration Managers 8. Technology use, monitoring and control

4. Accountants and Auditors 9. Resilience, stress tolerance and flexibility

5. Administrative and Executive Secretaries 10. Reasoning, problem-solving and ideation

6. Mining and Petroleum Extraction Workers 11. Creativity, originality and initiative

7. Assembly and Factory Workers 12. Systems analysis and evaluation

8. Mechanics and Machinery Repairers 13. Troubleshooting and user experience

9. Human Resources Specialists 14. Service orientation

10. Financial Analysts 15. Quality control and safety awareness

The Future of Jobs 73

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Leadership and social influence Less than 1 month 3 to 6 months 6 to 12 months 22.3% 18.8% 13.9%

2. Reasoning, problem-solving and ideation

3. Resilience, stress tolerance and flexibility

19.4% 25.6%

Responses to shifting skill needs 93% Projected use of training providers Share of companies surveyed 79% Share of companies surveyed 63% Hire new permanent staff with skills relevant to 59% 42% Internal learning and development new technologies 48%

20% Private training providers

17.6% External online training

8.2% Public educational institutions 6.2% Public training providers

6% Private educational institutions

The Future of Jobs 74 Country Profile 1/2 Working Age Population

China -

Education & skills worst best Jobs & work worst best

Digital skills among active population* 71.7% Labour force participation 74% 66.9% 45.1% 2020 2010 73.6% 28.2% Attainment of basic education 71.1% Vulnerable employment

— 18% 2020

Business relevance of basic education* Working cond. impact of gig economy*

2020 2020

Attainment of advanced education Unemployment rate

Business relevance of tertiary education* Unemployment rate

2020 —

Supply of business-relevant skills* Unemployment, monthly

2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

Unempl. rate among workers with basic educ. Unemployment rate change, women

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video neural networks, NLP) 96% Encryption and cyber security 94% conferencing) 90% 92.3% Internet of things and connected devices 88% Provide more opportunities to work remotely Big data analytics 84% 82.1% E-commerce and digital trade 73% Robots, non-humanoid (industrial automation, 69% Accelerate automation of tasks drones, etc.) 66% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 53.8% 3D and 4D printing and modelling

41%

EMERGING Data Analysts and Scientists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Information Security Analysts by frequency 4. Internet of Things Specialists 1. Analytical thinking and innovation 6. Supply Chain and Logistics Specialists 2. Active learning and learning strategies 8. Assembly and Factory Workers 3. Complex problem-solving 10. 4. Technology design and programming

REDUNDANT 5. Creativity, originality and initiative

1. Data Entry Clerks 6. Resilience, stress tolerance and flexibility

2. Accounting, Bookkeeping and Payroll Clerks 7. Critical thinking and analysis

3. Administrative and Executive Secretaries 8. Emotional intelligence

4. Business Services and Administration Managers 9. Technology use, monitoring and control

5. Assembly and Factory Workers 10. Reasoning, problem-solving and ideation

6. Accountants and Auditors 11. Leadership and social influence

7. General and Operations Managers 12. Troubleshooting and user experience

8. Client Information and Customer Service Workers 13. Service orientation

9. Human Resources Specialists 14. Systems analysis and evaluation

10. Financial and Investment Advisers 15. Quality control and safety awareness

The Future of Jobs 75

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 18.7% 19.9%

2. Critical thinking and analysis

3. Complex problem-solving 1 to 3 months 18.8% 7. Reasoning, problem-solving and ideation 3 to 6 months 8. Creativity, originality and initiative

4. Service orientation Over 1 year 10. Technology use, monitoring and control

Responses to shifting skill needs 90% Projected use of training providers Share of companies surveyed 85% Share of companies surveyed Expect existing employees to pick up skills on 70% 40.7% Internal learning and development the job 68%

17.5% Private training providers 6.9% Public educational institutions

The Future of Jobs 76 Country Profile 1/2 Working Age Population

France 45,968,569

Education & skills worst best Jobs & work worst best

Digital skills among active population* 57.1% Labour force participation 58.4% 84.2% 7.4% WEIGHTED AVERAGE 2019-2020 2019 55.7% 49.7% Attainment of basic education 30.1% Vulnerable employment 67.2% 7.3% 2017 2020 55.9% 5.2% Business relevance of basic education* 4.6% Working cond. impact of gig economy* 5.4%

WEIGHTED AVERAGE 2019-2020 13.2% 2020 -1.6% 10.3% -2% Attainment of advanced education Unemployment rate -1.2% 2017 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 J U LY 2 0 2 0

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Artificial intelligence (e.g. machine learning, 94% neural networks, NLP) 91% conferencing) Encryption and cyber security 89% 91.7% 89% Cloud computing 89% Provide more opportunities to work remotely 78% Big data analytics 77% 75% 74% Augmented and virtual reality 74% Accelerate automation of tasks Robots, non-humanoid (industrial automation, 72% 54.2% E-commerce and digital trade

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Distributed ledger technology (e.g. blockchain)

providers) Text, image and voice processing

EMERGING Data Analysts and Scientists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Internet of Things Specialists by frequency 4. Assembly and Factory Workers 1. Active learning and learning strategies 5. General and Operations Managers 6. FinTech Engineers 2. Critical thinking and analysis 8. Business Services and Administration Managers 3. Analytical thinking and innovation 10. 4. Technology design and programming

REDUNDANT 5. Complex problem-solving

1. Data Entry Clerks 6. Creativity, originality and initiative

2. Administrative and Executive Secretaries 7. Resilience, stress tolerance and flexibility

3. Accountants and Auditors 8. Emotional intelligence

4. Accounting, Bookkeeping and Payroll Clerks 9. Service orientation

5. Assembly and Factory Workers 10. Leadership and social influence

6. Financial Analysts 11. Reasoning, problem-solving and ideation

7. Human Resources Specialists 12. Systems analysis and evaluation

8. General and Operations Managers 13. Technology use, monitoring and control

9. Client Information and Customer Service Workers 14. Persuasion and negotiation

10. Claims Adjusters, Examiners, and Investigators 15. Troubleshooting and user experience

The Future of Jobs 77

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 16.2% 19.8%

2. Emotional intelligence

3. Critical thinking and analysis

4. Resilience, stress tolerance and flexibility

5. Management of personnel 1 to 3 months 13.5% 8. Complex problem-solving 3 to 6 months Over 1 year 18% 32.5%

6. Technology design and programming

Responses to shifting skill needs 93% Projected use of training providers Share of companies surveyed 81% Share of companies surveyed Retrain existing employees 52% 37.8% Internal learning and development Hire new permanent staff with skills relevant to 43%

25.8% External online training

16% Private training providers 7.9% Public training providers 7.6% Public educational institutions 4.9% Private educational institutions

The Future of Jobs 78 Country Profile 1/2 Working Age Population

Germany 62,281,725

Education & skills worst best Jobs & work worst best

Digital skills among active population* 62.5% Labour force participation 63.3% 96.3% 5.6% WEIGHTED AVERAGE 2019-2020 2019 64.7% 41.6% Attainment of basic education 25.7% Vulnerable employment 2.9% 2018 69.6% 2020 60.8% 4.2% Business relevance of basic education* 1.8% Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 5.4% 2020

Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 J U LY 2 0 2 0

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 92% Big data analytics 90% conferencing) 90% 85.7% Internet of things and connected devices 90% Artificial intelligence (e.g. machine learning, 83% Provide more opportunities to work remotely neural networks, NLP) 81% E-commerce and digital trade 76% 77.1% 73% Encryption and cyber security 71% Accelerate automation of tasks Robots, non-humanoid (industrial automation, 60% 51.4% Augmented and virtual reality

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Text, image and voice processing

providers) Distributed ledger technology (e.g. blockchain)

37.1%

EMERGING Data Analysts and Scientists Emerging skills 1. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered 2. Big Data Specialists by frequency 4. Information Security Analysts 1. Active learning and learning strategies 6. Software and Applications Developers 2. Analytical thinking and innovation 8. Process Automation Specialists 3. Complex problem-solving 10. 4. Resilience, stress tolerance and flexibility

REDUNDANT 5. Leadership and social influence

1. Data Entry Clerks 6. Critical thinking and analysis

2. Administrative and Executive Secretaries 7. Creativity, originality and initiative

3. Accounting, Bookkeeping and Payroll Clerks 8. Technology design and programming

4. Accountants and Auditors 9. Emotional intelligence

5. Business Services and Administration Managers 10. Service orientation

6. General and Operations Managers 11. Systems analysis and evaluation

7. Client Information and Customer Service Workers 12. Reasoning, problem-solving and ideation

8. Financial and Investment Advisers 13. Technology use, monitoring and control

9. Assembly and Factory Workers 14. Instruction, mentoring and teaching

10. Human Resources Specialists 15. Troubleshooting and user experience

The Future of Jobs 79

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 23.7% 19.7%

2. Complex problem-solving 1 to 3 months 18% 9. Service orientation 3 to 6 months Over 1 year 16.5% 22.1%

Responses to shifting skill needs 95% Projected use of training providers Share of companies surveyed 85% Share of companies surveyed Expect existing employees to pick up skills on 66% 42.5% Internal learning and development the job 54% Hire new permanent staff with skills relevant to 49%

19.1% Private training providers

6.7% Public training providers

5% Public educational institutions

The Future of Jobs 80 Country Profile 1/2 Working Age Population

India 588,373,756

Education & skills worst best Jobs & work worst best

Digital skills among active population* 49.2% Labour force participation 55.5% WEIGHTED AVERAGE 2019-2020 37.2% 2018 Attainment of basic education 38.9% Vulnerable employment 42.3% 2.5% — 9.2% 2020 1.6% Business relevance of basic education* 31.1% Working cond. impact of gig economy*

WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education Unemployment rate

— 2018

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2018 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2018 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 98% Encryption and cyber security 95% 90.3% 90% Internet of things and connected devices 88% Accelerate the digitalization of work processes (e.g. use of digital tools, video 86% Big data analytics 81% conferencing) 77% 87.1% Text, image and voice processing 75% Artificial intelligence (e.g. machine learning, 73% Accelerate automation of tasks neural networks, NLP) 64% 58.1% drones, etc.) Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 51.6% Power storage and generation

48.4%

EMERGING AI and Machine Learning Specialists Emerging skills 1. Information Security Analysts Skills identified as being in high demand within their organization, ordered 2. Internet of Things Specialists by frequency 4. Project Managers 1. Analytical thinking and innovation 6. Digital Marketing and Strategy Specialists 2. Complex problem-solving 7. Software and Applications Developers 8. Business Development Professionals 3. Active learning and learning strategies 10. 4. Critical thinking and analysis

REDUNDANT 5. Resilience, stress tolerance and flexibility

1. Administrative and Executive Secretaries 6. Technology design and programming

2. General and Operations Managers 7. Emotional intelligence

3. Assembly and Factory Workers 8. Creativity, originality and initiative

4. Accounting, Bookkeeping and Payroll Clerks 9. Leadership and social influence

5. Data Entry Clerks 10. Reasoning, problem-solving and ideation

6. Accountants and Auditors 11. Technology use, monitoring and control

7. Architects and Surveyors 12. Service orientation

8. Human Resources Specialists 13. Troubleshooting and user experience

9. Client Information and Customer Service Workers 14. Systems analysis and evaluation

10. Business Services and Administration Managers 15. Persuasion and negotiation

The Future of Jobs 81

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 24.2% 18.9%

2. Complex problem-solving 6 to 12 months 8. Technology use, monitoring and control Over 1 year

20.4%

Responses to shifting skill needs 95% Projected use of training providers 92% Share of companies surveyed 84% Share of companies surveyed Expect existing employees to pick up skills on 67% 41.5% Internal learning and development the job 65% 56%

21.1% External online training

17.7% Private training providers

8.4% Public educational institutions 5.4% Private educational institutions

The Future of Jobs 82 Country Profile 1/2 Working Age Population

Indonesia 153,009,507

Education & skills worst best Jobs & work worst best

Digital skills among active population* 60.6% Labour force participation 74% 50.9% 47.5% WEIGHTED AVERAGE 2019-2020 2019 55.3% 30.5% Attainment of basic education 10% Vulnerable employment 1.8%

2018 64% 2020 Business relevance of basic education* 2.5% Working cond. impact of gig economy* 1.4% WEIGHTED AVERAGE 2019-2020 22.2% 2020

Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 95% Encryption and cyber security 95% 91.7% 95% Cloud computing 89% Accelerate the digitalization of work processes (e.g. use of digital tools, video 89% Big data analytics 84% conferencing) Artificial intelligence (e.g. machine learning, 78% 75% neural networks, NLP) 72% Robots, non-humanoid (industrial automation, 68% Accelerate automation of tasks drones, etc.) 68%

EMERGING Data Analysts and Scientists Emerging skills 1. AI and Machine Learning Specialists Skills identified as being in high demand within their organization, ordered 2. Digital Marketing and Strategy Specialists by frequency 3. Renewable Energy Engineers 4. Process Automation Specialists 1. Creativity, originality and initiative 6. Digital Transformation Specialists 2. Complex problem-solving 7. Business Services and Administration Managers 8. Business Development Professionals 3. Active learning and learning strategies

REDUNDANT 4. Emotional intelligence

1. Accounting, Bookkeeping and Payroll Clerks 5. Analytical thinking and innovation

2. Data Entry Clerks 6. Troubleshooting and user experience

3. Material-Recording and Stock-Keeping Clerks 7. Leadership and social influence

4. Assembly and Factory Workers 8. Critical thinking and analysis

5. Administrative and Executive Secretaries 9. Resilience, stress tolerance and flexibility

6. Mining and Petroleum Extraction Workers 10. Reasoning, problem-solving and ideation

7. Mechanics and Machinery Repairers 11. Service orientation

8. Human Resources Specialists 12. Technology design and programming

9. Business Services and Administration Managers 13. Technology use, monitoring and control

10. Accountants and Auditors 14. Systems analysis and evaluation

11. Instruction, mentoring and teaching

The Future of Jobs 83

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 17.1% 16.5%

2. Technology design and programming

3. Critical thinking and analysis 1 to 3 months 7. Service orientation 3 to 6 months Over 1 year 19.2% 28.5% 8. Emotional intelligence

Responses to shifting skill needs 94% Projected use of training providers Share of companies surveyed 82% Share of companies surveyed Look to automate the work 71% 41.3% Internal learning and development Retrain existing employees 53%

19.6% Private training providers

6.7% Private educational institutions 5.4% Public training providers 4.9% Public educational institutions

The Future of Jobs 84 Country Profile 1/2 Working Age Population

Italy 46,122,130

Education & skills worst best Jobs & work worst best

Digital skills among active population* 50.7% Labour force participation 52.9% 78.5% 16.9% WEIGHTED AVERAGE 2019-2020 2019 51.8% 43.3% Attainment of basic education 14.4% Vulnerable employment 8.7% 2015 61.6% 2020 52.3% 7.5% Business relevance of basic education* 5.5% Working cond. impact of gig economy* 12.3% -1.8% WEIGHTED AVERAGE 2019-2020 19.1% 2020 -2% -1.7% Attainment of advanced education Unemployment rate

2015 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Cloud computing 94% Big data analytics 88% conferencing) Encryption and cyber security 88% 100% Robots, non-humanoid (industrial automation, 82% drones, etc.) 80% Provide more opportunities to work remotely Augmented and virtual reality 80% Text, image and voice processing 76% 80% Power storage and generation 71% 3D and 4D printing and modelling 71% Accelerate automation of tasks New materials (e.g. nanotubes, graphene) 69%

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

EMERGING AI and Machine Learning Specialists Emerging skills Internet of Things Specialists 1. Data Analysts and Scientists Skills identified as being in high demand within their organization, ordered 2. Digital Transformation Specialists by frequency 3. Assembly and Factory Workers 4. Project Managers 1. Creativity, originality and initiative 5. Process Automation Specialists 6. General and Operations Managers 2. Analytical thinking and innovation 8. Application engineers 3. Critical thinking and analysis 10. 4. Active learning and learning strategies

REDUNDANT 5. Resilience, stress tolerance and flexibility

1. Data Entry Clerks 6. Emotional intelligence

2. Administrative and Executive Secretaries 7. Leadership and social influence

3. Accounting, Bookkeeping and Payroll Clerks 8. Complex problem-solving

4. Business Services and Administration Managers 9. Technology use, monitoring and control

5. Assembly and Factory Workers 10. Service orientation

6. Accountants and Auditors 11. Technology design and programming

7. Human Resources Specialists 12. Reasoning, problem-solving and ideation

8. Financial and Investment Advisers 13. Persuasion and negotiation

9. Electronics and Telecommunications Installers and Repairers 14. Quality control and safety awareness

10. Credit and Loans Officers 15. Coordination and time management

The Future of Jobs 85

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 24.1% 20.6%

2. Emotional intelligence

3. Technology design and programming

4. Leadership and social influence

5. Critical thinking and analysis 6 to 12 months 20.7% 8. Resilience, stress tolerance and flexibility Over 1 year 18.6%

Responses to shifting skill needs 1 to 3 months 86% Projected use of training providers Look to automate the work 86% 57% Share of companies surveyed Hire new permanent staff with skills relevant to 43% new technologies 36% 41.5% Internal learning and development Hire new temporary staff with skills relevant to 33% new technologies 31%

20.9% External online training

16.9% Private training providers 7.4% Public educational institutions 6.6% Private educational institutions 6.6% Public training providers

The Future of Jobs 86 Country Profile 1/2 Working Age Population

Japan 98,710,000

Education & skills worst best Jobs & work worst best

Digital skills among active population* 50.8% Labour force participation 63.7% 8.3% WEIGHTED AVERAGE 2019-2020 56.3% 2019 45.6% Attainment of basic education 58.6% Vulnerable employment 52.9% 2.2% — 1.9% 2020 Business relevance of basic education* 3.1% Working cond. impact of gig economy* 2.7%

WEIGHTED AVERAGE 2019-2020 2020 0.3% 0.2% Attainment of advanced education Unemployment rate 0.4% — 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 J U LY 2 0 2 0

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

— 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video neural networks, NLP) 97% Internet of things and connected devices 97% conferencing) 95% 93.5% Big data analytics 92% Provide more opportunities to work remotely Encryption and cyber security 81% 83.9% Augmented and virtual reality 68% 60% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology E-commerce and digital trade 59%

providers) Text, image and voice processing 61.3% Robots, non-humanoid (industrial automation, Accelerate automation of tasks Distributed ledger technology (e.g. blockchain)

48.4% Robots, humanoid

38.7%

EMERGING Data Analysts and Scientists Emerging skills 1. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered 2. Digital Marketing and Strategy Specialists by frequency 4. Information Security Analysts 1. Analytical thinking and innovation 6. Digital Transformation Specialists 2. Active learning and learning strategies 7. Project Managers 8. Management and Organisation Analysts 3. Creativity, originality and initiative 10. 4. Complex problem-solving

REDUNDANT 5. Technology use, monitoring and control

1. Data Entry Clerks 6. Technology design and programming

2. Accounting, Bookkeeping and Payroll Clerks 7. Resilience, stress tolerance and flexibility

3. Administrative and Executive Secretaries 8. Reasoning, problem-solving and ideation

4. Sales Representatives, Wholesale and Manufacturing, Technic… 9. Technology installation and maintenance

5. General and Operations Managers 10. Critical thinking and analysis

6. Business Services and Administration Managers 11. Emotional intelligence

7. Assembly and Factory Workers 12. Troubleshooting and user experience

8. Mechanics and Machinery Repairers 13. Systems analysis and evaluation

9. Legal Secretaries 14. Leadership and social influence

10. Statistical, Finance and Insurance Clerks 15. Service orientation

The Future of Jobs 87

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 6 to 12 months 22.2% 19.5% 12.6%

2. Technology design and programming

3. Systems analysis and evaluation

4. Reasoning, problem-solving and ideation

19% 26.8%

Responses to shifting skill needs 94% Projected use of training providers 91% Share of companies surveyed 88% Share of companies surveyed Expect existing employees to pick up skills on 74% 40.4% Internal learning and development the job 71% 45%

20.3% External online training

18.5% Private training providers 7.1% Private educational institutions 6.6% Public educational institutions

The Future of Jobs 88 Country Profile 1/2 Working Age Population

Malaysia 16,231,000

Education & skills worst best Jobs & work worst best

Digital skills among active population* 66.3% Labour force participation 77.6% 74.2% 21.7% WEIGHTED AVERAGE 2019-2020 2018 58.4% 32.7% Attainment of basic education 18.8% Vulnerable employment 2016 65.2% 2020 64.4% Business relevance of basic education* Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education Unemployment rate

2016 2018

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

Unempl. rate among workers with basic educ. Unemployment rate change, women

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 94% Big data analytics 94% conferencing) 88% 100% Encryption and cyber security 88% Artificial intelligence (e.g. machine learning, 75% Provide more opportunities to work remotely neural networks, NLP) 73% Text, image and voice processing 73% 75% Robots, non-humanoid (industrial automation, 69% drones, etc.) 56% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Augmented and virtual reality 56%

providers) E-commerce and digital trade

EMERGING Data Analysts and Scientists Emerging skills Strategic Advisors 1. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered 2. Digital Transformation Specialists by frequency 3. Digital Marketing and Strategy Specialists 4. Big Data Specialists 1. Emotional intelligence 5. AI and Machine Learning Specialists 6. Cyber Security Specialists 2. Creativity, originality and initiative 7. Software and Applications Developers 8. Renewable Energy Engineers 3. Analytical thinking and innovation 10. 4. Technology design and programming

REDUNDANT 5. Complex problem-solving

1. Data Entry Clerks 6. Active learning and learning strategies

2. Administrative and Executive Secretaries 7. Troubleshooting and user experience

3. Accounting, Bookkeeping and Payroll Clerks 8. Systems analysis and evaluation

4. Human Resources Specialists 9. Leadership and social influence

5. Mining and Petroleum Extraction Workers 10. Critical thinking and analysis

6. Mechanics and Machinery Repairers 11. Technology use, monitoring and control

7. Environmental and Occupational Health and Hygiene Professio… 12. Resilience, stress tolerance and flexibility

8. Assembly and Factory Workers 13. Reasoning, problem-solving and ideation

9. Accountants and Auditors 14. Service orientation

10. Business Services and Administration Managers 15. Instruction, mentoring and teaching

The Future of Jobs 89

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 33.4% 16.2%

2. Emotional intelligence

3. Quality control and safety awareness 6 to 12 months 11.6% 8. Service orientation Over 1 year 17%

Responses to shifting skill needs 1 to 3 months 86% Projected use of training providers Look to automate the work 86% 86% Share of companies surveyed Hire new permanent staff with skills relevant to 71% new technologies 64% 36.1% Internal learning and development 62% Expect existing employees to pick up skills on 50% 22.9% External online training

22.1% Private training providers

8.2% Public educational institutions 4.8% Private educational institutions

The Future of Jobs 90 Country Profile 1/2 Working Age Population

Mexico 73,069,000

Education & skills worst best Jobs & work worst best

Digital skills among active population* 42.9% Labour force participation 64.6% 63.2% 26.9% WEIGHTED AVERAGE 2019-2020 2019 42.5% 45.6% Attainment of basic education 16.4% Vulnerable employment 2018 57.6% 2020 50.5% 3.3% Business relevance of basic education* 3.9% Working cond. impact of gig economy* 2.4% 1.4% WEIGHTED AVERAGE 2019-2020 18.9% 2020 0.7% 1.9% Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 91% Internet of things and connected devices 91% 94.4% 91% Cloud computing 91% Accelerate the digitalization of work processes (e.g. use of digital tools, video 86% Big data analytics 82% conferencing) 78% 88.9% E-commerce and digital trade 64% Artificial intelligence (e.g. machine learning, 62% Accelerate automation of tasks neural networks, NLP) 60% 83.3% 55.6% Robots, non-humanoid (industrial automation, Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

EMERGING AI and Machine Learning Specialists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Information Security Analysts by frequency 3. Project Managers 4. Process Automation Specialists 1. Complex problem-solving 6. Architects and Surveyors 2. Active learning and learning strategies 7. FinTech engineers 8. University and Higher Education Teachers 3. Analytical thinking and innovation 10. 4. Critical thinking and analysis

REDUNDANT 5. Technology design and programming

1. Accounting, Bookkeeping and Payroll Clerks 6. Reasoning, problem-solving and ideation

2. Data Entry Clerks 7. Creativity, originality and initiative

3. Administrative and Executive Secretaries 8. Emotional intelligence

4. General and Operations Managers 9. Troubleshooting and user experience

5. Architects and Surveyors 10. Service orientation

6. Bank Tellers and Related Clerks 11. Resilience, stress tolerance and flexibility

7. Assembly and Factory Workers 12. Technology use, monitoring and control

8. Statistical, Finance and Insurance Clerks 13. Leadership and social influence

9. Material-Recording and Stock-Keeping Clerks 14. Persuasion and negotiation

10. Accountants and Auditors 15. Coordination and time management

The Future of Jobs 91

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 16.4% 18.2%

2. Reasoning, problem-solving and ideation

3. Active learning and learning strategies 1 to 3 months 23.6% 7. Creativity, originality and initiative

4. Troubleshooting and user experience

5. Technology use, monitoring and control Over 1 year 10. Persuasion and negotiation

Responses to shifting skill needs 95% 3 to 6 months 90% 18.6% Share of companies surveyed 85% 75% Projected use of training providers Retrain existing employees 65% 60% Share of companies surveyed Hire new permanent staff with skills relevant to 60% 43.2% Internal learning and development

9.7% Private educational institutions 6.5% Public educational institutions 4.7% Public training providers

The Future of Jobs 92 Country Profile 1/2 Working Age Population

Netherlands 12,236,238

Education & skills worst best Jobs & work worst best

Digital skills among active population* 77.4% Labour force participation 63.9% 90.4% 12.6% WEIGHTED AVERAGE 2019-2020 2019 71.6% 38.7% Attainment of basic education 33% Vulnerable employment 2018 77.9% 2020 63.7% 2.8% Business relevance of basic education* Working cond. impact of gig economy* 3%

WEIGHTED AVERAGE 2019-2020 2.2% 2020 0% 4% 0% Attainment of advanced education 2.8% Unemployment rate 2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 AUGUST 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 91% Internet of things and connected devices 91% conferencing) Artificial intelligence (e.g. machine learning, 88% 96% neural networks, NLP) 86% E-commerce and digital trade 86% Provide more opportunities to work remotely 83% Cloud computing 72% 88% 68% Encryption and cyber security 65% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Robots, non-humanoid (industrial automation, 58% providers) Text, image and voice processing

EMERGING Data Analysts and Scientists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Information Security Analysts by frequency 3. Food Scientists and Technologists 4. Organizational Development Specialists 1. Analytical thinking and innovation 6. FinTech Engineers 2. Active learning and learning strategies 7. Digital Marketing and Strategy Specialists 8. Business Development Professionals 3. Leadership and social influence 10. 4. Critical thinking and analysis

REDUNDANT 5. Creativity, originality and initiative

1. Data Entry Clerks 6. Complex problem-solving

2. Administrative and Executive Secretaries 7. Resilience, stress tolerance and flexibility

3. Accounting, Bookkeeping and Payroll Clerks 8. Technology use, monitoring and control

4. Assembly and Factory Workers 9. Service orientation

5. Client Information and Customer Service Workers 10. Technology design and programming

6. Business Services and Administration Managers 11. Emotional intelligence

7. Credit and Loans Officers 12. Reasoning, problem-solving and ideation

8. Bank Tellers and Related Clerks 13. Systems analysis and evaluation

9. Cashiers and Ticket Clerks 14. Troubleshooting and user experience

10. Insurance Underwriters 15. Instruction, mentoring and teaching

The Future of Jobs 93

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 22.5% 16.2%

2. Resilience, stress tolerance and flexibility 6 to 12 months 17.7% 7. Reasoning, problem-solving and ideation Over 1 year 23.8%

3. Technology design and programming

Responses to shifting skill needs 97% Projected use of training providers Share of companies surveyed 83% Share of companies surveyed Expect existing employees to pick up skills on 70% 38.7% Internal learning and development the job 58% 57%

20.8% External online training

8.9% Public educational institutions 8.6% Public training providers 6.3% Private educational institutions

The Future of Jobs 94 Country Profile 1/2 Working Age Population

Pakistan 82,345,263

Education & skills worst best Jobs & work worst best

Digital skills among active population* 50.7% Labour force participation 56.3% 36.4% 55.3% WEIGHTED AVERAGE 2019-2020 45.8% 2018 47.3% Attainment of basic education 8.7% Vulnerable employment 54.9% 2.8% 2017 2020 Business relevance of basic education* 4.5% Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 2020 31.1% Attainment of advanced education Unemployment rate

2017 2018

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2018 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2018 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely Big data analytics 91% Cloud computing 91% 71.4% Encryption and cyber security 91% Text, image and voice processing 86% Accelerate the digitalization of work processes (e.g. use of digital tools, video Artificial intelligence (e.g. machine learning, 83% neural networks, NLP) 70% conferencing) Power storage and generation 65% 71.4% Distributed ledger technology (e.g. blockchain) 56% Augmented and virtual reality 55% Accelerate automation of tasks 3D and 4D printing and modelling 47%

EMERGING Business Development Professionals Emerging skills 1. Mechanics and Machinery Repairers Skills identified as being in high demand within their organization, ordered 2. Digital Transformation Specialists by frequency 4. Sales and Marketing Professionals 1. Active learning and learning strategies 6. Business Services and Administration Managers 2. Leadership and social influence 8. Advertising and Public Relations Professionals 3. Critical thinking and analysis 10. 4. Creativity, originality and initiative

REDUNDANT 5. Analytical thinking and innovation

1. Data Entry Clerks 6. Reasoning, problem-solving and ideation

2. Administrative and Executive Secretaries 7. Complex problem-solving

3. Management and Organisation Analysts 8. Technology use, monitoring and control

4. General and Operations Managers 9. Troubleshooting and user experience

5. Door-To-Door Sales Workers, News and Street Vendors, and R… 10. Systems analysis and evaluation

6. Assembly and Factory Workers 11. Attention to detail, trustworthiness

7. Accountants and Auditors 12. Resilience, stress tolerance and flexibility

8. Legal Secretaries 13. Coordination and time management

9. Business Services and Administration Managers 14. Technology design and programming

10. Postal Service Clerks 15. Quality control and safety awareness

The Future of Jobs 95

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 27.3% 20.1%

2. Coordination and time management

3. Management of personnel

4. Creativity, originality and initiative

5. Technology use, monitoring and control 6 to 12 months 14.7% 9. Technology design and programming Over 1 year 14.6%

Responses to shifting skill needs 96% Projected use of training providers Share of companies surveyed 86% Share of companies surveyed Retrain existing employees 64% 51% Internal learning and development Look to automate the work 36%

18.3% Private training providers

16.5% External online training 6.9% Public training providers 4.2% Private educational institutions 3.1% Public educational institutions

The Future of Jobs 96 Country Profile 1/2 Working Age Population

Poland 26,745,715

Education & skills worst best Jobs & work worst best

Digital skills among active population* 55.6% Labour force participation 59% 85.3% 15.9% WEIGHTED AVERAGE 2019-2020 2019 40.7% 42.1% Attainment of basic education 25% Vulnerable employment 50.6% 2.8% 2016 52.7% 2020 1.8% 2.7% Business relevance of basic education* 7.9% Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education Unemployment rate

2016 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 J U LY 2 0 2 0

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Artificial intelligence (e.g. machine learning, 87% neural networks, NLP) 86% conferencing) Cloud computing 80% 85.7% 73% Big data analytics 71% Provide more opportunities to work remotely 69% E-commerce and digital trade 69% 71.4% Robots, non-humanoid (industrial automation, 67% drones, etc.) 60% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Power storage and generation 46%

providers) Text, image and voice processing New materials (e.g. nanotubes, graphene)

EMERGING AI and Machine Learning Specialists Emerging skills 1. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered 2. Database and Network Professionals by frequency 4. Social Media Strategist 1. Creativity, originality and initiative 5. Materials Engineers 6. Business Development Professionals 2. Active learning and learning strategies 8. Robotics Engineers 3. Resilience, stress tolerance and flexibility 10. 4. Complex problem-solving

REDUNDANT 5. Analytical thinking and innovation

1. Data Entry Clerks 6. Technology use, monitoring and control

2. Administrative and Executive Secretaries 7. Service orientation

3. Accounting, Bookkeeping and Payroll Clerks 8. Critical thinking and analysis

4. Material-Recording and Stock-Keeping Clerks 9. Technology design and programming

5. Financial Analysts 10. Reasoning, problem-solving and ideation

6. Assembly and Factory Workers 11. Management of personnel

7. Accountants and Auditors 12. Emotional intelligence

8. Car, Van and Motorcycle Drivers 13. Management of financial, material resources

9. Business Services and Administration Managers 14. Leadership and social influence

10. Architects and Surveyors 15. Instruction, mentoring and teaching

The Future of Jobs 97

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Active learning and learning strategies Less than 1 month 6 to 12 months 27.2% 20.6%

2. Resilience, stress tolerance and flexibility

3. Management of personnel

4. Analytical thinking and innovation

5. Technology design and programming Over 1 year 25% 10. Service orientation 1 to 3 months 3 to 6 months 13.2% 14%

Responses to shifting skill needs 89% Projected use of training providers Share of companies surveyed 78% Share of companies surveyed Retrain existing employees 67% 39.8% Internal learning and development Expect existing employees to pick up skills on 56%

14.3% Private training providers 11.4% Public educational institutions

4.1% Private educational institutions

The Future of Jobs 98 Country Profile 1/2 Working Age Population

Russian Federation 106,913,416

Education & skills worst best Jobs & work worst best

Digital skills among active population* 66% Labour force participation 66.1% 5.3% WEIGHTED AVERAGE 2019-2020 48% 2019 42.4% Attainment of basic education 53.1% Vulnerable employment 59.2% 3.8% — 2020 3.6% Business relevance of basic education* 9.2% Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education Unemployment rate

— 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 80% Big data analytics 76% 80.6% 73% Encryption and cyber security 72% Accelerate the digitalization of work processes (e.g. use of digital tools, video 71% Text, image and voice processing 67% conferencing) Artificial intelligence (e.g. machine learning, 66% 80.6% neural networks, NLP) 65% E-commerce and digital trade 50% Accelerate automation of tasks Robots, non-humanoid (industrial automation, 48% 47.2% Internet of things and connected devices

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Augmented and virtual reality

providers) Power storage and generation

30.6%

EMERGING AI and Machine Learning Specialists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Software and Applications Developers by frequency 3. Sales Representatives, Wholesale and Manufacturing, Technic… 4. Process Automation Specialists 1. Complex problem-solving 5. Management and Organisation Analysts 6. Digital Marketing and Strategy Specialists 2. Analytical thinking and innovation 8. Business Services and Administration Managers 3. Active learning and learning strategies 10. 4. Emotional intelligence

REDUNDANT 5. Resilience, stress tolerance and flexibility

1. Accounting, Bookkeeping and Payroll Clerks 6. Critical thinking and analysis

2. Administrative and Executive Secretaries 7. Technology use, monitoring and control

3. Data Entry Clerks 8. Creativity, originality and initiative

4. Sales Representatives, Wholesale and Manufacturing, Technic… 9. Troubleshooting and user experience

5. Accountants and Auditors 10. Technology design and programming

6. Lawyers 11. Service orientation

7. Mechanics and Machinery Repairers 12. Reasoning, problem-solving and ideation

8. Legal Secretaries 13. Leadership and social influence

9. Door-To-Door Sales Workers, News and Street Vendors, and R… 14. Persuasion and negotiation

10. Assembly and Factory Workers 15. Attention to detail, trustworthiness

The Future of Jobs 99

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Creativity, originality and initiative Less than 1 month 3 to 6 months 22.6% 16.1%

2. Emotional intelligence 6 to 12 months 7. Leadership and social influence Over 1 year 8. Critical thinking and analysis

3. Reasoning, problem-solving and ideation 1 to 3 months 21.2%

Responses to shifting skill needs 83% Projected use of training providers Share of companies surveyed 72% Share of companies surveyed Expect existing employees to pick up skills on 57% 38.6% Internal learning and development the job 57% 43% 18.3% External online training Retrain existing employees 15.9% Private training providers

Hire new permanent staff with skills relevant to 9.9% Public educational institutions new technologies 9.6% Public training providers 7.8% Private educational institutions

The Future of Jobs 100 Country Profile 1/2 Working Age Population

Saudi Arabia 20,518,278

Education & skills worst best Jobs & work worst best

Digital skills among active population* 73.9% Labour force participation 64.4% 68.8% 3% WEIGHTED AVERAGE 2019-2020 51.1% 2018 31.5% 30.3% Attainment of basic education 71.3% Vulnerable employment 4.5%

2017 71% 2020 7.6% Business relevance of basic education* 0.8% Working cond. impact of gig economy*

WEIGHTED AVERAGE 2019-2020 16.1% 2020

Attainment of advanced education Unemployment rate

2017 2018

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2014 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2014 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 94% Internet of things and connected devices 93% 100% 93% E-commerce and digital trade 88% Temporarily reassign workers to different tasks 86% Cloud computing 81% 85.7% Artificial intelligence (e.g. machine learning, 81% neural networks, NLP) 64% Accelerate the digitalization of work processes (e.g. use of digital tools, video Text, image and voice processing 64% conferencing) Encryption and cyber security 78.6% Robots, non-humanoid (industrial automation, Accelerate the implementation of upskilling/ reskilling programmes Distributed ledger technology (e.g. blockchain)

71.4% Augmented and virtual reality

EMERGING AI and Machine Learning Specialists Emerging skills Software and Applications Developers 1. Data Analysts and Scientists Skills identified as being in high demand within their organization, ordered 2. Digital Transformation Specialists by frequency 3. Organizational Development Specialists 4. Industrial and Production Engineers 1. Complex problem-solving 5. Mathematicians, Actuaries and Statisticians 6. Digital Marketing and Strategy Specialists 2. Leadership and social influence 8. Advertising and Public Relations Professionals 3. Analytical thinking and innovation

REDUNDANT 4. Active learning and learning strategies

1. Administrative and Executive Secretaries 5. Resilience, stress tolerance and flexibility

2. Data Entry Clerks 6. Critical thinking and analysis

3. Mechanics and Machinery Repairers 7. Technology use, monitoring and control

4. Material-Recording and Stock-Keeping Clerks 8. Troubleshooting and user experience

5. Business Services and Administration Managers 9. Creativity, originality and initiative

6. Accounting, Bookkeeping and Payroll Clerks 10. Technology design and programming

7. Accountants and Auditors 11. Systems analysis and evaluation

8. Assembly and Factory Workers 12. Service orientation

9. Sales Representatives, Wholesale and Manufacturing, Technic… 13. Reasoning, problem-solving and ideation

10. Strategic Advisors 14. Emotional intelligence

11. Attention to detail, trustworthiness

The Future of Jobs 101

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Leadership and social influence Less than 1 month 3 to 6 months 25.3% 20.3%

2. Resilience, stress tolerance and flexibility 6 to 12 months 9. Persuasion and negotiation Over 1 year 10. Management of financial, material resources 1 to 3 months 26.5%

Responses to shifting skill needs 93% Projected use of training providers Share of companies surveyed 87% Share of companies surveyed Expect existing employees to pick up skills on 64% 49.3% Internal learning and development the job 43%

25.9% External online training

9.4% Private training providers 7% Public training providers

4.5% Private educational institutions 3.9% Public educational institutions

The Future of Jobs 102 Country Profile 1/2 Working Age Population

Singapore 2,938,300

Education & skills worst best Jobs & work worst best

Digital skills among active population* 77% Labour force participation 73% 81.4% WEIGHTED AVERAGE 2019-2020 67.6% 2019 9.7% 46.7% Attainment of basic education Vulnerable employment 32.6% 79% 3.6% 2018 69.1% 2020

Business relevance of basic education* 2.6% Working cond. impact of gig economy* 3.4% WEIGHTED AVERAGE 2019-2020 4.6% 2020

Attainment of advanced education Unemployment rate

2018 2016

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2017 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2017 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Artificial intelligence (e.g. machine learning, 97% neural networks, NLP) 93% conferencing) Internet of things and connected devices 90% 100% 86% Text, image and voice processing 86% Provide more opportunities to work remotely 83% Big data analytics 76% 95.5% 75% E-commerce and digital trade 69% Accelerate the implementation of upskilling/ reskilling programmes 61% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Robots, non-humanoid (industrial automation, providers) Power storage and generation 59.1%

EMERGING Data Analysts and Scientists Emerging skills 1. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered 2. Big Data Specialists by frequency 3. Information Security Analysts 4. Digital Marketing and Strategy Specialists 1. Analytical thinking and innovation 6. FinTech Engineers 2. Active learning and learning strategies 7. Devops Engineer 8. Database and Network Professionals 3. Leadership and social influence 10. 4. Emotional intelligence

REDUNDANT 5. Creativity, originality and initiative

1. Data Entry Clerks 6. Technology design and programming

2. Accounting, Bookkeeping and Payroll Clerks 7. Complex problem-solving

3. Administrative and Executive Secretaries 8. Troubleshooting and user experience

4. Accountants and Auditors 9. Resilience, stress tolerance and flexibility

5. General and Operations Managers 10. Technology use, monitoring and control

6. Business Services and Administration Managers 11. Instruction, mentoring and teaching

7. Human Resources Specialists 12. Critical thinking and analysis

8. Client Information and Customer Service Workers 13. Technology installation and maintenance

9. Assembly and Factory Workers 14. Service orientation

10. Bank Tellers and Related Clerks 15. Reasoning, problem-solving and ideation

The Future of Jobs 103

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 27.4% 17.7%

2. Emotional intelligence 6 to 12 months 16.9% 7. Resilience, stress tolerance and flexibility Over 1 year 22.1%

3. Technology design and programming

4. Technology use, monitoring and control

Responses to shifting skill needs 1 to 3 months 15.8% 92% Projected use of training providers Hire new permanent staff with skills relevant to 92% new technologies 84% Share of companies surveyed Expect existing employees to pick up skills on 62% 42.4% Internal learning and development the job 54% 43%

24% External online training

15% Private training providers 4.2% Public educational institutions

The Future of Jobs 104 Country Profile 1/2 Working Age Population

South Africa 31,627,389

Education & skills worst best Jobs & work worst best

Digital skills among active population* 29.9% Labour force participation 64.9% 10.3% WEIGHTED AVERAGE 2019-2020 29.9% 2019 46.2% Attainment of basic education 49.7% Vulnerable employment 24.8% — 11.8% 2020 Business relevance of basic education* 32.7% Working cond. impact of gig economy*

WEIGHTED AVERAGE 2019-2020 2020

Attainment of advanced education Unemployment rate

— 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate automation of tasks Artificial intelligence (e.g. machine learning, 93% neural networks, NLP) 93% 75% Text, image and voice processing 87% Provide more opportunities to work remotely Internet of things and connected devices 87% 62.5% Encryption and cyber security 86% Accelerate the digitalization of work processes (e.g. use of digital tools, video Big data analytics 79% Robots, non-humanoid (industrial automation, 71% conferencing) drones, etc.) 62.5% Augmented and virtual reality

Accelerate ongoing organizational transformations (e.g. restructuring) E-commerce and digital trade

37.5% Distributed ledger technology (e.g. blockchain)

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

EMERGING Process Automation Specialists Emerging skills 1. Social Psychologists Skills identified as being in high demand within their organization, ordered 2. Management and Organisation Analysts by frequency 3. Business Development Professionals 4. Big Data Specialists 1. Analytical thinking and innovation 5. Assembly and Factory Workers 6. Compliance Officers 2. Critical thinking and analysis 7. Chemists and Chemical Laboratory Scientists 8. AI and Machine Learning Specialists 3. Troubleshooting and user experience 10. 4. Leadership and social influence

REDUNDANT 5. Complex problem-solving

1. Accounting, Bookkeeping and Payroll Clerks 6. Systems analysis and evaluation

2. Client Information and Customer Service Workers 7. Creativity, originality and initiative

3. Data Entry Clerks 8. Technology use, monitoring and control

4. Administrative and Executive Secretaries 9. Quality control and safety awareness

5. Vehicle, Window, Laundry and Other Hand Cleaning Workers 10. Persuasion and negotiation

6. Sales Representatives, Wholesale and Manufacturing, Technic… 11. Emotional intelligence

7. Insurance Underwriters 12. Technology installation and maintenance

8. Business Services and Administration Managers 13. Resilience, stress tolerance and flexibility

9. Assembly and Factory Workers 14. Reasoning, problem-solving and ideation

10. Accountants and Auditors 15. Active learning and learning strategies

The Future of Jobs 105

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 15.7% 18%

2. Technology design and programming

3. Critical thinking and analysis 6 to 12 months 7. Reasoning, problem-solving and ideation 1 to 3 months 27.7% 8. Creativity, originality and initiative

4. Active learning and learning strategies

Responses to shifting skill needs Over 1 year 82% Projected use of training providers Look to automate the work 73% 64% Share of companies surveyed Retrain existing employees 64% 64% 55.9% Internal learning and development Strategic redundancies of staff who lack the skills 55% to use new technologies ­

15.8% External online training

9.5% Private training providers 7.3% Public educational institutions 7.3% Public training providers 4.2% Private educational institutions

The Future of Jobs 106 Country Profile 1/2 Working Age Population

Spain 35,092,188

Education & skills worst best Jobs & work worst best

Digital skills among active population* 55.2% Labour force participation 61.2% 77.7% 11% WEIGHTED AVERAGE 2019-2020 2019 52.4% 45.5% Attainment of basic education 31.1% Vulnerable employment 12.8% 2018 59.7% 2020 15.3% 13.7% Business relevance of basic education* 8% Working cond. impact of gig economy* 18.2% 1.1% WEIGHTED AVERAGE 2019-2020 2020 0.8% Attainment of advanced education Unemployment rate 1.5%

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 J U LY 2 0 2 0

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video Artificial intelligence (e.g. machine learning, 96% neural networks, NLP) 96% conferencing) Cloud computing 92% 92.9% 88% Encryption and cyber security 88% Provide more opportunities to work remotely 84% E-commerce and digital trade 77% 85.7% 74% Text, image and voice processing 70% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 68% 78.6% Distributed ledger technology (e.g. blockchain)

Accelerate automation of tasks New materials (e.g. nanotubes, graphene) 64.3% drones, etc.)

EMERGING Internet of Things Specialists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. AI and Machine Learning Specialists by frequency 4. Software and Applications Developers 1. Analytical thinking and innovation 6. Process Automation Specialists 2. Active learning and learning strategies 8. Assembly and Factory Workers 3. Critical thinking and analysis 10. 4. Creativity, originality and initiative

REDUNDANT 5. Complex problem-solving

1. Data Entry Clerks 6. Technology use, monitoring and control

2. Administrative and Executive Secretaries 7. Resilience, stress tolerance and flexibility

3. Accounting, Bookkeeping and Payroll Clerks 8. Leadership and social influence

4. Accountants and Auditors 9. Technology design and programming

5. Statistical, Finance and Insurance Clerks 10. Emotional intelligence

6. Business Services and Administration Managers 11. Systems analysis and evaluation

7. Financial Analysts 12. Persuasion and negotiation

8. Client Information and Customer Service Workers 13. Troubleshooting and user experience

9. Claims Adjusters, Examiners, and Investigators 14. Service orientation

10. Assembly and Factory Workers 15. Reasoning, problem-solving and ideation

The Future of Jobs 107

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 21.2% 16.8%

2. Management of personnel Over 1 year 8. Systems analysis and evaluation 1 to 3 months 15.4%

Responses to shifting skill needs 95% 3 to 6 months 85% 15.4% Share of companies surveyed 85% 70% Projected use of training providers Retrain existing employees 45% 45% Share of companies surveyed Look to automate the work 33% 45.5% Internal learning and development

6.8% Private educational institutions 5.7% Public educational institutions

The Future of Jobs 108 Country Profile 1/2 Working Age Population

Switzerland 6,326,839

Education & skills worst best Jobs & work worst best

Digital skills among active population* 72% Labour force participation 68.5% 97.1% 8.9% WEIGHTED AVERAGE 2019-2020 2019 77.9% 40.9% Attainment of basic education 39% Vulnerable employment 2018 82.3% 2020 62.7% 4.1% Business relevance of basic education* 3.2% Working cond. impact of gig economy* 4.1% WEIGHTED AVERAGE 2019-2020 6.7% 2020 0.2% -0.4% Attainment of advanced education Unemployment rate 2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 JUNE 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely 95% Big data analytics 91% 90.9% Artificial intelligence (e.g. machine learning, 90% neural networks, NLP) 90% Accelerate the digitalization of work processes (e.g. use of digital tools, video E-commerce and digital trade 86% conferencing) Internet of things and connected devices 77% 90.9% 76% Distributed ledger technology (e.g. blockchain) 71% Accelerate automation of tasks 65% 72.7% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology providers) Robots, non-humanoid (industrial automation, 45.5% drones, etc.)

EMERGING Data Analysts and Scientists Emerging skills 1. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered 2. Process Automation Specialists by frequency 4. Strategic Advisors 1. Analytical thinking and innovation 6. Information Security Analysts 2. Active learning and learning strategies 8. Biologists and Geneticists 3. Complex problem-solving 10. 4. Technology use, monitoring and control

REDUNDANT 5. Technology design and programming

1. Accounting, Bookkeeping and Payroll Clerks 6. Resilience, stress tolerance and flexibility

2. Data Entry Clerks 7. Critical thinking and analysis

3. Administrative and Executive Secretaries 8. Instruction, mentoring and teaching

4. Accountants and Auditors 9. Emotional intelligence

5. Business Services and Administration Managers 10. Service orientation

6. Human Resources Specialists 11. Creativity, originality and initiative

7. Financial Analysts 12. Systems analysis and evaluation

8. Claims Adjusters, Examiners, and Investigators 13. Technology installation and maintenance

9. Cashiers and Ticket Clerks 14. Reasoning, problem-solving and ideation

10. Assembly and Factory Workers 15. Leadership and social influence

The Future of Jobs 109

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Complex problem-solving Less than 1 month 6 to 12 months 20.6% 19.5%

2. Resilience, stress tolerance and flexibility 1 to 3 months 15.5% 8. Leadership and social influence 3 to 6 months 9. Technology design and programming Over 1 year

Responses to shifting skill needs 94% Projected use of training providers Share of companies surveyed 88% Share of companies surveyed Look to automate the work 47% 35.5% Internal learning and development Retrain existing employees 38%

25.4% External online training

17.2% Private training providers

8.3% Private educational institutions 6.5% Public educational institutions

The Future of Jobs 110 Country Profile 1/2 Working Age Population

Thailand 47,215,919

Education & skills worst best Jobs & work worst best

Digital skills among active population* 54.9% Labour force participation 0.3% 72.2% 45.1% 0.5% 48.2% WEIGHTED AVERAGE 2019-2020 46% 2019 39.7% Attainment of basic education 19.1% Vulnerable employment 60.5% 0.3% 2016 2020 0.2% 53.6% 0.3% Business relevance of basic education* 0.6% Working cond. impact of gig economy* 0.3% WEIGHTED AVERAGE 2019-2020 2020 Attainment of advanced education Unemployment rate

2016 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 98% Internet of things and connected devices 95% conferencing) 90% 84.4% Encryption and cyber security 87% 85% Provide more opportunities to work remotely E-commerce and digital trade 80% 75% Big data analytics 67% Artificial intelligence (e.g. machine learning, 62% Accelerate automation of tasks neural networks, NLP) 59% 50% Robots, non-humanoid (industrial automation, Accelerate the implementation of upskilling/ reskilling programmes Power storage and generation

40.6% Distributed ledger technology (e.g. blockchain)

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

34.4%

EMERGING Data Analysts and Scientists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. AI and Machine Learning Specialists by frequency 4. Supply Chain and Logistics Specialists 1. Analytical thinking and innovation 5. Strategic Advisors 6. Database and Network Professionals 2. Complex problem-solving 7. Commercial and Industrial Designers 8. Business Development Professionals 3. Active learning and learning strategies 10. 4. Critical thinking and analysis

REDUNDANT 5. Creativity, originality and initiative

1. Data Entry Clerks 6. Troubleshooting and user experience

2. Administrative and Executive Secretaries 7. Leadership and social influence

3. Accounting, Bookkeeping and Payroll Clerks 8. Resilience, stress tolerance and flexibility

4. Assembly and Factory Workers 9. Technology design and programming

5. Construction Laborers 10. Technology use, monitoring and control

6. Sales Representatives, Wholesale and Manufacturing, Technic… 11. Reasoning, problem-solving and ideation

7. Human Resources Specialists 12. Technology installation and maintenance

8. Financial and Investment Advisers 13. Management of personnel

9. Client Information and Customer Service Workers 14. Attention to detail, trustworthiness

10. Business Services and Administration Managers 15. Emotional intelligence

The Future of Jobs 111

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 25.2% 17.5%

2. Technology use, monitoring and control 6 to 12 months 8. Technology design and programming Over 1 year 9. Reasoning, problem-solving and ideation

3. Resilience, stress tolerance and flexibility 1 to 3 months 23.1%

Responses to shifting skill needs 91% Projected use of training providers Share of companies surveyed 81% Share of companies surveyed Expect existing employees to pick up skills on 75% 37.6% Internal learning and development the job 59% Outsource some business functions to external 56%

19.2% Private training providers

17% External online training 11.2% Public training providers

7.8% Public educational institutions

The Future of Jobs 112 Country Profile 1/2 Working Age Population

United Arab Emirates 8,112,786

Education & skills worst best Jobs & work worst best

Digital skills among active population* 71.7% Labour force participation 0.9% 85.2% 82.9% 1.8% WEIGHTED AVERAGE 2019-2020 2019 32.5% 65.3% Attainment of basic education 51.8% Vulnerable employment

2018 71% 2020 70.5% Business relevance of basic education* 3.3% Working cond. impact of gig economy* WEIGHTED AVERAGE 2019-2020 11.4% 2020

Attainment of advanced education Unemployment rate

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 —

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 —

Unempl. rate among workers with adv. educ. Unemployment rate change

2017 —

Unempl. rate among workers with basic educ. Unemployment rate change, women

2017 —

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 —

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Provide more opportunities to work remotely Internet of things and connected devices 89% Encryption and cyber security 84% 89.6% Cloud computing 84% E-commerce and digital trade 84% Accelerate the digitalization of work processes (e.g. use of digital tools, video Text, image and voice processing 81% Artificial intelligence (e.g. machine learning, 77% conferencing) neural networks, NLP) 76% 77.1% Power storage and generation 65% Augmented and virtual reality 57% Accelerate automation of tasks Distributed ledger technology (e.g. blockchain) 56%

47.9%

39.6%

EMERGING Data Analysts and Scientists Emerging skills 1. Business Development Professionals Skills identified as being in high demand within their organization, ordered 2. AI and Machine Learning Specialists by frequency 4. Process Automation Specialists 1. Analytical thinking and innovation 5. Organizational Development Specialists 6. General and Operations Managers 2. Complex problem-solving 8. Big Data Specialists 3. Critical thinking and analysis 10. 4. Active learning and learning strategies

REDUNDANT 5. Leadership and social influence

1. Administrative and Executive Secretaries 6. Technology use, monitoring and control

2. Data Entry Clerks 7. Creativity, originality and initiative

3. Accounting, Bookkeeping and Payroll Clerks 8. Service orientation

4. Postal Service Clerks 9. Resilience, stress tolerance and flexibility

5. Business Services and Administration Managers 10. Emotional intelligence

6. Mechanics and Machinery Repairers 11. Technology design and programming

7. Accountants and Auditors 12. Troubleshooting and user experience

8. Material-Recording and Stock-Keeping Clerks 13. Quality control and safety awareness

9. Client Information and Customer Service Workers 14. Systems analysis and evaluation

10. Cashiers and Ticket Clerks 15. Persuasion and negotiation

The Future of Jobs 113

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Active learning and learning strategies Less than 1 month 3 to 6 months 30.6% 18.6%

2. Critical thinking and analysis

3. Creativity, originality and initiative 6 to 12 months 9. Technology use, monitoring and control Over 1 year

21.4%

Responses to shifting skill needs 98% Projected use of training providers Share of companies surveyed 84% Share of companies surveyed Expect existing employees to pick up skills on 50% 44.3% Internal learning and development the job 49%

15.5% Private training providers 6.5% Private educational institutions 5.1% Public educational institutions

The Future of Jobs 114 Country Profile 1/2 Working Age Population

United Kingdom 46,380,358

Education & skills worst best Jobs & work worst best

Digital skills among active population* 61% Labour force participation 64.3% 99.7% 12.9% WEIGHTED AVERAGE 2019-2020 2019 52.6% 47.5% Attainment of basic education 44.1% Vulnerable employment 2017 62.5% 2020 58.6% 2.5% Business relevance of basic education* 2% Working cond. impact of gig economy* 2.7% 4.6% WEIGHTED AVERAGE 2019-2020 11.1% 2020 -0.1% -0.2% Attainment of advanced education Unemployment rate 2017 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 JUNE 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 95% Encryption and cyber security 95% conferencing) 94% 94.3% Big data analytics 94% Artificial intelligence (e.g. machine learning, 92% Provide more opportunities to work remotely neural networks, NLP) 88% Internet of things and connected devices 81% 91.4% 75% Text, image and voice processing 73% Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 69% 65.7% Augmented and virtual reality

Accelerate automation of tasks Distributed ledger technology (e.g. blockchain) 57.1% drones, etc.)

48.6%

EMERGING Data Analysts and Scientists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Internet of Things Specialists by frequency 4. Process Automation Specialists 1. Active learning and learning strategies 5. Information Security Analysts 6. FinTech Engineers 2. Analytical thinking and innovation 8. Business Development Professionals 3. Creativity, originality and initiative 10. 4. Complex problem-solving

REDUNDANT 5. Critical thinking and analysis

1. Data Entry Clerks 6. Emotional intelligence

2. Accounting, Bookkeeping and Payroll Clerks 7. Resilience, stress tolerance and flexibility

3. Administrative and Executive Secretaries 8. Leadership and social influence

4. Accountants and Auditors 9. Technology design and programming

5. General and Operations Managers 10. Reasoning, problem-solving and ideation

6. Client Information and Customer Service Workers 11. Systems analysis and evaluation

7. Assembly and Factory Workers 12. Technology use, monitoring and control

8. Business Services and Administration Managers 13. Service orientation

9. Statistical, Finance and Insurance Clerks 14. Persuasion and negotiation

10. Bank Tellers and Related Clerks 15. Instruction, mentoring and teaching

The Future of Jobs 115

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 3 to 6 months 6 to 12 months 23.4% 17.1% 16.7%

18.5% 24.3%

Responses to shifting skill needs 98% Projected use of training providers 94% Share of companies surveyed 94% Share of companies surveyed Retrain existing employees 73% 43.7% Internal learning and development Hire new permanent staff with skills relevant to 55%

21.7% External online training

17.1% Private training providers 7.4% Private educational institutions 6% Public educational institutions 4.2% Public training providers

The Future of Jobs 116 Country Profile 1/2 Working Age Population

United States 221,426,962

Education & skills worst best Jobs & work worst best

Digital skills among active population* 69.4% Labour force participation 64.3% 96% 3.8% WEIGHTED AVERAGE 2019-2020 2019 64.5% 24.8% Attainment of basic education 45.2% Vulnerable employment 3%

2018 70.5% 2020 12.2% 69.7% 7.7% Business relevance of basic education* 2.2% Working cond. impact of gig economy* 4.3% 8.5% WEIGHTED AVERAGE 2019-2020 14.1% 2020 9.3%

Attainment of advanced education Unemployment rate 7.7%

2018 2019

Business relevance of tertiary education* Unemployment rate

WEIGHTED AVERAGE 2019-2020 Q2 2020

Supply of business-relevant skills* Unemployment, monthly

WEIGHTED AVERAGE 2019-2020 AUGUST 2020

Unempl. rate among workers with adv. educ. Unemployment rate change

2019 2019- Q2 2020 YOY CH.

Unempl. rate among workers with basic educ. Unemployment rate change, women

2019 2019- Q2 2020 YOY CH.

Share of youth not in empl., educ. or training Unemployment rate change, men

2020 2019- Q2 2020 YOY CH.

• The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.

Impact of COVID-19 on companies’ strategy Technology adoption

Share of companies surveyed looking to adopt this strategy as a result of Share of companies surveyed Accelerate the digitalization of work processes (e.g. use of digital tools, video 96% Internet of things and connected devices 95% conferencing) Artificial intelligence (e.g. machine learning, 93% 91.5% neural networks, NLP) 90% Encryption and cyber security 90% Provide more opportunities to work remotely 82% Big data analytics 81% 86.4% 78% Text, image and voice processing 77% Accelerate automation of tasks 65% 57.6% Robots, non-humanoid (industrial automation, Accelerate the digitalization of upskilling/ reskilling (e.g. education technology Augmented and virtual reality

providers) Distributed ledger technology (e.g. blockchain) 54.2%

EMERGING AI and Machine Learning Specialists Emerging skills 1. Big Data Specialists Skills identified as being in high demand within their organization, ordered 2. Internet of Things Specialists by frequency 4. Process Automation Specialists 1. Analytical thinking and innovation 6. Information Security Analysts 2. Active learning and learning strategies 7. Digital Marketing and Strategy Specialists 8. Business Development Professionals 3. Complex problem-solving 10. 4. Critical thinking and analysis

REDUNDANT 5. Resilience, stress tolerance and flexibility

1. Data Entry Clerks 6. Creativity, originality and initiative

2. Accounting, Bookkeeping and Payroll Clerks 7. Leadership and social influence

3. Administrative and Executive Secretaries 8. Reasoning, problem-solving and ideation

4. Assembly and Factory Workers 9. Emotional intelligence

5. Accountants and Auditors 10. Technology design and programming

6. Client Information and Customer Service Workers 11. Technology use, monitoring and control

7. Business Services and Administration Managers 12. Systems analysis and evaluation

8. General and Operations Managers 13. Troubleshooting and user experience

9. Mechanics and Machinery Repairers 14. Service orientation

10. Human Resources Specialists 15. Persuasion and negotiation

The Future of Jobs 117

Current skills in focus of existing reskilling/upskilling Average reskilling needs across their reskilling or upskilling programmes DURATION OF RESKILLING

1. Analytical thinking and innovation Less than 1 month 6 to 12 months 18.7% 17%

2. Technology use, monitoring and control 1 to 3 months 8. Creativity, originality and initiative Over 1 year 28% 9. Emotional intelligence

3. Reasoning, problem-solving and ideation

Responses to shifting skill needs 95% 3 to 6 months 93% 17.7% Share of companies surveyed 91% 85% Projected use of training providers Retrain existing employees 67% 54% Share of companies surveyed Expect existing employees to pick up skills on 51% 42.8% Internal learning and development

21.9% External online training

14.3% Private training providers 8.1% Public educational institutions 7% Private educational institutions

The Future of Jobs 118

Industry

The Future of Jobs 119 Industry Profile 1/2

14% Expected redeployment Average skills success rate of displaced instability among

workers workforce

41.3% 43.6%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 89% 1. Technology use, monitoring and control Internet of things and connected devices 87% Robots, non-humanoid (industrial automation, 85% 2. Critical thinking and analysis drones, etc.) 83% E-commerce and digital trade 76% 3. Active learning and learning strategies Big data analytics 74% 4. Leadership and social influence Encryption and cyber security 62% 5. Analytical thinking and innovation 3D and 4D printing and modelling 6. Reasoning, problem-solving and ideation Artificial intelligence (e.g. machine learning, neural networks, NLP) 7. Complex problem-solving 8. Service orientation 9. Resilience, stress tolerance and flexibility

10. Technology design and programming

11. Troubleshooting and user experience

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Business Development Professionals Software and Applications Developers 76.9% 1. Sales Representatives, Wholesale and Manufacturing, Technic… Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Internet of Things Specialists 4. Data Analysts and Scientists conferencing) 5. Project Managers 73.1% 6. Power Production Plant Operators 7. Assembly and Factory Workers Accelerate automation of tasks 57.7% 8. AI and Machine Learning Specialists Temporarily reduce workforce 38.5% 9.

1. Assembly and Factory Workers

2. Relationship Managers

3. Sales Representatives, Wholesale and Manufacturing, Technic…

4. Administrative and Executive Secretaries

5. Accounting, Bookkeeping and Payroll Clerks

The Future of Jobs 120

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 67.7% Modify the composition of the value chain Skills gaps among organization’s leadership 54.8% Inability to attract specialized talent 67.7% Shortage of investment capital 45.2% Insufficient understanding of opportunities 41.9% Expand its use of contractors doing task-specialized work Lack of flexibility of the regulatory framework 38.7% Lack of flexibility in hiring and firing 25.8% 48.4% Lack of interest among leadership 19.4% Other 9.7% Reduce its current workforce due to technological integration or automation 6.5% 45.2%

1. Technology use, monitoring and control

Augmentation of key job tasks by 2024 3. Complex problem-solving

4. Technology installation and maintenance

Machine share Human share 5. Critical thinking and analysis

Information and data processing 8. Service orientation

38.3% 9. Management of financial, material resources

Performing physical and manual work activities 10. Leadership and social influence

Looking for and receiving job-related information Average reskilling needs

All tasks DURATION OF RESKILLING

48.5% Less than 1 month 3 to 6 months 26.8% 16.6%

Performing complex and technical activities 6 to 12 months 52.6% Over 1 year

59% 1 to 3 months

The Future of Jobs 121 Industry Profile 1/2

Agriculture, Food and Beverage

11.2% Expected redeployment Average skills

47.6% 35.8%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 88% 1. Active learning and learning strategies Big data analytics 86% 80% 2. Analytical thinking and innovation E-commerce and digital trade 75% 75% 3. Technology use, monitoring and control Power storage and generation 62% 54% 4. Quality control and safety awareness Cloud computing 54% Artificial intelligence (e.g. machine learning, neural 50% 5. Creativity, originality and initiative networks, NLP) 50% Robots, non-humanoid (industrial automation, 6. Management of personnel 3D and 4D printing and modelling 7. Leadership and social influence

Text, image and voice processing 8. Instruction, mentoring and teaching

Biotechnology 9. Emotional intelligence

10. Complex problem-solving

11. Reasoning, problem-solving and ideation

12. Management of financial, material resources

13. Critical thinking and analysis

14. Coordination and time management

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Data Analysts and Scientists Car, Van and Motorcycle Drivers conferencing) 1. Digital Marketing and Strategy Specialists 75% 2. Database and Network Professionals 3. Cashiers and Ticket Clerks Provide more opportunities to work remotely 4. Business Services and Administration Managers 5. Business Development Professionals 66.7% 6. Big Data Specialists 7. AI and Machine Learning Specialists Temporarily reduce workforce 8. Advertising and Public Relations Professionals 50% 10.

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

41.7% REDUNDANT

5. Internet of Things Specialists

6. Food Processing and Related Trades Workers

7. Construction Laborers

8. Assembly and Factory Workers

9. AI and Machine Learning Specialists

The Future of Jobs 122

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 52.9% Modify the composition of the value chain Inability to attract specialized talent 52.9% Skills gaps among organization’s leadership 70.6% Lack of flexibility in hiring and firing 47.1% Insufficient understanding of opportunities 41.2% Reduce its current workforce due to technological integration or automation Lack of flexibility of the regulatory framework 35.3% 41.2% Shortage of investment capital 29.4% Lack of interest among leadership 23.5% Expand its current workforce 17.6% 35.3%

1. Leadership and social influence

Augmentation of key job tasks by 2024 2. Analytical thinking and innovation

Machine share Human share 3. Active learning and learning strategies

5. Quality control and safety awareness

Information and data processing 6. Critical thinking and analysis

48.1% 7. Creativity, originality and initiative

All tasks 8. Emotional intelligence

9. Complex problem-solving

49.6% 10. Persuasion and negotiation

Looking for and receiving job-related information 53.7%

Performing physical and manual work activities Average reskilling needs

59.1% Share of workforce within this industry

Performing complex and technical activities DURATION OF RESKILLING 3 to 6 months 21.1% 59.4% Less than 1 month 38.6%

62.6%

69.2%

Communicating and interacting 6 to 12 months 6.8% 73% Over 1 year Coordinating, developing, managing and advising 1 to 3 months 20.8% 82.9%

The Future of Jobs 123 Industry Profile 1/2

Automotive Expected redeployment Average skills 19.1% of displacement 44.4% 55.2%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 88% 1. Analytical thinking and innovation Encryption and cyber security 88% 82% 2. Critical thinking and analysis Internet of things and connected devices 80% 76% 3. Complex problem-solving Cloud computing 75% Artificial intelligence (e.g. machine learning, neural 67% 4. Systems analysis and evaluation networks, NLP) 64% E-commerce and digital trade 60% 5. Resilience, stress tolerance and flexibility 3D and 4D printing and modelling 6. Active learning and learning strategies

Power storage and generation 7. Creativity, originality and initiative drones, etc.) 8. Troubleshooting and user experience 9. Reasoning, problem-solving and ideation

10. Attention to detail, trustworthiness

11. Technology design and programming

12. Persuasion and negotiation

13. Technology installation and maintenance

14. Management of personnel

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Data Analysts and Scientists Business Development Professionals conferencing) 1. AI and Machine Learning Specialists 82.4% 2. Strategic Advisors 3. Materials Engineers Provide more opportunities to work remotely 4. Management and Organisation Analysts 5. Digital Transformation Specialists 64.7% 6. Database and Network Professionals 7. Environmental Protection Professionals Accelerate ongoing organizational transformations (e.g. restructuring) 58.8% 8. Robotics Engineers Temporarily reduce workforce 41.2% 9.

4. Material-Recording and Stock-Keeping Clerks

5. Cashiers and Ticket Clerks

6. Assembly and Factory Workers

7. Sales Representatives, Wholesale and Manufacturing, Technic…

8. Door-To-Door Sales Workers, News and Street Vendors, and R…

9. Agricultural Inspectors

The Future of Jobs 124

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 50% Modify the locations where the organization operates Skills gaps among organization’s leadership 44.4% Inability to attract specialized talent 44.4% 66.7% Lack of flexibility of the regulatory framework 38.9% Reduce its current workforce due to technological integration or automation Lack of interest among leadership 33.3% 61.1% Lack of flexibility in hiring and firing 27.8% Insufficient understanding of opportunities 27.8% Modify the composition of the value chain

Reduce its current workforce

38.9%

Augmentation of key job tasks by 2024 2. Critical thinking and analysis

Machine share Human share 3. Technology use, monitoring and control

Information and data processing 6. Complex problem-solving

46.5% 7. Reasoning, problem-solving and ideation

Looking for and receiving job-related information 8. Quality control and safety awareness 9. Persuasion and negotiation

10. Management of financial, material resources

49.3%

Administering Average reskilling needs

58.2% Share of workforce within this industry

Performing complex and technical activities DURATION OF RESKILLING 3 to 6 months 58.6% Less than 1 month

63.1%

Performing physical and manual work activities 6 to 12 months 14.1% 63.3% Over 1 year

66.2% 1 to 3 months

The Future of Jobs 125 Industry Profile 1/2

Consumer Expected redeployment Average skills of displacement 49.9% 43.2%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 94% 1. Complex problem-solving Big data analytics 91% 85% 2. Analytical thinking and innovation Encryption and cyber security 85% 82% 3. Active learning and learning strategies E-commerce and digital trade 82% 73% 4. Creativity, originality and initiative Cloud computing 59% 58% 5. Technology use, monitoring and control Text, image and voice processing 52% Artificial intelligence (e.g. machine learning, neural 6. Leadership and social influence Power storage and generation 7. Critical thinking and analysis

Augmented and virtual reality 8. Troubleshooting and user experience drones, etc.) 9. Service orientation

10. Systems analysis and evaluation

11. Management of financial, material resources

12. Attention to detail, trustworthiness

13. Reasoning, problem-solving and ideation

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Data Analysts and Scientists 81% 1. AI and Machine Learning Specialists 2. Process Automation Specialists Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Food Processing and Related Trades Workers 4. Organizational Development Specialists conferencing) 5. Management and Organisation Analysts 76.2% 6. Database and Network Professionals 7. Business Development Professionals Accelerate automation of tasks 52.4% 8. Assembly and Factory Workers Temporarily reassign workers to different tasks 47.6% 9. Permanently reduce workforce

5. Mechanics and Machinery Repairers

6. Sales Representatives, Wholesale and Manufacturing, Technic…

7. Material-Recording and Stock-Keeping Clerks

8. Door-To-Door Sales Workers, News and Street Vendors, and R…

9. Assembly and Factory Workers

The Future of Jobs 126

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 48.5% Modify the composition of the value chain Insufficient understanding of opportunities 42.4% Inability to attract specialized talent 36.4% 58.8% Skills gaps among organization’s leadership 33.3% Shortage of investment capital 24.2% Reduce its current workforce due to technological integration or automation Lack of interest among leadership 21.2% 32.4% Lack of flexibility in hiring and firing 21.2% Lack of flexibility of the regulatory framework 18.2% Modify the locations where the organization operates Other 3%

1. Active learning and learning strategies

2. Management of personnel

Augmentation of key job tasks by 2024 3. Leadership and social influence

4. Analytical thinking and innovation

Machine share Human share 5. Creativity, originality and initiative

7. Critical thinking and analysis

Information and data processing 8. Coordination and time management

38.3% 9. Complex problem-solving

Looking for and receiving job-related information 10. Reasoning, problem-solving and ideation

Identifying and evaluating job-relevant information Average reskilling needs 50.3% 50.7% 3 to 6 months Less than 1 month 22.4% Performing complex and technical activities 24%

53.9%

56.4%

59.6%

Communicating and interacting 1 to 3 months 6 to 12 months 26.9% 12.5% 64.7% Over 1 year

72.5%

The Future of Jobs 127 Industry Profile 1/2

Digital Communications and Information Technology

17.5% Expected redeployment Average skills

49.4% 44.1%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 95% 1. Analytical thinking and innovation Big data analytics 95% Artificial intelligence (e.g. machine learning, neural 95% 2. Technology design and programming networks, NLP) 95% Encryption and cyber security 92% 3. Complex problem-solving Internet of things and connected devices 82% 4. Active learning and learning strategies 73% Text, image and voice processing 72% 5. Resilience, stress tolerance and flexibility E-commerce and digital trade 6. Creativity, originality and initiative

Augmented and virtual reality 7. Critical thinking and analysis

Distributed ledger technology (e.g. blockchain) 8. Reasoning, problem-solving and ideation drones, etc.) 9. Leadership and social influence

10. Technology use, monitoring and control

11. Emotional intelligence

12. Troubleshooting and user experience

13. Service orientation

14. Persuasion and negotiation

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING AI and Machine Learning Specialists conferencing) 1. Big Data Specialists 90% 2. Information Security Analysts 3. Process Automation Specialists Provide more opportunities to work remotely 4. Digital Marketing and Strategy Specialists 5. Software and Applications Developers 86.7% 6. Digital Transformation Specialists Accelerate the implementation of upskilling/ reskilling programmes 63.3% 8. Architects and Surveyors Accelerate automation of tasks 53.3% 9. Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

4. Client Information and Customer Service Workers

5. Accountants and Auditors

6. Electronics and Telecommunications Installers and Repairers

7. Architects and Surveyors

8. Business Services and Administration Managers

The Future of Jobs 128

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 60% Modify the locations where the organization operates Inability to attract specialized talent 55% Skills gaps among organization’s leadership 51.2% Lack of flexibility of the regulatory framework 45% Insufficient understanding of opportunities 42.5% Modify the composition of the value chain Shortage of investment capital 32.5% Lack of flexibility in hiring and firing 30% 48.8% Lack of interest among leadership 27.5% Other 17.5% Expand its use of contractors doing task-specialized work 12.5% 48.8%

46.5%

39.5%

2. Technology design and programming

Augmentation of key job tasks by 2024 3. Technology use, monitoring and control

Machine share Human share 5. Critical thinking and analysis

7. Systems analysis and evaluation

Information and data processing 8. Reasoning, problem-solving and ideation

29.3% 9. Creativity, originality and initiative

Looking for and receiving job-related information 10. Leadership and social influence

Administering Average reskilling needs

46.6% Share of workforce within this industry

All tasks DURATION OF RESKILLING

49% Less than 1 month 3 to 6 months 26.2% 19.3%

49.5%

50.8%

Identifying and evaluating job-relevant information 6 to 12 months 53.8% 16.1% Reasoning and decision-making 18.7%

Communicating and interacting 1 to 3 months

65.2%

The Future of Jobs 129 Industry Profile 1/2

Education Expected redeployment Average skills 13.9% of displacement 30.9% 41.3%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered Big data analytics 95% 1. Creativity, originality and initiative Text, image and voice processing 95% Encryption and cyber security 89% 2. Active learning and learning strategies Artificial intelligence (e.g. machine learning, neural 86% networks, NLP) 76% 3. Technology design and programming E-commerce and digital trade 72% Augmented and virtual reality 70% 4. Emotional intelligence 3D and 4D printing and modelling 69% New materials (e.g. nanotubes, graphene) 67% 5. Critical thinking and analysis Internet of things and connected devices 62% 6. Complex problem-solving

7. Analytical thinking and innovation

8. Reasoning, problem-solving and ideation

9. Service orientation

10. Resilience, stress tolerance and flexibility

11. Leadership and social influence

12. Persuasion and negotiation

13. Technology use, monitoring and control

14. Instruction, mentoring and teaching

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Vocational Education Teachers University and Higher Education Teachers conferencing) 1. Strategic Advisors 100% 2. Robotics Engineers 3. Management and Organisation Analysts Provide more opportunities to work remotely 4. Information Security Analysts 88.2% 6. Business Development Professionals 7. Advertising and Public Relations Professionals Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 8. Agricultural Equipment Operators providers) 10. 70.6%

35.3% REDUNDANT

4. Statistical, Finance and Insurance Clerks

5. Postal Service Clerks

6. Business Services and Administration Managers

7. Technical Specialists

8. Insurance Underwriters

9. Building Caretakers and Housekeepers

The Future of Jobs 130

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Insufficient understanding of opportunities 68.2% Expand its current workforce Shortage of investment capital 50% Skills gaps in the local labour market 57.1% Skills gaps among organization’s leadership 45.5% Inability to attract specialized talent 45.5% Modify the locations where the organization operates Lack of flexibility of the regulatory framework 45.5% Lack of interest among leadership 31.8% 52.4% Lack of flexibility in hiring and firing 27.3% Other 22.7% Modify the composition of the value chain 9.1%

Augmentation of key job tasks by 2024 3. Reasoning, problem-solving and ideation

Machine share Human share 5. Active learning and learning strategies

7. Complex problem-solving

Information and data processing 8. Emotional intelligence

32.3% 9. Management of personnel

Administering 10. Persuasion and negotiation

Identifying and evaluating job-relevant information Average reskilling needs 48.2%

Looking for and receiving job-related information DURATION OF RESKILLING 3 to 6 months 49.1% 17.2% Performing physical and manual work activities 25.2%

All tasks 6 to 12 months 59.4% Over 1 year

60.9% 1 to 3 months 24.5%

64.9%

The Future of Jobs 131 Industry Profile 1/2

Energy Utilities & Technologies

11.8% Expected redeployment Average skills

51.1% 39.4%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered Text, image and voice processing 94% 1. Critical thinking and analysis Encryption and cyber security 88% Cloud computing 88% 2. Complex problem-solving Power storage and generation 88% Artificial intelligence (e.g. machine learning, neural 88% 3. Creativity, originality and initiative networks, NLP) 81% Big data analytics 76% 4. Analytical thinking and innovation Augmented and virtual reality 75% E-commerce and digital trade 71% 5. Active learning and learning strategies 3D and 4D printing and modelling 69% 6. Technology design and programming

8. Troubleshooting and user experience

9. Leadership and social influence

10. Technology use, monitoring and control

11. Resilience, stress tolerance and flexibility

12. Emotional intelligence

13. Reasoning, problem-solving and ideation

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Data Analysts and Scientists Renewable Energy Engineers 100% 1. Big Data Specialists 2. AI and Machine Learning Specialists Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Software and Applications Developers 4. Mechanics and Machinery Repairers conferencing) 5. Internet of Things Specialists 100% 6. Construction Laborers Accelerate automation of tasks 8. Robotics Engineers 69.2% 10.

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

46.2% REDUNDANT

2. Mining and Petroleum Extraction Workers

3. Power Production Plant Operators

4. Mining and Petroleum Plant Operators

5. Mechanics and Machinery Repairers

6. Legal Secretaries

7. Data Entry Clerks

8. Data Analysts and Scientists

The Future of Jobs 132

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 70.6% Modify the composition of the value chain Insufficient understanding of opportunities 58.8% Lack of flexibility of the regulatory framework 58.8% Skills gaps among organization’s leadership 41.2% Shortage of investment capital 35.3% Modify the locations where the organization operates Inability to attract specialized talent 35.3% Lack of flexibility in hiring and firing 35.3% 47.1% Lack of interest among leadership 23.5% Other 17.6% Expand its use of contractors doing task-specialized work 5.9%

Reduce its current workforce due to technological integration or automation

1. Critical thinking and analysis

Augmentation of key job tasks by 2024 3. Technology design and programming

4. Complex problem-solving

Machine share Human share 5. Reasoning, problem-solving and ideation

6. Quality control and safety awareness

Information and data processing 8. Systems analysis and evaluation

31.6% 9. Management of personnel

Looking for and receiving job-related information 10. Active learning and learning strategies 40.4%

Performing physical and manual work activities Average reskilling needs 45.4% 54.6% 6 to 12 months Less than 1 month 12.8% Administering 24%

56.8%

57.3%

All tasks Over 1 year 31.4%

61.4%

Communicating and interacting 1 to 3 months 17.5%

73.3%

Reasoning and decision-making 3 to 6 months

The Future of Jobs 133 Industry Profile 1/2

20.8% Expected redeployment Average skills of displacement workers workforce

50.5% 44.1%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered Encryption and cyber security 98% 1. Analytical thinking and innovation Big data analytics 95% E-commerce and digital trade 91% 2. Critical thinking and analysis Artificial intelligence (e.g. machine learning, neural 90% networks, NLP) 90% 3. Creativity, originality and initiative Text, image and voice processing 88% Internet of things and connected devices 88% 4. Complex problem-solving Distributed ledger technology (e.g. blockchain) 73% Augmented and virtual reality 62% 5. Active learning and learning strategies Power storage and generation 55% 6. Technology design and programming

7. Troubleshooting and user experience

8. Emotional intelligence

9. Technology use, monitoring and control

10. Leadership and social influence

11. Reasoning, problem-solving and ideation

12. Resilience, stress tolerance and flexibility

13. Systems analysis and evaluation

14. Instruction, mentoring and teaching

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Data Analysts and Scientists conferencing) 1. Digital Marketing and Strategy Specialists 83.3% 2. AI and Machine Learning Specialists Provide more opportunities to work remotely 4. Information Security Analysts 5. Database and Network Professionals 76.7% 6. Business Development Professionals Accelerate automation of tasks 8. Cyber Security Specialists 43.3% 10.

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

30% REDUNDANT

5. Client Information and Customer Service Workers

6. Bank Tellers and Related Clerks

7. Statistical, Finance and Insurance Clerks

8. Insurance Underwriters

9. General and Operations Managers

The Future of Jobs 134

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 58.5% Modify the composition of the value chain Inability to attract specialized talent 51.2% Skills gaps among organization’s leadership 54.8% Lack of flexibility of the regulatory framework 48.8% Insufficient understanding of opportunities 43.9% Reduce its current workforce due to technological integration or automation Shortage of investment capital 41.5% 50% Lack of flexibility in hiring and firing 19.5% Lack of interest among leadership 19.5% Modify the locations where the organization operates

1. Leadership and social influence

Augmentation of key job tasks by 2024 2. Analytical thinking and innovation

Machine share Human share 3. Critical thinking and analysis

Information and data processing 6. Technology use, monitoring and control

25.7% 7. Active learning and learning strategies

Looking for and receiving job-related information 8. Emotional intelligence 42.5%

Administering Average reskilling needs

52.7% Share of workforce within this industry

All tasks DURATION OF RESKILLING 3 to 6 months 13.4% 53.2% Less than 1 month 26.9%

55.1%

Performing physical and manual work activities 6 to 12 months 19.8% 60.4%

67.7%

69.5% Over 1 year 22.9% Coordinating, developing, managing and advising 1 to 3 months

69.8%

The Future of Jobs 135 Industry Profile 1/2

14.8% Expected redeployment Average skills

39.5% 39.1%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 95% 1. Leadership and social influence Cloud computing 95% 89% 2. Complex problem-solving Text, image and voice processing 85% 79% 3. Analytical thinking and innovation Big data analytics 67% 65% 4. Active learning and learning strategies Internet of things and connected devices 56% 50% 5. Critical thinking and analysis E-commerce and digital trade 45% Artificial intelligence (e.g. machine learning, neural 6. Technology design and programming Augmented and virtual reality 7. Resilience, stress tolerance and flexibility drones, etc.) 8. Technology use, monitoring and control 9. Creativity, originality and initiative

10. Technology installation and maintenance

11. Systems analysis and evaluation

12. Reasoning, problem-solving and ideation

13. Persuasion and negotiation

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Information Security Analysts Risk Management Specialists 85.7% 1. Digital Transformation Specialists 2. Data Analysts and Scientists Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Strategic Advisors 4. Software and Applications Developers conferencing) 5. Project Managers 78.6% 6. Database and Network Professionals Accelerate automation of tasks 50% 8. Online Learning Managers Temporarily reassign workers to different tasks 42.9% 9. Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

1. Accounting, Bookkeeping and Payroll Clerks

2. Sales and Marketing Professionals

3. Material-Recording and Stock-Keeping Clerks

4. Business Services and Administration Managers

5. Lawyers

6. Human Resources Specialists

7. Compliance Officers

The Future of Jobs 136

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Inability to attract specialized talent 55% Expand its current workforce Skills gaps in the local labour market 50% Insufficient understanding of opportunities 50% 47.4% Lack of flexibility in hiring and firing 40% Modify the composition of the value chain Shortage of investment capital 40% Lack of interest among leadership 25% 36.8% Lack of flexibility of the regulatory framework 20% 20% Modify the locations where the organization operates

Augmentation of key job tasks by 2024 2. Critical thinking and analysis

Machine share Human share 3. Leadership and social influence

Information and data processing 6. Resilience, stress tolerance and flexibility

28.9% 7. Emotional intelligence

Looking for and receiving job-related information 8. Technology use, monitoring and control 54.1%

57.5%

Administering Average reskilling needs

57.6% Share of workforce within this industry

Performing physical and manual work activities DURATION OF RESKILLING 3 to 6 months 59.9% Less than 1 month 27.3%

Identifying and evaluating job-relevant information 6 to 12 months 60.5% 21.8% Reasoning and decision-making 10.1%

Communicating and interacting 1 to 3 months 24.9% 69.7%

73.7%

The Future of Jobs 137 Industry Profile 1/2

10.6% Expected redeployment Average skills

44.2% 48.2%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered Big data analytics 95% 1. Active learning and learning strategies Artificial intelligence (e.g. machine learning, neural 89% networks, NLP) 89% 2. Emotional intelligence Text, image and voice processing 88% Encryption and cyber security 84% 3. Creativity, originality and initiative Cloud computing 84% E-commerce and digital trade 78% 4. Leadership and social influence Distributed ledger technology (e.g. blockchain) 72% Augmented and virtual reality 67% 5. Resilience, stress tolerance and flexibility 3D and 4D printing and modelling 65%

8. Complex problem-solving

9. Troubleshooting and user experience

10. Persuasion and negotiation

11. Technology design and programming

12. Quality control and safety awareness

13. Critical thinking and analysis

14. Coordination and time management

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Data Analysts and Scientists 100% 1. Social Science Research Assistants 2. Internet of Things Specialists Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Information Security Analysts 4. Digital Marketing and Strategy Specialists conferencing) 5. Biologists and Geneticists 87.5% 6. Specialist Medical Practitioners Accelerate automation of tasks 8. Training and Development Specialists 56.2% 10.

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

31.2% REDUNDANT

3. Waiters and Bartenders

4. Business Services and Administration Managers

5. Human Resources Specialists

6. Electronics and Telecommunications Installers and Repairers

7. Assembly and Factory Workers

8. Administrative and Executive Secretaries

The Future of Jobs 138

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Lack of flexibility of the regulatory framework 47.4% Reduce its current workforce due to technological integration or automation Skills gaps in the local labour market 42.1% 63.2% Inability to attract specialized talent 42.1% Shortage of investment capital 36.8% Modify the composition of the value chain Lack of flexibility in hiring and firing 36.8% Skills gaps among organization’s leadership 31.6% 52.6% Lack of interest among leadership 10.5% Insufficient understanding of opportunities 5.3% Expand its current workforce due to technological integration or automation

1. Creativity, originality and initiative

Augmentation of key job tasks by 2024 2. Leadership and social influence

Machine share Human share 3. Service orientation

4. Reasoning, problem-solving and ideation

5. Analytical thinking and innovation

Information and data processing 6. Quality control and safety awareness

34.6% 7. Critical thinking and analysis

Looking for and receiving job-related information 8. Management of personnel 41.6% 9. Active learning and learning strategies

All tasks Average reskilling needs

48.5% Share of workforce within this industry

Performing complex and technical activities DURATION OF RESKILLING 3 to 6 months 21.5% 51.8% Less than 1 month

52.9%

57.9%

Reasoning and decision-making 6 to 12 months 25.2% 60.6%

Coordinating, developing, managing and advising 1 to 3 months

68.6%

The Future of Jobs 139 Industry Profile 1/2

Manufacturing Expected redeployment Average skills 13.2% of displacement 44.6% 43.6%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 92% 1. Active learning and learning strategies Internet of things and connected devices 84% 82% 2. Technology use, monitoring and control E-commerce and digital trade 81% 79% 3. Analytical thinking and innovation Big data analytics 72% Robots, non-humanoid (industrial automation, 71% 4. Leadership and social influence drones, etc.) 69% Encryption and cyber security 64% 5. Resilience, stress tolerance and flexibility Artificial intelligence (e.g. machine learning, neural 62% networks, NLP) 6. Complex problem-solving 7. Systems analysis and evaluation 8. Reasoning, problem-solving and ideation 9. Technology design and programming

10. Critical thinking and analysis

11. Service orientation

12. Quality control and safety awareness

13. Creativity, originality and initiative

14. Troubleshooting and user experience

15. Technology installation and maintenance

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING Data Analysts and Scientists Business Development Professionals 80% 1. Strategic Advisors 2. Software and Applications Developers Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Internet of Things Specialists 4. Big Data Specialists conferencing) 5. AI and Machine Learning Specialists 77.1% 6. Sales Representatives, Wholesale and Manufacturing, Technic… 7. Robotics Engineers Accelerate automation of tasks 54.3% 8. Process Automation Specialists Temporarily reduce workforce 40% 9. Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

3. Assembly and Factory Workers

4. Relationship Managers

5. Business Services and Administration Managers

6. Accounting, Bookkeeping and Payroll Clerks

7. Sales Representatives, Wholesale and Manufacturing, Technic…

8. Mechanics and Machinery Repairers

9. General and Operations Managers

10. Door-To-Door Sales Workers, News and Street Vendors, and R…

The Future of Jobs 140

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 63.6% Modify the composition of the value chain Inability to attract specialized talent 59.1% Skills gaps among organization’s leadership 54.5% 65.9% Insufficient understanding of opportunities Shortage of investment capital 38.6% Reduce its current workforce due to technological integration or automation Lack of flexibility of the regulatory framework 31.8% 50% Lack of flexibility in hiring and firing 31.8% Lack of interest among leadership 25% Expand its use of contractors doing task-specialized work Other 9.1% 6.8% 45.5%

40.9%

36.4%

2. Technology use, monitoring and control

Augmentation of key job tasks by 2024 3. Complex problem-solving

Machine share Human share 5. Critical thinking and analysis

Information and data processing 8. Technology installation and maintenance

40.1% 9. Active learning and learning strategies

Looking for and receiving job-related information 10. Creativity, originality and initiative

All tasks Average reskilling needs

51% Share of workforce within this industry

Performing physical and manual work activities DURATION OF RESKILLING 3 to 6 months 51.3% 19.4% Administering 23.8%

51.4%

Performing complex and technical activities 6 to 12 months 16.5% 53.9% Over 1 year 17.9%

62.1% 1 to 3 months

64.1%

66.5%

The Future of Jobs 141 Industry Profile 1/2

Mining and Metals

19.9% Expected redeployment Average skills of displacement workers workforce

49.5% 40.6%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered drones, etc.) 90% 1. Technology use, monitoring and control Internet of things and connected devices 90% 90% 2. Analytical thinking and innovation Big data analytics 87% 83% 3. Critical thinking and analysis Cloud computing 76% 76% 4. Complex problem-solving Encryption and cyber security 62% 57% 5. Systems analysis and evaluation Text, image and voice processing 57% Artificial intelligence (e.g. machine learning, neural 6. Reasoning, problem-solving and ideation E-commerce and digital trade 7. Troubleshooting and user experience

Power storage and generation 8. Leadership and social influence

Augmented and virtual reality 9. Creativity, originality and initiative

10. Active learning and learning strategies

11. Emotional intelligence

12. Resilience, stress tolerance and flexibility

13. Quality control and safety awareness

14. Instruction, mentoring and teaching

15. Technology design and programming

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Provide more opportunities to work remotely EMERGING AI and Machine Learning Specialists 94.7% 1. Process Automation Specialists Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Software and Applications Developers 4. Digital Transformation Specialists conferencing) 5. Remote Sensing Scientists and Technologists 78.9% 6. Management and Organisation Analysts 7. Internet of Things Specialists Temporarily reassign workers to different tasks 42.1% 8. Big Data Specialists Temporarily reduce workforce 42.1% 9.

2. Assembly and Factory Workers

3. Mining and Petroleum Extraction Workers

4. Material-Recording and Stock-Keeping Clerks

5. Locomotive Engine Drivers and Related Workers

6. Heavy Truck and Bus Drivers

7. Financial Analysts

8. Construction Laborers

The Future of Jobs 142

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 73.3% Modify the composition of the value chain Inability to attract specialized talent 56.7% Insufficient understanding of opportunities 50% 62.1% Lack of flexibility in hiring and firing 46.7% Reduce its current workforce due to technological integration or automation Lack of flexibility of the regulatory framework 36.7% 51.7% Shortage of investment capital 26.7% Lack of interest among leadership 23.3% Expand its use of contractors doing task-specialized work Other 20% 10% 51.7%

44.8%

27.6%

Augmentation of key job tasks by 2024 3. Technology use, monitoring and control

Machine share Human share 5. Critical thinking and analysis

6. Reasoning, problem-solving and ideation

7. Active learning and learning strategies

Information and data processing 8. Resilience, stress tolerance and flexibility

32.3% 9. Management of personnel

Performing physical and manual work activities 10. Creativity, originality and initiative 40.5%

Looking for and receiving job-related information Average reskilling needs 46.1% 46.3% 6 to 12 months Less than 1 month 19.5% Identifying and evaluating job-relevant information 17.5% 50.9%

All tasks 1 to 3 months 22.7% 51.3% 3 to 6 months Reasoning and decision-making Over 1 year 24.7%

65.4%

67.6%

73.2%

The Future of Jobs 143 Industry Profile 1/2

Oil and Gas Expected redeployment Average skills of displacement 48.1% 42.6%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 93% 1. Active learning and learning strategies Text, image and voice processing 87% 86% 2. Technology design and programming Cloud computing 86% 79% 3. Service orientation Big data analytics 79% Robots, non-humanoid (industrial automation, 71% 4. Leadership and social influence drones, etc.) 71% 3D and 4D printing and modelling 71% 5. Emotional intelligence Encryption and cyber security 6. Critical thinking and analysis

Augmented and virtual reality 7. Complex problem-solving Artificial intelligence (e.g. machine learning, neural networks, NLP) 8. Analytical thinking and innovation 9. Troubleshooting and user experience

10. Creativity, originality and initiative

11. Technology installation and maintenance

12. Reasoning, problem-solving and ideation

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Renewable Energy Engineers Sheet and Structural Metal Workers, Moulders and Welders conferencing) 1. Robotics Engineers 77.8% 2. Process Automation Specialists Provide more opportunities to work remotely 4. ICT Operations and User Support Technicians 66.7% 6. Big Data Specialists 7. AI and Machine Learning Specialists Accelerate the digitalization of upskilling/ reskilling (e.g. education technology 8. providers) 10.

33.3% REDUNDANT

2. Assembly and Factory Workers

3. Mechanics and Machinery Repairers

4. Material-Recording and Stock-Keeping Clerks

5. Mining and Petroleum Extraction Workers

6. Legal Secretaries

The Future of Jobs 144

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 50% Modify the composition of the value chain Shortage of investment capital 42.9% Lack of flexibility in hiring and firing 42.9% 71.4% Lack of flexibility of the regulatory framework Insufficient understanding of opportunities 35.7% Reduce its current workforce due to technological integration or automation Inability to attract specialized talent 35.7% 42.9% Skills gaps among organization’s leadership 35.7% Lack of interest among leadership 28.6% Expand its use of contractors doing task-specialized work Other 21.4% 7.1% 42.9%

1. Technology design and programming

2. Quality control and safety awareness

Augmentation of key job tasks by 2024 3. Complex problem-solving

Machine share Human share 5. Technology installation and maintenance

6. Analytical thinking and innovation

Information and data processing 8. Critical thinking and analysis

40.5% 9. Troubleshooting and user experience

Looking for and receiving job-related information 10. Resilience, stress tolerance and flexibility

Performing physical and manual work activities Average reskilling needs

54.3% Share of workforce within this industry

Administering DURATION OF RESKILLING

58.8% Less than 1 month 6 to 12 months 13.6% 19.9%

59.2%

64.8% 1 to 3 months Identifying and evaluating job-relevant information 3 to 6 months 66.8% Over 1 year 28.1%

73.5%

73.9%

80.2%

The Future of Jobs 145 Industry Profile 1/2

Professional Services

11.6% Expected redeployment Average skills

41.3% 48%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered Big data analytics 88% 1. Analytical thinking and innovation Text, image and voice processing 86% Encryption and cyber security 79% 2. Complex problem-solving Artificial intelligence (e.g. machine learning, neural 78% networks, NLP) 76% 3. Critical thinking and analysis Internet of things and connected devices 74% E-commerce and digital trade 70% 4. Creativity, originality and initiative Augmented and virtual reality 57% Distributed ledger technology (e.g. blockchain) 53% 5. Active learning and learning strategies Power storage and generation 45%

7. Emotional intelligence

8. Leadership and social influence

9. Persuasion and negotiation

10. Resilience, stress tolerance and flexibility

11. Technology design and programming

12. Technology use, monitoring and control

13. Quality control and safety awareness

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING Digital Marketing and Strategy Specialists conferencing) 1. Data Analysts and Scientists 92.9% 2. Business Development Professionals Provide more opportunities to work remotely 4. Business Services and Administration Managers 85.7% 6. Process Automation Specialists 7. Lawyers Accelerate automation of tasks 8. Financial Analysts 45.2% 10.

Accelerate the digitalization of upskilling/ reskilling (e.g. education technology

40.5% REDUNDANT

4. Relationship Managers

5. Legal Secretaries

6. Management and Organisation Analysts

7. General and Operations Managers

8. Electronics and Telecommunications Installers and Repairers

9. Business Services and Administration Managers

The Future of Jobs 146

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Shortage of investment capital 51% Expand its current workforce Skills gaps in the local labour market 41.2% Insufficient understanding of opportunities 39.2% 53.8% Lack of flexibility of the regulatory framework 35.3% Expand its use of contractors doing task-specialized work Inability to attract specialized talent 35.3% Lack of interest among leadership 35.3% 51.9% Lack of flexibility in hiring and firing 27.5% Other 17.6% Modify the composition of the value chain

42.3%

32.7%

1. Active learning and learning strategies

2. Creativity, originality and initiative

Augmentation of key job tasks by 2024 3. Analytical thinking and innovation

Machine share Human share 5. Emotional intelligence

7. Reasoning, problem-solving and ideation

Looking for and receiving job-related information 8. Management of personnel 37.3% 9. Leadership and social influence

Information and data processing 10. Persuasion and negotiation

37.7%

Administering Average reskilling needs

44.4% Share of workforce within this industry

Identifying and evaluating job-relevant information DURATION OF RESKILLING 3 to 6 months 45% 17.1% Performing physical and manual work activities 29% 48.3%

51.8%

All tasks 6 to 12 months 57.6% Over 1 year 17.8%

Communicating and interacting 1 to 3 months 20.5%

The Future of Jobs 147 Industry Profile 1/2

14.7% Expected redeployment Average skills success rate of displaced instability among

workers workforce

49.1% 38.2%

Technology adoption in industry Emerging skills

Share of companies surveyed Skills identified as being in high demand within their organization, ordered 94% 1. Active learning and learning strategies Cloud computing 94% Artificial intelligence (e.g. machine learning, neural 88% 2. Complex problem-solving networks, NLP) 87% E-commerce and digital trade 76% 3. Analytical thinking and innovation Internet of things and connected devices 69% 4. Technology use, monitoring and control 65% Encryption and cyber security 62% 5. Technology design and programming Robots, non-humanoid (industrial automation, 60% drones, etc.) 6. Systems analysis and evaluation 8. Quality control and safety awareness 9. Leadership and social influence

10. Emotional intelligence

11. Attention to detail, trustworthiness

12. Management of personnel

13. Resilience, stress tolerance and flexibility

14. Reasoning, problem-solving and ideation

15. Critical thinking and analysis

Impact of COVID-19 on companies’ strategy Emerging and redundant job roles

Share of companies surveyed looking to adopt this strategy as a result of Role identified as being in high demand or increasingly redundant within COVID-19 their organization, ordered by frequency

Accelerate the digitalization of work processes (e.g. use of digital tools, video EMERGING AI and Machine Learning Specialists conferencing) 1. Data Analysts and Scientists 92.9% 2. Architects and Surveyors Provide more opportunities to work remotely 4. Supply Chain and Logistics Specialists 5. Environmental Protection Professionals 64.3% 6. Organizational Development Specialists 7. Product Managers Accelerate automation of tasks 50% 8. Ship and Boat Captains Accelerate ongoing organizational transformations (e.g. restructuring) 35.7% 9.

3. Architects and Surveyors

4. Sales Representatives, Wholesale and Manufacturing, Technic…

5. Postal Service Clerks

6. Business Services and Administration Managers

7. Accountants and Auditors

8. Door-To-Door Sales Workers, News and Street Vendors, and R…

9. Material-Recording and Stock-Keeping Clerks

The Future of Jobs 148

Barriers to adoption of new technologies Expected impact on workforce

Share of companies surveyed Share of companies surveyed

Skills gaps in the local labour market 64.7% Modify the locations where the organization operates Inability to attract specialized talent 58.8% Lack of flexibility of the regulatory framework 58.8% Shortage of investment capital 35.3% Skills gaps among organization’s leadership 29.4% Modify the composition of the value chain Lack of flexibility in hiring and firing 23.5% Insufficient understanding of opportunities 23.5% 58.8% Other 23.5% Lack of interest among leadership 5.9% Reduce its current workforce due to technological integration or automation 5.9% 47.1%

2. Quality control and safety awareness

Augmentation of key job tasks by 2024 3. Service orientation

Machine share Human share 5. Attention to detail, trustworthiness

Information and data processing 8. Complex problem-solving

32.2% 9. Systems analysis and evaluation

Administering 10. Management of personnel

43.2%

Performing complex and technical activities Average reskilling needs 43.7% Looking for and receiving job-related information 6 to 12 months 43.8% DURATION OF RESKILLING 16.1%

All tasks Less than 1 month 26.6%

50.2%

51.9%

Identifying and evaluating job-relevant information Over 1 year 52.5% 26.8%

Performing physical and manual work activities 1 to 3 months 3 to 6 months 14.4% 16% 55.2%

56.1%

59.4%

The Future of Jobs 149

Appendix A: Report Methodology

The Future of Jobs Report is based on the results The survey consists of quantitative as well as of the 2020 edition of the Future of Jobs survey, qualitative questions seeking to capture the a unique source of information that gathers the strategic knowledge, projections and planning of the insights from the largest companies worldwide on respondents. The study is designed to reveal the the changing nature of work. world’s leading employers’ estimates on how the labour force is transforming, their projections on how The survey asks senior executives to share the planning quickly these shifts will happen, and their efforts in for their companies’ workforce transformation with addressing these changes. a time horizon up to 2024. It aims to provide timely and unique insights on the trends affecting the labour In total the survey comprises 49 questions and was market, the rate of technological adoption among made available in four languages: English, Spanish, firms, the shifting job landscape and associated Japanese and Russian. changes to skills needs as well as business planning for appropriate upskilling and reskilling. Survey distribution

The 2020 survey dissemination took place during The survey was distributed via an online platform the first half of 2020. The survey provides a much- through three dissemination networks. The primary needed compass for business, governments, civil distribution route was to the World Economic Forum society Organizations as well as the public at large partners and constituents in collaboration with on the short-and medium-term transformations to the World Economic Forum Regional and Industry the labour market. teams. The survey was further disseminated through a network of Partner Institutes—local partner Survey design organizations that administered the survey in their respective economies. Further dissemination through The survey builds on the methodology from the partner organizations enabled the strengthening of 2016 and 2018 survey editions. Following survey regional representation by extending the sample to best practice and in consultation with the World local companies. As a third dissemination channel, Economic Forum Global Future Council on the new the New Economy and Society team shared the Education and Work Agenda, several questions were survey with the collaborators from the countries in refined and new questions were added. The three which the Closing the Skills and Innovation Gap core concepts that are key to the construction of Accelerators are present (South Africa, UAE, Bahrain, the Future of Jobs Survey remain unchanged in this India, Pakistan). The Accelerator project brings about edition. That is, the nature of work is broken down tangible change by building a national public-private into three interrelated subcategories: job roles, tasks collaboration platform to increase employability of and skills. Task are defined as the actions necessary the current workforce and increase work-readiness to turn a set of inputs into valuable outputs. A and critical skills among the future workforce. collection of tasks forms the content of job roles, while skills are capabilities needed to be able to For the full overview of the survey partners, please perform the tasks well. refer to the Survey Partners and Acknowledgements sections at the end of the report. The survey is structured into four parts. The first part includes questions on the expected transformations The network of survey partners responsible for the to the workforce, including the major trends that are dissemination followed clear sampling guidelines, affecting the labour market and the technologies which specified the level of the respondent, the that are being adopted. The second part focuses on target companies and the sample composition. As jobs, skills and tasks and how these are expected to the questions in the survey require deep insight into evolve over a four-year period. The third part collects an organization’s current strategy as well as talent- information on training programmes and employee related aspects of operationalizing this strategy, reskilling needs and efforts. Finally, to understand the target respondents were senior executives in the shorter-term impacts of the global pandemic, charge of human resources, strategy and innovation a fourth section was added on the effects of the departments. COVID-19 on the workforce.

The Future of Jobs 150 The target companies were specified as the largest Financial Services; Consumer; Mining and Metals; multinational and national companies, significant in Education; Government and Public Sector; Health terms of revenue or employee size. The threshold and Healthcare; Automotive; Agriculture, Food and was set at companies with 100 employees or more Beverage; Transportation and Storage; Energy as questions concerning technology absorption and Utilities and Technologies; Oil and Gas and Advanced its consequential impact on employee planning are Manufacturing. The countries represented are the most relevant for larger companies with a significant United States, the United Kingdom, the United Arab share of employment. Emirates, China, Germany, India, Saudi Arabia, Poland, the Russian Federation, Japan, France, Thailand, Finally, the guidelines specified the industry Australia, Brazil, Canada, the Netherlands, Singapore, representation, which should reflect the structure of Spain, Pakistan, Mexico, Switzerland, Argentina, the economy by industry in proportion to the share Indonesia, Italy, South Africa and Malaysia. of GDP (see Table A1), while also ensuring good geographical coverage. In total, the report’s data set contains 291 unique responses by global companies, collectively The data was collected over a nine-month period representing more than 7.7 million employees from January to September 2020. In late February, worldwide. Out of scope of this report are responses the survey was updated to reflect the new global from small companies with fewer than 100 employees context. A specific section with questions relating as well as responses from the informal sector. directly to the COVID-19 health crisis and its implications for the workforce was included. The report aims to provide guidance and stimulating discussion. However, the results should be treated By 23 March, when most economies were with caution when looking to generalize its findings in experiencing the effects of the pandemic and had a manner that could be considered representative of started to implement measures to slow the spread all trends across an entire industry or country. of the virus, only 24% of the Future of Jobs Surveys had been completed. By mid-April, by which time Classification framework most economies were in full or partial lockdown for jobs and skills (see Figure 2), 36% of companies had completed the survey. Therefore, most of the responses were Following the 2016 and 2018 taxonomy, this year’s collected during the COVID-19 pandemic while report employed the Occupational Information at least partial lockdown measures were in place, Network (ONET) framework for its categories and therefore captured some of the impact of of analysis for jobs, skills and tasks. ONET was COVID-19 on the organization’s workforce planning. developed by the US Department of Labor in Nevertheless, results should be interpreted with collaboration with its Bureau of Labor Statistics’ caution as companies might not have been fully Standard Classification of Occupations (SOC) aware of the implications of their health crisis on their and remains the most extensive and respected workforce during the early phases of the pandemic. classification of its kind. In its unabridged form, the ONET-SOC taxonomy includes detailed information Representativeness on 974 individual occupations in the United States, grouped into approximately 20 broader job families, With the purpose to represent the planning and which are regularly revised and updated for new and projections of global business, 65% of the final emerging occupations to keep up with the changing sample is composed of multinational companies, occupational landscape. while 35% is from larger local companies, significant in terms of revenue or size. The final sample includes The Generalized Work Activities segment of the responses from Chief Executive Officers (12%), top ONET methodology was used to form the list executives (59%), middle-level executives (25%), of tasks used in the survey. In addition, for the and, in exceptional cases, other respondents such classification of skills, the report team employed an as consultants (3%). abridged version of the “Worker Characteristics” and Worker Requirement classifications; in particular, Over half of the final sample (52%) is composed bundles 1.A., 1.C., 2.A., and 2.B. Additional details of respondents from Human Resources about the composition of the skills list used in this departments, responsible for the planning of report can be found in Table A2. the company’s employees. Other responses represent the views of executives from the The list of roles used in the report is enhanced with organization’s strategic departments, including roles which were consistently added to previous Finance, Operation and Strategy. editions of the report. In addition, the skills taxonomy used is an adapted and enhanced version of the After applying the representative criteria, the final O*NET taxonomy, enriched by feedback and insights sample comprised 15 industry clusters and 26 from New Metrics collaborators. For details please countries which collectively represent 80% of see Tables A2 and A3. the world GDP. The industries represented are: Professional Services; Manufacturing; Digital Communications and Information Technology;

The Future of Jobs 151 TABLE A1 Taxonomy of industry categories

Industry cluster Industry Alternative names Agriculture, Food and Beverage Agriculture, Forestry, Fishing and Hunting Agriculture, Food and Beverage Food and Beverages Retail, Consumer Goods and Lifestyle Automotive Retail, Consumer Goods and Lifestyle Automotive Accomodation and Food Services Retail, Consumer Goods and Lifestyle Consumer Restaurants Consumer Retail / Retail Trade Utilities Consumer Telecommunications Banking Digital Communications and Information Technology Information Technology Financial Services and Insurance / Finance and Digital Communications and Information Technology Electronics Insurance Digital Communications and Information Technology Education Management Financial Services and Insurance / Finance and Education Education Services Insurance Education Higher Education Financial Services and Insurance / Finance and Education Energy Utilities Insurance Energy Utilities & Technologies Energy Technology Public Administration / Government Administration Energy Utilities & Technologies Banking and Capital Markets Non-Profit Organization Management Financial Services Health Care and Social Assistance / Hospital & Insurance and Asset Management Health care Financial Services Information Technology & Services Institutional Investors Financial Services Mining, Quarrying, and Oil and Gas Extraction Private Investors Financial Services Mining, Quarrying, and Oil and Gas Extraction Government and Public Sector Mining, Quarrying, and Oil and Gas Extraction Government and Public Sector Non-Profits - - Information Technology Construction Infra, Urban Dev. & Real Estate Real Estate, Rental and Leasing Infra, Urban Dev. & Real Estate Advanced Manufacturing Aerospace Manufacturing Chemical and Advanced Materials Manufacturing Arts, Entertainment and Recreation Manufacturing Marketing and Advertising Media, Entertainment & Culture Information and Media Media, Entertainment & Culture - Media, Entertainment & Culture Mining and Metals Administrative and Support and Waste Management and Military Remediation Services Mining and Metals Oil and Gas Oil Field Services and Equipment Office and Facilities Support Services Other Services Administrative and Support Services Oil and Gas Management of Companies and Enterprises Oil and Gas Professional, Scientific and Technical Services Other Services Transportation and Warehousing Professional Services Wholesale Trade Professional Services Aviation, Travel and Tourism Professional Services Supply Chain and Transportation

The Future of Jobs 152 TABLE A2 Classification of skills used, based on O*NET content model 1/2

Competency bundle Competency Description Active learning and learning strategies Active learning Understanding the implications of new information for both current and future Analytical thinking and innovation Learning strategies problem-solving and decision-making. Attention to detail, trustworthiness Selecting and using training/instructional methods and procedures appropriate for Analytical thinking the situation when learning or teaching new things. Complex problem-solving Job requires analyzing information and using logic to address work-related issues Coordination and time management Innovation and problems. Attention to detail Job requires creativity and alternative thinking to develop new ideas for and Creativity, originality and initiative Dependability answers to work-related problems. Critical thinking and analysis Integrity Job requires being careful about detail and thorough in completing work tasks. Complex problem-solving Emotional intelligence Time management Job requires being reliable, responsible and dependable, and fulfilling obligations. Coordination Instruction, mentoring and teaching Initiative Job requires being honest and ethical. Leadership and social influence Critical thinking Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions. Management of financial, material Monitoring Managing one’s own time and the time of others. resources Concern for others Adjusting actions in relation to others’ actions. Management of personnel Manual dexterity, endurance and Cooperation Job requires a willingness to take on responsibilities and challenges. Using logic and reasoning to identify the strengths and weaknesses of alternative precision Social orientation solutions, conclusions or approaches to problems. Social perceptiveness Monitoring/assessing performance of yourself, other individuals, or organizations Memory, verbal, auditory and spatial Instructing to make improvements or take corrective action. abilities Leadership Job requires being sensitive to others’ needs and feelings and being understanding Management of financial resources and helpful on the job. Persuasion and negotiation Job requires being pleasant with others on the job and displaying a good-natured, Quality control and safety awareness Management of material resources cooperative attitude. Reading, writing, math and active listening Job requires preferring to work with others rather than alone, and being personally Management of personnel resources connected with others on the job. Being aware of others’ reactions and understanding why they react as they do. Endurance Flexibility, balance and coordination Teaching others how to do something. Physical strength abilities Control movement abilities Job requires a willingness to lead, take charge and offer opinions and direction. Fine manipulative abilities Determining how money will be spent to get the work done, and accounting for Reaction time and speed abilities these expenditures. Attentiveness Obtaining and seeing to the appropriate use of equipment, facilities and materials Memory needed to do certain work. Perceptual abilities Motivating, developing and directing people as they work, identifying the best Spatial abilities people for the job. Verbal abilities The ability to exert oneself physically over long periods without getting out of Negotiation breath. Persuasion Abilities related to the control of gross body movements. Quality control analysis Abilities related to the capacity to exert force. Active listening Abilities related to the control and manipulation of objects in time and space

Abilities related to the manipulation of objects.

Abilities related to speed of manipulation of objects.

Abilities related to application of attention.

Abilities related to the recall of available information.

Abilities related to the acquisition and organization of visual information.

Abilities related to the manipulation and organization of spatial information Abilities that influence the acquisition and application of verbal information in problem-solving. Bringing others together and trying to reconcile differences.

Persuading others to change their minds or behaviour. Conducting tests and inspections of products, services or processes to evaluate quality or performance. Giving full attention to what other people are saying, taking time to understand the points being made, asking questions as appropriate, and not interrupting at inappropriate times.

The Future of Jobs 153 TABLE A2 Classification of skills used, based on O*NET content model 2/2

Competency bundle Competency Description Mathematics Reasoning, problem-solving and ideation Reading comprehension Using mathematics to solve problems. Resilience, stress tolerance and flexibility Science Speaking Understanding written sentences and paragraphs in work related documents. Service orientation Writing Systems analysis and evaluation Idea generation and reasoning abilities Using scientific rules and methods to solve problems.

Technology design and programming Quantitative abilities Talking to others to convey information effectively Technology installation and maintenance Technology use, monitoring and control Adaptability/flexibility Communicating effectively in writing as appropriate for the needs of the audience. Abilities that influence the application and manipulation of information in problem- Troubleshooting and user experience Self control solving. Visual, auditory and speech abilities Abilities that influence the solution of problems involving mathematical Stress tolerance relationships. Service orientation Job requires being open to change (positive or negative) and to considerable Judgment and decision-making variety in the workplace. Job requires maintaining composure, keeping emotions in check, controlling anger Systems analysis and avoiding aggressive behavior, even in very difficult situations. Job requires accepting criticism and dealing calmly and effectively with high stress Systems evaluation situations. Programming Actively looking for ways to help people. Technology design Considering the relative costs and benefits of potential actions to choose the most Equipment maintenance appropriate one. Installation Determining how a system should work and how changes in conditions, operations Repairing and the environment will affect outcomes. Equipment selection Identifying measures or indicators of system performance and the actions needed Operation and control to improve or correct performance, relative to the goals of the system. Operation monitoring Writing computer programmes for various purposes. Operations analysis Generating or adapting equipment and technology to serve user needs. Troubleshooting Performing routine maintenance on equipment and determining when and what Auditory and speech abilities kind of maintenance is needed. Visual abilities Installing equipment, machines, wiring or programmes to meet specifications. Repairing machines or systems using the needed tools. Determining the kind of tools and equipment needed to do a job. Controlling operations of equipment or systems. Watching gauges, dials or other indicators to make sure a machine is working properly. Analyzing needs and product requirements to create a design. Determining causes of operating errors and deciding what to do about them. Abilities related to auditory and oral input. Abilities related to visual sensory input.

The Future of Jobs 154 TABLE A3 Classification of skills used, skills taxonomy 1/2

Competency type Taxonomy cluster Taxonomy cluster Taxonomy cluster Taxonomy cluster level 3 definition level 1 level 2 level 3 Skills and knowledge: Skills Business skills Management and Coordination and time Capacity to manage one’s time and planning in tandem with are the capabilities needed to communication of management others. complete a task, and therefore Innovation and activities Management of financial, Developed capacities for gathering resources to achieve a job. creativity material resources tasks including how money will be spent to get the work done, Knowledge is the body of facts, Problem-solving obtaining equipment, facilities, and materials and accounting for principles and theories that are Digital Sales, communication and expenditures. related to a field of work or study Technology use and marketing of products and Developed capacities to identify and shape effective value proposi- and can be further split into development services tions for products and services, as well as to sell products on that dependent knowledge (practical Quality control and safety basis. and procedural) and context- awareness Conducting tests and inspections of products, services or processes independent or theoretical Analyticial thinking and to evaluate quality and level of performance. knowledge. originality3 Capacity to analyze information and use logic to address issues and problems, apply alternative thinking to develop new, original ideas Analyticial thinking and and answers. originality3 Capacity to solve novel, ill-defined problems in complex, real-world Complex problem-solving settings. Abilities that influence the acquisition and application of knowledge Systems analysis and in problem-solving. evaluation Capacities used to understand, monitor and improve socio-technical Critical thinking and analysis systems. Using logic and reasoning to identify the strengths and weaknesses Creating and maintaining of alternative solutions, conclusions or approaches to problems as technology5 well as assessing performance of yourself, other individuals or orga- nizations to make improvements or take corrective action. Capacity to use programming to design machines or technological systems which fit user needs. In addition, understanding how others use tools, determine the cause of operating errors and how to fix them.

Using and operating Skills include: technology6 - Artificial Intelligence

• Computer Hardware & Networking Systems

Industry-specialized - Cybersecurity and Application Security

• Data Science and Analysis
• Human Computer Interaction
• Scrum/Agile Product Development
• Software & Programming
• Technical Support and Maintenance
• Web Development

Capacity to select the right tools needed to perform tasks, use those tools well and set up and operate technology. Skills include:

• Accounting and Finance Software
• Construction Management Software
• Clininal Information Systems
• Digital Design
• Digital Literacy
• Digital Marketing
• Geographic Information Systems
• Human Resourse Management Systems
• Productivity Software
• Machining & Manufacturing Technologies
• Scientific Computing

Skills specific to certain fields or professions: Documentation in Cloud Computing, Video and Editing in Marketing, Sales and Content or Radiation Oncology (in the Care Economy professional cluster). The cluster excludes skills related to the operation and design of digital technologies.

The Future of Jobs 155 TABLE A3 Classification of skills used, skills taxonomy 2/2

Competency type Taxonomy cluster Taxonomy cluster Taxonomy cluster Taxonomy cluster level 3 definition level 1 level 2 level 3 Working with people Management of personnel Motivating, developing and directing people as they work, identifying Attitudes: Consistent behaviours, Interpersonal the best people for the job. emotional intelligence traits and Self-management Persuasion and negotiation Persuading others to change their minds or behaviour as well as beliefs that individuals exhibit that bringing them together and trying to reconcile differences. influence their approach to a variety Service orientation Actively looking for ways to help others as well as to make them feel of things such as ideas, persons and attended to and welcome. situations. Attitudes are learned and Emotional intelligence Developed capacities used to work with people to achieve goals and often a big part of the driving force in particular being pleasant, cooperative, sensitive to others, easy to of learning and the approach to Leadership and social get along with and enjoying work with people. doing tasks. influence Having an impact on others in the organization, and displaying Learning strategies, instruc- energy and leadership. tion, mentoring and teaching4 Capacities for teaching others how to do something, including selecting and using training/instructional methods and procedures Initative2 appropriate for the situation when learning or teaching new things. Willingness to take on responsibilities and challenges.

Abilites: The range of physical, Physical abilities Social justice Active learning1 Understanding the implications of new information for both current psychomotor, cognitive and sensory Physical abilities and future problem-solving and decision-making. abilities that are required to perform Attention to detail, trustwor- Dependability, commitment to doing the job correctly and carefully, a job role. Core literacies thiness being trustworthy, accountable and paying attentive to details. Resilience, stress tolerance Maturity, poise, flexibility and restraint to cope with pressure, stress, Cognitive: Core literacies and flexibility criticism, setbacks, personal and work-related problems. Commonly cover conceptual Awareness of the wider world, of history and of social justice issues thinking and the ability to process Manual dexterity, endurance that result from historical inequalities. Playing an active role in the thoughts and perform various mental and precision global and local community and the appliation of civic values. activities, and are most closely Memory, verbal, auditory and Abilities related to the capacity to manipulate and control objects, associated with learning, reasoning spatial abilities strength, endurance, flexibility, balance and coordination. and problem-solving. Visual, auditory and speech Abilities that influence the acquisition and application of knowledge abilities in problem-solving. Reading, writing, math, active Abilities that influence visual, auditory and speech perception. listening Core literacies needed to work with and acquire more specific skills in a variety of different domains.

Source Note 1 listed as “Active learning and learning strategies” throughout the report; 2 listed as “Creativity, originality and initiative” throughout the report; 3 listed as “Analytical thinking and innovation” throughout the report; 4 listed as “Instruction, mentoring and teaching” throughout the report; 5 listed as “Technology design and programming” throughout the report”; 6 listed as “Technology use, monitoring and control” throughout the report.

The Future of Jobs 156 Contributors

World Economic Forum Platform for Shaping the Future of the New Economy and Society

Project team

Saadia Zahidi Member of Managing Board

Vesselina Ratcheva Insight Lead, Benchmarking Practice

Guillaume Hingel Insight Lead, Benchmarking Practice

Sophie Brown Project Specialist

We are extremely grateful to our colleagues on the Platform team for their collaboration, help and efforts, and in particular to Ida Jeng Christensen, Eoin Ó Cathasaigh, Genesis Elhussein, Till Leopold and SungAh Lee. A special thank you to Michael Fisher for his excellent copyediting work and to Accurat for their outstanding graphic designing and layout of the report.

Collaborations

The Platform for the New Economy and Society aims to empower decision-making among leaders in business and policy by providing fresh, actionable insight through collaboration with leading experts and data-holding companies as part of its New Metrics Co-Lab. We would like to thank the following contributors for their collaboration and support to this report:

Automatic Data Processing (ADP) Matthew Levin, Chief Strategy Officer, ADP LLC Ahu Yildirmaz, Co-Head, ADP Research Institute Renzhong Meng, Director, ADP Research Institute

Coursera Emily Glassberg Sands, Head of Data Science Vinod Bakthavachalam, Senior Data Scientist Eric Karsten, Data Scientist

FutureFit AI Hamoon Ekhtiari, CEO Terralynn Forsyth, Head of Product

Linkedin Rachel Bowley, Senior Data Scientist, Economic Graph Murat Erer, Senior Insights Analyst Mariano Mamertino, Senior Economist, Economic Graph Team Kristin Keveloh, Manager, Economic Graph Team Sein O Muineachain, Manager, Economic Graph Research and Insights (EMEA)

The Future of Jobs 157

New Economy and Society Partners

The World Economic Forum would like to thank the Partners of the Platform for Shaping the New Economy and Society for their guidance and support to this report.

Platform Partners

AARP EY Open Society Institute Accenture FutureFit AI PAO Severstal Adecco Group AG Google Inc. PayPal AIG HCL Technologies PJSC PhosAgro Alghanim Industries Heidrick & Struggles Pladis Foods Limited AlixPartners Henry Schein Inc. PricewaterhouseCoopers Amazon Web Services Hewlett Packard Enterprise International Limited Aroundtown SA HP Inc Prince Mohammed Bin Salman bin Automatic Data Processing Inc. HSBC Abdulaziz (MiSK) Foundation (ADP) Hubert Burda Media Procter & Gamble Bahrain Economic Development IBM Corporation Publicis Groupe Board Indus Group QI Group Bank of America Infosys Ltd RBC Financial Group Bank of Montreal Ingka Group (IKEA) Recruit Holdings Co. Ltd Barclays Invesco Ltd Reliance Industries Limited BC Energy Investments Corp. Islamic Development Bank RMZ Corp. Bill & Melinda Gates Foundation JLL Royal DSM NV Bloomberg LP Johnson & Johnson Salesforce, Sàrl Boston Consulting Group Kearney Inc. Sanofi Centene Corporation KIRKBI A/S/The LEGO Foundation SAP SE Charoen Pokphand Group LinkedIn Corporation Saudi Aramco Company Limited (CP Group) LRN Corporation Sea Limited Cisco Systems Inc. ManpowerGroup Sempra Energy Clayton, Dubilier & Rice LLC Marsh & McLennan Companies/ Standard Chartered Bank CNH Industrial N.V. Mercer Stanley Black & Decker Inc. Coursera Inc. McKinsey and Company Teck Resources Limited Crescent Enterprises Merck KGaA Trip.com Group Ltd Dassault Systèmes SE Microsoft Corp. Uber Technologies Dawood Hercules Corporation Natixis Udacity Dell Technologies NBC Universal Unilever Deloitte Nestlé Verizon Communications Dentsu Inc. NMC Healthcare Visa Inc. Deutsche Bank AG Nokia Corporation VMware Inc. Deutsche Post DHL Group Novartis AG Willis Towers Watson Dogan irketler Grubu Holding A.S Novolipetsk Steel (NLMK) Wipro DP World Limited NYSE Group Inc. Workday Inc. Eurasian Resources Group Sàrl Oando Plc WorldQuant LLC European Investment Bank (EIB) Omnicom Group Inc. Zurich Insurance Group

In addition, to our partners, the Platform for Shaping the Future of the New Economy and Society would like to thank the members of the Stewardship Board for their strategic guidance.

Platform Stewardship Board Members Adam Grant, Saul P. Steinberg Professor of Management and Psychology, The Wharton School, A. Michael Spence, William R. Berkley Professor University of Pennsylvania in Economics and Business, NYU Stern School of Business Ahmad bin Abdullah Humaid Belhoul Al Falasi, Minister of State for Entrepreneurship and SMEs, Achim Steiner, Administrator, United Nations United Arab Emirates Government Development Programme (UNDP) The Future of Jobs 158 Alain Dehaze, Chief Executive Officer, Adecco Group Laura Liswood, Secretary-General, Council of AG Women World Leaders

Alicia Bárcena Ibarra, Executive Secretary, United Lynda Gratton, Professor of Management Practice, Nations Economic Commission for Latin America London Business School and the Caribbean (ECLAC) Magdalena Andersson, Minister of Finance, Ministry Allen Blue, Co-Founder and Vice-President, of Finance of Sweden Products, LinkedIn Corporation Mariana Mazzucato, Professor of Economics of Andrew McAfee, Co-Director and Co-Founder, MIT Innovation and Public Value; Founder and Director, Initiative on the Digital Economy; Principal Research Institute for Innovation and Public Purpose, Scientist, Massachusetts Institute of Technology University College London (UCL) (MIT) Martine Ferland, Chief Executive Officer, Mercer Asheesh Advani, President and Chief Executive Limited Officer, JA Worldwide Minouche Shafik, Director, London School of Badr Jafar, Chief Executive Officer, Crescent Economics and Political Science Enterprises Peter Hummelgaard, Minister for Employment, Brian Gallagher, President and Chief Executive Ministry of Employment of Denmark Officer, United Way Worldwide Peter T. Grauer, Chairman, Bloomberg LP Bruno Le Maire, Minister of Economy and Finance, Ministry of the Economy, Finance and the Recovery Phumzile Mlambo-Ngcuka, Undersecretary-General of France and Executive Director, United Nations Entity for Gender Equality and the Empowerment of Women Erik Brynjolfsson, Schussel Family Professor; (UN WOMEN) Director, MIT Initiative on the Digital Economy, MIT - Sloan School of Management Rania Al-Mashat, Minister of International Cooperation, Ministry of International Cooperation of Frank Appel, Chief Executive Officer, Deutsche Post Egypt DHL Group Ricardo Hausmann, Founder and Director, Growth Guy Ryder, Director-General, International Labour Lab, Harvard University Organization (ILO) Rich Lesser, Global Chief Executive Officer, Boston Henrietta H. Fore, Executive Director, United Nations Consulting Group Children’s Fund (UNICEF) Robert E. Moritz, Global Chairman, PwC Jo Ann Jenkins, Chief Executive Officer, AARP Salil S. Parekh, Chief Executive Officer and Managing John Goodwin, Chief Executive Officer, The LEGO Director, Infosys Limited Foundation Sharan Burrow, General Secretary, International Jonas Prising, Chairman and Chief Executive Officer, Trade Union Confederation (ITUC) ManpowerGroup Sharon Thorne, Global Chair, Deloitte Josephine Teo, Minister for Manpower and Second Minister for Home Affairs, Ministry of Manpower of Stanley M. Bergman, Chairman of the Board and Singapore Chief Executive Officer, Henry Schein Inc.

Khalid Al-Falih, Minister of Investment, Ministry of Tariq Al Gurg, Chief Executive Officer, Dubai Cares Investment of Saudi Arabia Xavier Sala-i-Martin, Professor, Department of Laura D’Andrea Tyson, Distinguished Professor of Economics, Columbia University the Graduate School, Haas School of Business, University of California, Berkeley

To learn more about the Platform for Shaping the Future of the New Economy and Society, please visit: https://www.weforum.org/platforms/shaping-the-future- of-the-new-economy-and-society To get involved, please contact cnes@weforum.org

The Future of Jobs 159 Survey Partners

The Future of Jobs Report 2020 is the result of extensive collaboration between the World Economic Forum and regional survey partners. We would like to recognize the following organizations for their contribution to the World Economic Forum’s Future of Jobs Survey and this report.

Argentina Russian Federation IAE Business School—Universidad Austral Eurasia Competitiveness Institute (ECI)

Bahrain Switzerland Bahrain Economic Development Board University of St. Gallen, Competence Centre for Diversity and Inclusion (CCDI-HSG) LeadCap Knowledge Solutions Pvt. Ltd (LeadCap South Africa Ventures) Business Leadership South Africa National Skill Development Corporation (NSDC) Business Unity South Africa Trade & Industrial Policy Strategies (TIPS) KADIN Indonesia Thailand Chulalongkorn Business School, Chulalongkorn Japan University Waseda University Thailand Management Association (TMA)

Mexico United Arab Emirates Mexican Institute for Competitiveness (IMCO) National Program for Advanced Skills

Netherlands United Kingdom Amsterdam Centre for Business Innovation, Confederation of British Industry (CBI) Amsterdam Business School, University of Amsterdam

Pakistan Mishal Pakistan Punjab Skills Development Fund

The World Economic Forum would like to thank Global Future Council on the New Education and Work Agenda for their thought leadership and strategic guidance on the Education 4.0 framework and the Schools of the Future campaign.

Global Future Council on the New Education and Work Agenda

Suzanne Fortier, Principal and Vice-Chancellor, McGill University, Canada (Council Co-Chair)

Sarah Kirby, Group Head, Organization Design and Human Resource Strategy, Zurich Insurance Group, Switzerland (Council Co-Chair)

Jeremias Adams-Prassl, Professor of Law, University of Oxford, UK

Abdullah Al Karam, Chairman and Director-General, Knowledge and Human Development Authority, United Arab Emirates

Erik Brynjolfsson, Schussel Family Professor; Director, MIT Initiative on the Digital Economy, MIT - Sloan School of Management, USA

Greetje Corporaal, Postdoctoral Research Fellow, Oxford Internet Institute, University of Oxford, UK (Council Fellow)

Xiao Dun, Founder, 17Zyuoye, China

The Future of Jobs 160 Susan Gianinno, Senior Adviser, Publicis Groupe, France Emily Glassberg Sands, Head, Data Science, Coursera Inc., USA Mark Graham, Professor of Internet Geography, Oxford Internet Institute, University of Oxford, UK Lynda Gratton, Professor of Management Practice, London Business School, UK Anne-Sophie Grouchka, Member of the Executive Board, France; Chief Customer Officer, Allianz SE, France Harsha Jalihal, Vice-President, Human Resources, USA, Unilever, USA Jawad Khan, Chief Executive Officer, Punjab Skills Development Fund, Pakistan Annie Koh, V3 Group Professor of Family Entrepreneurship; Professor of Finance, Practice; Vice-President, Office of Business Development, Singapore Management University, Singapore Frida Polli, Co-Founder and Chief Executive Officer, Pymetrics Inc., USA Dan Restuccia, Chief Analytics and Product Officer, Burning Glass Technologies, USA Lee Sangheon, Director, Employment Policy Department, International Labour Organization, Switzerland Bettina Schaller, Head, Group Public Affairs, The Adecco Group, Switzerland Andria Zafirakou, Teacher, Arts and Textile, Alperton Community School, UK Ray Tong Zhilei, Chairman and Chief Executive Officer, ChineseAll Digital Publishing Group Co. Ltd, China

The Future of Jobs 161

The Future of Jobs 162 The World Economic Forum is the International Organization for Public-Private Cooperation and engages the foremost political, business and other leaders of society to shape global, regional and industry agendas.

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