Full report
Published: 17 September 2018

Reader: The Future of Jobs Report 2018

Preparing the Future Workforce


A significant volume of research on the theme of the future of work has emerged since the World Economic Forum published its initial report on the subject—The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution1—at the Forum’s Annual Meeting in January 2016.

What the future of work might hold is a concern that resonates broadly and that has fuelled extensive discussion among policy-makers, business leaders and individual workers.2 Over the past few years, academics, think tanks, strategy consultants and policy-makers have debated what the future of work might look like, how it can be productively shaped for the benefit of economies and societies, and the implications of changes to work for individuals, for their livelihoods, and for the youngest generations studying to enter the future workforce.3

1 World Economic Forum, The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution, 2016. For an overview of some of this recent research, see: Balliester, Thereza and Adam Elsheikhi, The Future of Work: A Literature Review, ILO Research Department Working Paper No. 29, International Labour Organization, 2018.

2 African Development Bank (AFDB), Asian Development Bank (ADB), European Bank for Reconstruction and Development (EBRD), and Inter-American Development Bank (IDB), , 2018.

3 According to the International Labour Organization’s literature review, existing research on the future of work covers a wide range of topics, with a particular focus on technological innovations and inequality. Aspects that would merit additional analysis include the impact of demographics and environmental changes and, ‘[with] regard to the future of job creation and destruction, projections on the impact of automation on agriculture would be essential … particularly for developing countries’; Balliester, and Elsheikhi, .


Common to these recent debates is an awareness that, as technological breakthroughs rapidly shift the frontier between the work tasks performed by humans and those performed by machines and algorithms, global labour markets are likely to undergo major transformations. These transformations, if managed wisely, could lead to a new age of good work, good jobs and improved quality of life for all, but if managed poorly, pose the risk of widening skills gaps, greater inequality and broader polarization. In many ways, the time to shape the future of work is now.

To support responses to the critical questions confronting businesses, governments and workers over the coming years, and to reassess its 2016 findings, the World Economic Forum has conducted a second iteration of the Future of Jobs Survey. While much valuable analysis has been authored over the past two years by a broad range of analysts and researchers, the debate has often focused on the far-term horizon, looking to the future of work in 2030, 2040 or 2050. Those approaches can be complemented by an operational time horizon—with the potential to hold up a mirror to current practises, to provide an opportunity for leaders to re-asses their current direction and its likely outcomes, and to consider potential adjustments. As forecasts of the extent of structural change across global labour markets depend on taking into consideration the time horizon, this report—and future editions—aim to provide a (rolling) five-year outlook. This edition covers the 2018–2022 period.

A particular focus of this new edition of the report is to arrive at a better understanding of the potential of new technologies to create as well as disrupt jobs and to improve the quality and productivity of the existing work of human employees. Our findings indicate that, by 2022, augmentation of existing jobs through technology may free up workers from the majority of data processing and information search tasks—and may also increasingly support them in high-value tasks such as reasoning and decision-making as augmentation becomes increasingly common over the coming years as a way to supplement and complement human labour. The changes heralded by the use of new technologies hold the potential to expand labour productivity across industries, and to shift the axis of competition between companies from a focus on automation-based labour cost reduction to an ability to leverage technologies as tools to complement and enhance human labour.

The data in this report represents the current understanding of human resources leaders—primarily of large employers with operations in multiple geographic locations—of the factors informing their planning, hiring, training and investment decisions at present and through to the report’s 2022 time horizon. The findings described throughout the report are not foregone conclusions but trends emerging from the collective actions and investment decisions taken or envisaged by companies today. The usefulness of this focused perspective lies precisely in its operational concreteness, shedding light on the understanding and intentions of companies that are often setting the pace of global labour market change within their sectors and geographies as well as shaping demand for talent across global value chains and fast-growing online talent platforms.

Since the publication of the 2016 edition of the report, business leaders’ view of the human resources function has begun to shift decisively—continuing a broader rethinking that has been going on for some time. Talent management and workforce analytics are increasingly integral elements of companies’ future-readiness plans. Yet relatively few organizations have so far formulated comprehensive workforce strategies for the Fourth Industrial Revolution. Therefore, this report also aims to serve as a call to action. Rapid adaptation to the new labour market is possible, provided there is concerted effort by all stakeholders. By evaluating the issues at hand from the perspective of some of the world’s largest employers, we hope to improve current knowledge around anticipated skills requirements, recruitment patterns and training needs. Furthermore, it is our hope that this knowledge can incentivize and enhance partnerships between governments, educators, training providers, workers and employers in order to better manage the transformative workforce impact of the Fourth Industrial Revolution.

Survey and research design

The Future of Jobs Report 2018, and the corresponding survey and research framework, represent an evolution of the approach taken in the report’s 2016 edition. The original research framework was developed in collaboration with leading experts from the World Economic Forum’s Global Future Councils, including representatives from academia, international organizations, professional service firms and the heads of human resources of major organizations. The 2018 edition reflects lessons learned from the design and execution of the original survey. The employer survey at the heart of this report was conducted in the first half of 2018 through the World Economic Forum’s global membership community—covering a comprehensive range of industries and geographies (for details, see Appendix B: Industry and Regional Classifications)—and in close collaboration with a number of leading research institutes and industry associations worldwide.

The survey focused on gathering the views of business executives—principally Chief Human Resources Officers (CHROs) facing the workforce changes afoot in today’s enterprises. The questions asked can be briefly outlined in three parts: (1) questions aimed at mapping the transformations currently underway; (2) questions focused on documenting shifting work tasks and therefore skills requirements in the job roles performed by individuals in the workplace of 2022; and (3) questions aimed at understanding the priorities and objectives companies have set themselves in terms of workforce training and reskilling and upskilling (Appendix A: Report Methodology provides a detailed overview of the report’s survey design and research methodology).

The resulting data set represents the operational understanding of strategic human resources professionals, specifically those of large employers operating in multiple locations (Figures 1a and 1b). While only a minority of the world’s global workforce of more than three billion people is directly employed by large multinational employers, these companies often act as anchors for local firm ecosystems. Therefore, in addition to their own significant share of employment, workforce-planning decisions by these firms have the potential to transform local labour markets through indirect employment effects and spillovers, and by setting the pace for adoption of new technologies and changing skills and occupational requirements.

Figure 1: Sample overview by number of locations and number of employees, 2018

Source: Source: Future of Jobs Survey 2018, World Economic Forum.

In total, the report’s data set contains 313 unique responses by global companies from a wide range of industry sectors, collectively representing more than 15 million employees (Table 1). In addition, the report’s regional analysis is based on a diversified sample with a focus on balanced representation of company-level responses for 20 developed and emerging economies—Argentina, Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Mexico, Philippines, Russian Federation, Singapore, South Africa, Korea, Rep., Switzerland, Thailand, United Kingdom, United States and Vietnam—collectively representing about 70% of global GDP. Two sections in the latter part of the report are dedicated to industry- and country-level analysis: The Future of Jobs across Industries and The Future of Jobs across Regions. Appendix B: Industry and Regional Classifications provides an overview of categorizations used.

Table 1: Employees represented by companies surveyed

Source: Source: Future of Jobs Survey 2018, World Economic Forum.

Structure of the report

This report consists of two parts. Part 1 explores the future of jobs, work tasks, skills and workforce strategies over the 2018 to 2022 period, as reflected in the operational understanding of CHROs and others at the frontlines of workforce transformation in some of the world’s largest employers. It touches first on expected trends, technological disruptions and strategic drivers of change transforming business models. It then explores a range of priority issues with regard to the development of comprehensive workforce strategies for the Fourth Industrial Revolution, including employee reskilling and workforce augmentation. Next, it examines specific implications for a range of different industries and geographies. Part 1 concludes with a set of recommendations for upgrading and reviewing existing talent and workforce strategies. Part 2 of the report presents detailed industry-by-industry and country-by-country trends and provides a range of industry-specific and country-specific practical information to decision-makers and experts through dedicated Industry Profiles and Country Profiles. In addition, the reader may refer to the report’s methodological appendix for further information on our survey design, sample selection criteria and research methodology.

Strategic Drivers of New Business Models

As the Fourth Industrial Revolution unfolds, companies are seeking to harness new and emerging technologies to reach higher levels of efficiency of production and consumption, expand into new markets, and compete on new products for a global consumer base composed increasingly of digital natives. More and more, employers are therefore also seeking workers with new skills from further afield to retain a competitive edge for their enterprises and expand their workforce productivity. Some workers are experiencing rapidly expanding opportunities in a variety of new and emerging job roles, while others are experiencing a rapidly declining outlook in a range of job roles traditionally considered ‘safe bets’ and gateways to a lifetime career.

Even as technological advancements pose challenges to existing business models and practices, over the coming years, these same dynamics of technological change are set to become the primary drivers of opportunities for new growth. For example, based on one recent estimate, even a somewhat moderately paced rollout of new automation technologies over the next 10 to 20 years would lead to an investment surge of up to US$8 trillion in the United States alone.4

4 Bain & Company, , 2018.


According to the global employers surveyed for this report, four specific technological advances—ubiquitous high-speed mobile internet; artificial intelligence; widespread adoption of big data analytics; and cloud technology—are set to dominate the 2018–2022 period as drivers positively affecting business growth (Table 2). They are flanked by a range of socio-economic trends driving business opportunities in tandem with the spread of new technologies, such as national economic growth trajectories; expansion of education and the middle classes, in particular in developing economies; and the move towards a greener global economy through advances in new energy technologies. By contrast, technological and social trends expected to negatively impact business growth include increasing protectionism; cyber threats; shifts in government policies; the effects of climate change; and increasingly ageing societies.

By 2022, according to the stated investment intentions of companies surveyed for this report, 85% of respondents are likely or very likely to have expanded their adoption of user and entity big data analytics (Figure 2). Similarly, large proportions of companies are likely or very likely to have expanded their adoption of technologies such as the internet of things and app- and web-enabled markets, and to make extensive use of cloud computing. Machine learning and augmented and virtual reality are poised to likewise receive considerable business investment. While estimated use cases for humanoid robots, a fixture of the current media discourse on the future of jobs, appear to remain somewhat more limited over the 2018–2022 period under consideration in this report,5 collectively, a broader range of recent robotics technologies at or near commercialization—including stationary robots, non-humanoid land robots and fully automated aerial drones, in addition to machine learning algorithms and artificial intelligence—are attracting significant business interest in adoption.6

5 According to an estimate by Bain & Company, based primarily on the rapidly declining cost of robotic dexterity for service applications, humanoid robots are likely to reach commercialization in the early 2020s, specifically creating ‘a strong business case for the automation of many tasks in restaurant kitchens and bars’; see: Bain & Company, .

6 For example, ‘cobots’—robotic helper units installed alongside human workers to enhance their productivity and often costing less than one-quarter the price of traditional robots—are set to have a large commercial and workforce impact over the coming years, being well-placed for deployment in many parts of the service sector as yet largely untouched by workplace automation; see: Bain & Company, .

There are complex feedback loops between new technology, jobs and skills. New technologies can drive business growth, job creation and demand for specialist skills but they can also displace entire roles when certain tasks become obsolete or automated. Skills gaps—both among workers and among the leadership of organizations—can speed up the trends towards automation in some cases but can also pose barriers to the adoption of new technologies and therefore impede business growth.

Opportunities for new and emerging technologies to drive inclusive economic and business growth over the 2018–2022 period are manifold, yet concrete and viable mechanisms for preparing the global labour market—thereby enabling employers to better leverage these opportunities across industries and regions—remain elusive. A mindset of agile learning on the part of both company leaders and workers will be needed, starting with an ability to reimagine the routines and limits of today’s jobs as part of a comprehensive workforce strategy for the Fourth Industrial Revolution.

In order to harness the transformative potential of the Fourth Industrial Revolution, business leaders across all industries and regions will increasingly be called upon to formulate a comprehensive workforce strategy ready to meet the challenges of this new era of accelerating change and innovation. Policy-makers, educators, labour unions and individual workers likewise have much to gain from deeper understanding of the new labour market and proactive preparation for the changes underway. Key factors to consider include mapping the scale of occupational change underway and documenting emerging and declining job types; highlighting opportunities to use new technologies to augment human work and upgrade job quality; tracking the evolution of job-relevant skills; and, finally, documenting the business case for investment in retraining, upskilling and workforce transformation. The following three sub-sections of the report aim to provide informative data and evidence to support such an endeavour.

The 2022 jobs landscape

As discussed in the report’s Introduction, recent projections of the extent of structural change in the global labour market depend significantly on the time horizon taken into consideration.7 In addition to the rate of technological advancement itself, a range of other considerations—such as ease of commercialization, public adoption of new technologies8 and existing labour laws—influence the rate at which these developments accelerate workforce transformation.

7 See, for example, the differing perspectives provided by: Bain & Company, ; McKinsey & Company, , McKinsey Global Institute (MGI), 2017; and PwC, , 2018.

8 As noted by a recent Bain & Company study, while public reaction to new technologies is likely to vary substantially from one country to the next, thereby accelerating or decelerating their adoption, differences in public policies toward new technologies such as automation may be harder to sustain if their applications are tradeable. For example, if London were to deregulate the application of fully autonomous machine learning algorithms in financial markets, competitive forces are likely to put greater pressure on technology regulators in New York to follow suit. By contrast, if London were to permit coffee shops more generous labour automation leeway than New York, differences are more likely to remain localized; see: Bain & Company, .


In the estimates of employers surveyed for this report, global labour markets are set to undergo significant transformation over the coming five years.

A cluster of emerging roles will gain significantly in importance over the coming years, while another cluster of job profiles are set to become increasingly redundant (Figure 3). Across all industries, by 2022, the cluster of emerging professions is set to increase its share of employment from 16% to 27% of the total employee base of our company respondents, whereas the employment share of declining roles is set to decrease from currently 31% to 21% (Figure 3). In purely quantitative terms, therefore, the expectation emerging from the estimates of employers surveyed for this report is that, by 2022, structural decline of certain types of jobs (10% decline) will be fully counter-balanced by job creation and the emergence of new professions (11% growth).About half of today’s core jobs—making up the bulk of employment across industries—will remain somewhat stable in the period up to 2022.

Applied to our sample, representing over 15 million workers in total, the above numbers would suggest a decline of 0.98 million jobs and a gain of 1.74 million jobs. Extrapolating from these trends for the global (non-agricultural) workforce employed by large firms, we generate a range of estimates for job churn in the period up to 2022. One of these indicates that 75 million jobs may be displaced by the above trends, while 133 million additional new roles may emerge concurrently.9

9 These extrapolated figures are based on employers’ current projections for the set of roles with increasing, declining and stable demand in the period up to 2022, which were estimated by employers as a share of each enterprise’s total workforce. The figures were then applied to the International Labour Organization’s estimates and projections of global non-agricultural employment in both 2018 and 2022, adjusted for the estimated share of total employment represented by this report’s respondent data, i.e. large businesses. The figures used for estimating the global share of large business employment are based on established estimates by the World Bank, US Bureau of Labor Statistics and Eurostat, holding the distribution of firm size constant between 2018 and 2022.


It should be noted, however, that these projections primarily represent the share of roles within the remit of large multinational employers. A complementary perspective might emerge from analysis that focuses on small- and medium-sized enterprises, or more fully takes into account employment sectors such as health, care and education. In particular such segments of economic activity hold the promise for further job creation opportunities.

As they stand today responses to the Future of Jobs Survey indicate the potential for a positive outlook for the future of jobs. Yet that outlook is underscored by the need to manage a series of workforce shifts, set to accompany the adoption of new technologies. By 2022, 59% of employers surveyed for this report expect that they will have significantly modified the composition of their value chain, and nearly half expect to have modified their geographical base of operations. In addition, 50% of companies expect that automation will lead to some reduction in their full-time workforce, based on the job profiles of their employee base today.

Also by 2022, 38% of businesses surveyed expect to extend their workforce to new productivity-enhancing roles, and more than a quarter expect automation to lead to the creation of new roles in their enterprise. In addition, businesses are set to expand their use of contractors doing task-specialized work, with many respondents highlighting their intention to engage workers in a more flexible manner, utilizing remote staffing beyond physical offices and decentralization of operations. Respondents expect increased job creation in such project-based, temporary and freelancing roles, pointing to structural labour market transformations in terms of contractual arrangements and employment relations as well as occupational profiles. In summary, while overall job losses are predicted to be offset by job gains, there will be a significant shift in the quality, location, format and permanency of new roles.

Among the range of roles that are set to experience increasing demand in the period up to 2022 are established roles such as Data Analysts and Scientists, Software and Applications Developers, and Ecommerce and Social Media Specialists that are significantly based on and enhanced by the use of technology. Also expected to grow are roles that leverage distinctively ‘human’ skills such as Customer Service Workers, Sales and Marketing Professionals, Training and Development, People and Culture, and Organizational Development Specialists as well as Innovation Managers. Moreover, our analysis finds extensive evidence of accelerating demand for a variety of wholly new specialist roles related to understanding and leveraging the latest emerging technologies: AI and Machine Learning Specialists, Big Data Specialists, Process Automation Experts, Information Security Analysts, User Experience and Human-Machine Interaction Designers, Robotics Engineers and Blockchain Specialists (Table 3).

Across the industries surveyed, jobs expected to become increasingly redundant over the 2018–2022 period are routine-based, middle-skilled white-collar roles—such as Data Entry Clerks, Accounting and Payroll Clerks, Secretaries, Auditors, Bank Tellers and Cashiers (Table 3)—that are susceptible to advances in new technologies and process automation. These shifts reflect unfolding and accelerating trends that have evolved over a number of recent years—continuing developments that have impacted roles in retail banking (ATMs), consumer sales (self-checkout kiosks) and other sectors.10 Given that the skills requirements of emerging roles frequently look very different from those of roles experiencing redundancy, proactive, strategic and targeted efforts will be needed to map and incentivize workforce redeployment.

10 Barclays, , 2018.


Industries are set to take diverse routes in the adoption of new technologies, and the distinctive nature of the work performed within each sector will result in disruption to jobs and skills that will demand industry-specific adaptation. For example, given comparatively high levels of education in the financial services industry, displaced roles may be somewhat more easily offset by redeploying workers in alternative, higher value-added functions. In contrast, the two largest job roles in the consumer industry, Cashiers and Sales Associates—accounting for no less than 45% of total industry employment—have a comparatively small share of workers with advanced education.11 Cross-industry analysis of the roles experiencing falling and rising demand suggests the possibility of leveraging those industry-specific differences for the benefit of displaced workers, by expanding the search for new opportunities across the industry landscape.

While the labour market shifts described in this section are not foregone conclusions, they are reasonable forecasts emerging from the actions and investment decisions taken by companies in response to global trends today. As new technology adoption builds momentum, companies feel competitive pressures similar to the way they felt compelled to create global supply chains in the 1990s and 2000s.12 These trends affecting business leaders’ decision environments are prompting a wide range of company responses that collectively shape the future nature of jobs (Figure 4).

11 Ibid.

12 Bain & Company, .


While individual companies may not have the option to disconnect their corporate strategy from the fundamental trajectory of these wider trends, such as the unfolding Fourth Industrial Revolution, they do, however, have the possibility of formulating a proactive response. Two investment decisions, in particular, will be crucial to shaping the future of jobs: the question of whether to prioritize automation or augmentation and the question of whether or not to invest in workforce reskilling. These two crucial dimensions are examined further in the following two sub-sections.

From automation to augmentation

Some forecasts project that advances in automation will result in the wholesale replacement of the human workforce. Encompassing the near- or medium-term timeframes, our analysis suggests another perspective: that work currently performed by humans is being augmented by machine and algorithmic labour. Responses from employers surveyed for this report can be interpreted as evidence for the increasing viability of what a number of experts have called an ‘augmentation strategy’. Namely, it has been suggested that businesses can look to utilize the automation of some job tasks to complement and enhance the human workforces’ comparative strengths and ultimately to enable and empower employees to extend to their full potential and competitive advantage.13 Rather than narrowly focusing on automation-based labour cost savings, an augmentation strategy takes into account the broader horizon of value creating activities that can be accomplished by human workers, often in complement to technology, when they are freed of the need to perform routinized, repetitive tasks and better able to use their distinctively human talents.14

13 See: Ton, Zeynep and Sarah Kalloch, , Harvard Business Review, June 2017; Deloitte, , 2018.

14 Davenport, Thomas and Julia Kirby, , Harvard Business Review, June 2015.


Importantly, most automation occurs at the level of specific work tasks, not at the level of whole jobs.15 For example, according to one recent study, whereas nearly two-thirds of today’s job roles entail at least 30% of tasks that could be automated based on currently available technology, only about one-quarter of today’s job roles can be said to have more than 70% of tasks that are automatable.16 A similar recent analysis finds that workforce automation is likely to play out in three waves between today and the mid-2030s, increasing the share of fully automatable manual tasks in the most affected current job roles from less than 5% today to nearly 40% by the mid-2030s, and the share of automatable tasks involving social skills from less than 5% today to about 15% in the same time horizon.17 The most relevant question to businesses, governments and individuals is not to what extent automation will affect current employment numbers, but how and under what conditions the global labour market can be supported in reaching a new equilibrium in the division of labour between human workers, robots and algorithms. Workforce planning and investment decisions taken today will play a crucial role in shaping this process.

15 See for example: Arntz, Melanie, Terry Gregory and Ulrich Zierahn, , OECD Social, Employment and Migration Working Papers No 189, Organisation for Economic Cooperation and Development (OECD), 2016; McKinsey Global Institute, , McKinsey Global Institute (MGI), 2017; PwC, . For a range of relevant additional considerations, see: van der Zande, Jochem, et al., , Innovative Internet: Report 5, Stockholm School of Economics Institute for Research, 2018.

16 McKinsey Global Institute, .

17 PwC, ; the three waves of workforce automation identified by the report consist of an (to early 2020s; involving ‘automation of simple computational tasks and analysis of structured data, affecting data-driven sectors such as financial services’); an (to late 2020s; involving ‘dynamic interaction with technology for clerical support and decision making … including robotic tasks in semi-controlled environments such as moving objects in warehouses); and an (to mid-2030s; involving ‘automation of physical labour and manual dexterity, and problem-solving in dynamic real-world situations that require responsive actions, such as in transport and construction’).


Waves of automation have reshaped the global economy throughout history. Since the first and second industrial revolutions, organizations have bundled specific work tasks into discrete job roles, giving rise to distinct occupational profiles and optimizing the process of economic value creation based on the most efficient division of labour between humans and machines technologically available at the time.18 As technological change and progress have increased workforce productivity by ‘re-bundling’ work tasks into new kinds of jobs, so they have seen the decline of obsolete job profiles and the dynamic rise of wholly new ones, historically leaving the balance of net job and economic value creation firmly on the positive side.19

18 A thought-provoking empirical perspective on this process is provided by: Cohen, Lisa, “Assembling Jobs: A Model of How Tasks Are Bundled Into and Across Jobs”, , vol. 24, no. 2, 2012.

19 Autor, David, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation”, , vol. 29, no. 3, 2015, pp. 3–30.


While the Fourth Industrial Revolution’s wave of technological advancement will reduce the number of workers required to perform certain work tasks, responses by the employers surveyed for this report indicate that it will create increased demand for the performance of others, leading to new job creation. Moreover, while the current popular discourse is often fixated on technology that substitutes for humans, technology will also create new tasks—from app development to piloting drones to remotely monitoring patient health20—opening up opportunities for work never previously done by human workers,21 highlighting that different types of new technology may bring about very different outcomes for workers.22

20 For example, since its launch in 2008, developers have earned more than US$86 billion through Apple’s App Store platform, and app development is estimated to have created more than 1.7 million jobs in the United States and more than 2 million jobs in Europe; see: Apple, , https://www.apple.com/newsroom/2018/01/app-store-kicks-off-2018-with-record-breaking-holiday-season, 2018; Mandel, M., , Progressive Policy Institute, http://www.progressivepolicy.org/blog/u-s-app-economy-update, 2017; and Mandel, M., , Progressive Policy Institute, http://www.progressivepolicy.org/blog/update-on-european-app-economy-jobs, 2018.

21 Dellot, Benedict, “Why automation is more than just a job killer”, , 20 July 2018, https://www.thersa.org/discover/publications-and-articles/rsa-blogs/2018/07/the-four-types-of-automation-substitution-augmentation-generation-and-transference. The RSA, a British think tank, accordingly distinguishes four types of automation: (1) (‘technology taking on a task that would [otherwise have been] be undertaken by a worker’; (2) (‘[technology] expand[ing] the capability of workers, allowing them to achieve more and better-quality work in a shorter space of time’); (3) (‘[technology] generat[ing] tasks that were never done by humans previously … creat[ing] work rather than captur[ing] it from others’); (4) (‘technology shift[ing] responsibility for undertaking a task from workers to consumers. Self-service checkouts, for instance, have not done away with the job of processing items through tills. Instead they’ve merely passed on the responsibility to shoppers. … This form of automation typically relies on … sophisticated UX and UI Design’); ibid.

22 An innovative effort to distinguish between labour-substituting and labour-augmenting technologies—based on 78 individual tools and technologies—is provided by: Nedelkoska, Ljubica and Glenda Quintini,, OECD Social, Employment and Migration Working Papers, No. 202, OECD, http://dx.doi.org/10.1787/2e2f4eea-en, 2018.


The rise of workplace automation in its many forms has the potential to vastly improve productivity and augment the work of human employees. Automation technology can help remove the burden of repetitive administrative work and enable employees to focus on solving more complex issues while reducing the risk of error, allowing them to focus on value-added tasks.23 Examples of now well-established and almost unremarkable automation-based augmentation technology that hardly existed 25 years ago range from computer-aided design and modelling software used by architects, engineers and designers, to robotic medical tools used by doctors and surgeons, through to search engine technology that allows researchers to find more relevant information. In theory, these technologies take away tasks from workers, but in practice their overall effect is to vastly amplify and augment their abilities.24

23 KPMG, ; Cognizant, , 2015.

24 Dellot, .


The estimates of companies surveyed for this report provide a nuanced view of how human-machine collaboration might evolve in the time horizon up to 2022 (Figure 5). In today’s enterprise, machines and algorithms most often complement human skills in information and data processing. They also support the performance of complex and technical tasks, as well as supplementing more physical and manual work activities. However, some work tasks have thus far remained overwhelmingly human: Communicating and interacting; Coordinating, developing, managing and advising; as well as Reasoning and decision-making. Notably, in terms of total working hours, in the aggregate no work task was yet estimated to be predominantly performed by a machine or an algorithm.

By 2022, this picture is projected to change somewhat. Employers surveyed for this report expect a deepening across the board of these existing trends, with machines and algorithms on average increasing their contribution to specific tasks by 57%. Relative to their starting point today, the expansion of machines’ share of work task performance is particularly marked in Reasoning and decision-making; Administering; and Looking for and receiving job-related information. The majority of an organization’s information and data processing and information search and transmission tasks will be performed by automation technology (Figure 5).

Based on one recent estimate, the next wave of labour-augmenting automation technology could lead to an average labour productivity increase across sectors of about 30% compared to 2015, with some significant variation by industry.25 For employers, optimally integrating humans and automation technology will require an analytical ability to deconstruct the work performed in their organizations today into discrete elements—that is, seeing the work tasks of today’s job roles as independent and fungible components—and then reconfiguring these components to reveal human-machine collaboration opportunities that are more efficient, effective and impactful.26 Among other things, success in this domain will require a strategic repositioning of the corporate human resource function and expanded organizational capabilities in data analysis and workforce analytics.27

25 Measured in incremental additional US$ of gross output per worker, i.e. excluding baseline forecasts of labour productivity growth; Bain & Company, .

26 Jesuthasan, Ravin and John Boudreau, , Harvard Business Review, April 2017; also see: Jesuthasan, Ravin, “You may not be a disrupter, but you might find opportunities in the gig economy”, , 24 July 2017, https://www.willistowerswatson.com/en/insights/2017/07/insights-gig-economy.

27 Shook, Ellyn and Mark Knickrehm, , Accenture Strategy, 2017.


For workers, improved productivity may allow them to re-focus their work on high-value activities that play to the distinctive strengths of being human. However, to unlock this positive vision, workers will need to have the appropriate skills that will enable them to thrive in the workplace of the future. And as discussed in detail in the next section, even for those who currently have these skills, the pace at which tasks are being augmented and skills are changing continues to accelerate.

The reskilling imperative

Current shifts underway in the workforce will displace some workers while at the same time create new opportunities for others. However, maximizing the gains and minimizing the losses requires attention not just from policy-makers, but also coherent responses from companies to find win-win solutions for workers and for their bottom line. Leading research documents the potentially divergent impact of the introduction of automation technology, demonstrating how both job design (how tasks are organized into jobs) and employee’s possession (or lack thereof) of skills complementing newly introduced technologies contribute to eventual outcomes for companies and workers.28 Workers with in-demand skills ready for augmentation may see their wages and job quality increase considerably. Conversely, even if automation only affects a subset of the tasks within their job role, workers lacking appropriate skills to adapt to new technologies and move on to higher value tasks may see their wages and job quality suppressed by technology steadily eroding the value of their job, as it encroaches on the tasks required to perform it.29 Therefore, central to the success of any workforce augmentation strategy is the buy-in of a motivated and agile workforce, equipped with futureproof skills to take advantage of new opportunities through continuous retraining and upskilling.30 Given the wave of new technologies and trends disrupting business models and the changing division of labour between workers and machines transforming current job profiles, the vast majority of employers surveyed for this report expect that, by 2022, the skills required to perform most jobs will have shifted significantly. While these skill shifts are likely to play out differently across different industries and regions,31 globally, our respondents expect average skills stability—the proportion of core skills required to perform a job that will remain the same—to be about 58%, meaning an average shift of 42% in required workforce skills over the 2018–2022 period.32

28 Autor, David, Frank Levy and Richard Murnane, , NBER Working Paper No. 7890, National Bureau of Economic Research, 2000.

29 Barclays, .

30 Shook and Knickrehm, .

31 For a detailed analysis, see the sections The Future of Jobs across Industries and The Future of Jobs across Regions; also see: McKinsey & Company, , Discussion Paper, McKinsey Global Institute (MGI), 2018.

32 For a more extensive discussion of the concept of , see: World Economic Forum, , 2016 and CEDEFOP, , 2012.


Key skills demand trends identified by our analysis include, on the one hand, a continued fall in demand for manual skills and physical abilities and, on the other hand, a decrease in demand for skills related to the management of financial and other resources as well as basic technology installation and maintenance skills (Table 4). Skills continuing to grow in prominence by 2022 include Analytical thinking and innovation as well as Active learning and learning strategies. The sharply increased importance of skills such as Technology design and programming highlights the growing demand for various forms of technology competency identified by employers surveyed for this report. Proficiency in new technologies is only one part of the 2022 skills equation, however, as ‘human’ skills such as creativity, originality and initiative, critical thinking, persuasion, and negotiation will likewise retain or increase their value, as will attention to detail, resilience, flexibility and complex problem-solving. Emotional intelligence, leadership and social influence as well as service orientation also see an outsized increase in demand relative to their current prominence.

Companies will need to pursue a range of organizational strategies in order to stay competitive in the face of rapidly changing workforce skills requirements. To do this, the skills of executive leadership and the human resources function will also need to evolve to successfully lead the transformation. With regard to likely approaches towards workers facing shifting skills demand, companies surveyed for this report specifically highlight three future strategies: hiring wholly new permanent staff already possessing skills relevant to new technologies; seeking to completely automate the work tasks concerned; and retraining existing employees (Figure 6). The likelihood of hiring new permanent staff with relevant skills is nearly twice the likelihood of strategic redundancies of staff lagging behind in new skills adoption. However nearly one-quarter of companies are undecided or unlikely to pursue the retraining of existing employees. Two-thirds expect workers to adapt and pick up skills in the course of their changing jobs. Between one-half and two-thirds are likely to turn to external contractors, temporary staff and freelancers to address their skills gaps.

Respondents to our survey further indicate that they are set to prioritize and focus their reskilling and upskilling efforts on employees currently performing high value roles as a way of strengthening their enterprise’s strategic capacity, with 54% and 53% of companies, respectively, stating they intend to target employees in key roles and in frontline roles which will be using relevant new technologies. In addition, 41% of employers are set to focus their reskilling provision on high-performing employees while a much smaller proportion of 33% stated that they would prioritize at-risk employees in roles expected to be most affected by technological disruption. In other words, those most in need of reskilling and upskilling are least likely to receive such training.

Our findings corroborate a range of recent research indicating that, currently, only about 30% of employees in today’s job roles with the highest probability of technological disruption have received any kind of professional training over the past 12 months. In addition, they are on average more than three times less likely than employees in less exposed roles to have participated in any on-the-job training or distance learning and about twice less likely to have participated in any formal education.33 Other recent research similarly finds that, currently, reskilling and upskilling efforts are largely focused on already highly-skilled and highly-valued employees.34

These findings are a cause for concern, given that making an inclusive culture of lifelong learning a reality is increasingly imperative for organizations and for workers whose growth strategies and job roles are being affected by technological change. In particular, they highlight that the bottom-line impact and business case for reskilling and upskilling investments remain somewhat unclear and require much greater attention. Time requirements, costs, success cases and appropriate delivery models for reskilling and upskilling are likely to look very different for different categories of job roles and workers.

To provide a preliminary picture, companies surveyed for this report highlight that, overwhelmingly, their key success metric for reskilling and upskilling initiatives is increased workforce productivity—chosen by 90% of respondent employers—followed by retention of high-skilled workers, enabling workers in frontline roles to make the best use of new technologies and increased employee satisfaction. Significantly smaller proportions of companies regard reskilling as a means of lowering recruitment costs, redeploying employees in disrupted job roles or as a way to increase the skills base of their medium- and lower-skilled workforce. In short, to date reskilling has been regarded by employers as a narrow strategy focused on specific subsets of employees, not as a comprehensive strategy to drive workforce transformation.

Finally, while companies themselves will need to take the lead in creating capacity within their organizations to support their transition towards the workforce of the future, the economic and societal nature of these challenges means that they will also increasingly need to learn to partner with other stakeholders for managing the large-scale retraining and upskilling challenges ahead. Tangible collaboration opportunities include partnering with educators to reshape school and college curricula, intra- and inter-industry collaboration on building talent pipelines, and partnerships with labour unions to enhance cross-industry talent mobility. Governments may likewise become key partners in creating incentives for lifelong learning, ensuring shared standards for retraining and strengthening safeguards for workers in transition.35 However, more guidance and good practice learning opportunities will be needed. Currently, respondents to our survey expect to continue to primarily look to specialized internal departments to meet their retraining needs for the period up to 2022, with some supplementary support from professional services firms, industry associations and academic experts (Figure 8). Less than half of companies actively consider partnering with government programmes and slightly more than a fifth see labour unions as preferred partners.

33 Nedelkoska and Quintini, .

34 McKinsey & Company, .

35 Ibid.


Companies surveyed for this report anticipate that, over the 2018–2022 period, on average, around half of all retraining will be delivered through internal departments, about one quarter through private training providers and about one-fifth through public education institutions. About 34% of the retraining to be delivered directly by employers is expected to result in an accreditation recognized outside of the company in question. Expanding such systems for certifiable skills recognition could significantly promote the marketplace for corporate reskilling and upskilling in the near future and improve outcomes for workers. These findings highlight both the future role of companies as learning organizations and the range of possible reskilling and upskilling multistakeholder collaboration arrangements.

The Future of Jobs across Industries

The future of jobs is not singular. It will diverge by industry and sector, influenced by initial starting conditions around the distribution of tasks, different investments in technology adoption, and the skills availability and adaptability of the workforce. As a consequence, different industries experience variation in the composition of emerging roles and in the nature of roles that are set to have declining demand.

Among the trends driving growth across industries over the 2018–2022 period, advances in mobile internet are likely to have a distinct impact in the Aviation, Travel & Tourism industry, the Financial Services & Investors industries, and in the Consumer industry. The rapid adoption of new technologies by consumers as well as advancements in cloud technology are set to drive growth in the Information & Communication Technologies industry, while the availability of big data is expected to have an even broader impact on the Financial Service & Investors and the Energy Utilities & Technologies industries. New energy supplies and technologies, in tandem with advances in computing power, are set to drive gains in the Energy Utilities & Technologies sector. Among non-technological drivers of business growth, increasing affluence in developing economies is poised to drive growth in the Aviation, Travel & Tourism; Global Health & Healthcare; and Chemistry, Advanced Materials & Biotechnology industries.

Table 5 demonstrates the range of demand for the adoption of specific technologies. Robotic technology is set to be adopted by 37% to 23% of the companies surveyed for this report, depending on industry. Companies across all sectors are most likely to adopt the use of stationary robots, in contrast to humanoid, aerial or underwater robots. However, leaders in the Oil & Gas industry report the same level of demand for stationary and aerial and underwater robots, while employers in the Financial Services & Investors industry are most likely to signal the planned adoption of humanoid robots in the period up to 2022. Distributed ledger technologies are set to have a particular impact in the Financial Services industry, which promises to be an early adopter of the technology. In fact, 73% of respondents expect their enterprise to adopt its use. Another industry set to scale its adoption of distributed ledger technologies will be the Global Health & Healthcare industry. Machine learning is expected to be adopted across a range of industries, including banking and insurance, where it may disrupt risk prediction; in the medical field, where it may be used for advanced diagnosis; across the energy sector, where it may lead to predictive maintenance; and in the consumer sector, where it may enhance the industry’s ability to model demand.

While technologies have the capacity to automate and potentially augment a variety of tasks across enterprises, this will vary by industry-specific capital investment, the risks associated with automating sensitive tasks, the unknown knock-on-effects of how machines and algorithms will perform the task, the presence of a longer-term workforce strategy, and the managerial challenges of re-orienting the operations of different enterprises. Additionally, many sectors face disruption and shifts in demand through non-technological factors, such as the effect of ageing in the Global Health & Healthcare industry. Efficiencies in healthcare technologies will thus become necessary innovations to meet the demographic changes afoot, freeing time spent in administration and record keeping for caregiving activities.36

The growth potential of new technological expansion is buffered by multi-dimensional skills gaps across local and global labour markets, and among the leadership of enterprises. Skills gaps among the local labour market are among the most cited barriers to appropriate technology adoption for a number of industries, but they are particularly strong concerns for business leaders in the Aviation Travel & Tourism, Information & Communication Technologies, Financial Services & Investors, and Mining & Metals industries. Companies in Global Health & Healthcare as well as Infrastructure industries are most likely to cite leadership skills gaps as significant barriers, while the Chemistry, Advanced Materials & Biotechnology and Information & Communication Technologies sectors report broad global labour market skills shortages.

There is a distinctive footprint of tasks performed across each industry. For example, on average, workers in the Mining & Metals industry spend the majority of their time in physical and manual tasks, while those in the Professional Services industry spend the majority of their time on tasks related to communicating and interacting. In the Oil & Gas, Infrastructure, and Chemistry, Advanced Materials & Biotechnology industries, the tasks that occupy today’s workers for the largest proportion of their time focus on the performance of complex and technical activities. Administrative activities are particularly prominent in the Infrastructure industry as well in the Mining & Metals and Financial Services & Investors industries.

As industries make investments in new technologies, the impact on each industry as a whole is determined by the task composition of each sector and the desirability of automating or augmenting specific tasks. Existing research has highlighted that some industries remain labour-intensive in the production of goods and services, leading to low productivity growth.37 If managed well, the augmentation of a range of tasks today can create the opportunity for new, higher productivity growth. For example, administering and physical tasks are often low value and low productivity tasks. In the current projections of companies surveyed for this report, administrative tasks in the Financial Services & Investors sector are set to be significantly replaced by machine labour. While today machines and algorithms perform 36% of the collective hours spent on this task, by 2022 this share will rise to 61%, with knock-on effects on the demand for Data Entry Clerks, Secretarial staff and Accounting staff. In the Energy and Consumer sectors, physical and manual work activities will also be replaced. Today, respectively 38% and 30% of such tasks in these two sectors are performed by machines and algorithms. By 2022, those rates are expected to be 56% and 50% respectively, with knock-on effects on demand for Assembly and Factory Workers, Cashiers, and Stock-Keeping Clerks. Distinctively, the Aviation Travel & Tourism and Information & Communication Technologies sectors are those most likely to venture into automating some complex and technical activities. For example, today 25% of labour in the Information & Communications Technology industry is performed by machines and algorithms, while 46% is projected for 2022.

36 Ibid.

37 See: Bain & Company, ; McKinsey & Company, ; Barclays, .


All industries expect sizable skills gaps, stating that at least 50% of their workforce will require reskilling of some duration. According to respondents to the Future of Jobs Survey, more than 55% of workers across the Aviation, Travel & Tourism; Financial Services & Investors; Chemistry, Advanced Materials & Biotechnology; and Global Health & Healthcare sectors will need some reskilling. The Aviation, Travel & Tourism industry outlines the largest demand for reskilling, projecting that 68% of its workforce will require some reskilling. Further, companies in that industry project that 18% of the workforce will require reskilling lasting more than one year.

While most industry respondents expect to observe declining demand for a set of, often labour-intensive roles dominated by manual and routinized work, that decline is often counter-balanced by growth across other specializations. A critical concern that will affect all industries will be the imperative to reskill workers currently in roles that have declining prospects into ones with expanding prospects.

Many of the companies surveyed for this report project that, by 2022, they will both expand and contract parts of their current workforce, with expansion likely to offset the contraction. However, this balance looks different across different industry sectors. Mining & Metals industry respondents, alongside those from the Consumer and Information & Communication Technologies industries, expect to see a reduction in their workforce due to automation, while Professional Services industry respondents expect that the changes afoot are more likely to lead to an expansion of their workforce.

Projected adaptations specific to the skilling needs associated with these changes include the potential to buy, build, borrow or automate talent. In particular, many of the Future of Jobs Survey respondents highlighted that they are likely to hire new permanent staff with skills that are relevant to the adopted technologies. The broad mobility sector is most likely to look to automation as a way to solve its projected talent challenges, and is least likely to look to reskill current employees. In contrast, companies in the Global Health & Healthcare industry—in addition to the Chemistry, Advanced Materials & Biotechnology industry—are most likely to look to retrain existing workers.

The trusted partners with the potential to support industries in their transformation vary across three key groups: specialized departments within the companies in question, professional services firms and industry associations. A series of other potential stakeholders—education institutions, government programmes and labour unions—received less emphasis as possible partners in these transitions. The Oil & Gas, Mining & Metals, and Energy Utilities & Technology industries are more likely to look to industry associations to support their workforce transition. Companies in the Global Health & Healthcare sector name professional services firms as their primary support mechanism, but also name academic experts as their third-most important support pillar. Finally, Aviation, Travel & Tourism firms are most likely to name local education institutions as their third-most important support structure. Part 2 of this report contains distinct Industry Profiles that offer a deeper look at technology, jobs, tasks and skills trends within different sectors.

The Future of Jobs across Regions

As the Fourth Industrial Revolution unfolds across the globe, the future of jobs can be expected to develop with both common and differentiated characteristics across different countries and regions of the world.38 In the near term, our data shows that the mix of prevalent industries in different countries will result in different national combinations of the effects described in the previous section, The Future of Jobs across Industries. Additionally, as global companies choose to differentiate and locate specific job roles and economic activities in certain countries over others due to a range of strategic considerations, there will be a secondary effect on the future of jobs in a range of developed and emerging markets, highlighting the ongoing importance of global supply chains and multinational companies in shaping the structure of the global economy.3940 With regard to the factors determining job location decisions, companies surveyed for this report overwhelmingly cite availability of skilled local talent as their foremost consideration, with 74% of respondents providing this factor as their key consideration. In contrast, 64% of companies cite labour costs as their main concern (Table 7). Notably, while we find some evidence of pure labour cost considerations being more important in emerging economies—with, for example, 74% of companies operating in South Africa and a similar share of companies operating in the Philippines highlighting this rationale, compared to 57% in the United Kingdom—skilled local talent availability remains the single most important factor behind job location decisions in these economies as well. A range of additional relevant factors—such as the flexibility of local labour laws, industry agglomeration effects or proximity of raw materials—were considered of lower importance relative to skilled local talent availability and labour cost considerations.

38 For a recent comprehensive overview, see: African Development Bank (AFDB), Asian Development Bank (ADB), European Bank for Reconstruction and Development (EBRD), Inter-American Development Bank (IDB), 2018.

39Nedelkoska and Quintini,.40

40 See, for example: Baldwin, Richard, , Harvard University Press, 2016; Reijnders, Laurie S.M. and Gaaitzen de Vries, , GGDC Research Memorandum 167, University of Groningen-Groningen Growth and Development Centre, 2017.


Furthermore, our analysis finds some industry-specific variation with regard to overall labour cost sensitivity relative to skilled local talent availability considerations. For example, across countries and regions, Consumer, Energy Utilities & Technologies, Financial Services & Investors, Infrastructure, and Mining & Metals are industries that tend to emphasize labour cost over skilled local talent availability. In contrast, the Automotive, Aerospace, Supply Chain & Transport; Chemistry, Advanced Materials & Biotechnology; Global Health & Healthcare; and Information & Communication Technologies industries tend to place a larger priority on skilled local talent availability (Table 7).

While a detailed discussion of the potential impact of automation on manufacturing in different countries and regions—and the potential for ‘re-shoring’—is beyond the scope of this report, it is worth noting the link between labour costs, skills and investment in automation technologies in advanced and emerging economies. For example, according to one recent study, in 1997, manufacturing value-added per dollar of labour cost was twice as high in Mexico than in the United States. By 2013, this gap had shrunk to less than 15%.41 Provided simultaneous investment in automation technology and labour augmentation in advanced economies continues apace over the 2018–2022 period, it is not inconceivable that shifting comparative advantage in labour costs will affect the industrial structure of economies such as Vietnam through re-shoring of work tasks in sectors such as textiles, apparel, footwear or electronics assembly.42 Indeed, more than half of companies surveyed for this report expected that by 2022 they would be considering adjusting the composition of their value chains in response to the adoption of new technologies, and just under half expected targeting new talent by modifying the location of their operations.

41 Bain & Company, .

42 International Labour Organization (ILO), , 2017.


At least two key factors suggest that the grounds for optimism may outweigh concerns. Firstly, even if factory automation and labour augmentation in advanced industrial economies might lead to some re-shoring over the 2018–2022 period, many emerging economies are increasingly shifting toward a domestic consumption driven growth model, with rising local middles classes generating increased demand for goods and services traditionally intended for export.43 Secondly, as discussed in the section From Automation to Augmentation, new technologies give rise to new job roles, occupations and industries, with wholly new types of jobs emerging to perform new work tasks related to new technologies. Comparing occupational structures across advanced and emerging economies suggests that there is considerable scope for job growth in many sectors in the latter. For example, healthcare and education jobs provide 15% of total employment in the United States, and business services such as finance and real estate provide 19%, whereas, in emerging economies in East Asia and the Pacific, the respective shares are 3.5%–6.0% and 1.5%–6.0%, suggesting considerable scope for job growth.44

43 Asian Development Bank (ADB), , 2018.

44 Ibid.


However, in order to result in a positive outcome for workers and businesses alike in the midst of these geographically differentiated shifts, lifelong learning and national reskilling and upskilling plans for countries at every stage of economic development are paramount. Part 2 of this report offers a deeper look at technology, jobs, tasks and skills trends within different regions and countries through distinct Country and Regional Profiles. They are intended as a practical guide to exploring these issues in greater granularity and identifying opportunities for countries to build up their future talent pool in a targeted manner. The information provided might also prove useful to evaluate shifting comparative advantage due to new technologies that might affect future company and industry location decisions in relation to various countries in question.

Some of the most frequently cited job roles expected to experience an increase in demand across the geographies covered by the report over the 2018–2022 period—as highlighted by surveyed employers with operations in the respective country or region—include Software and Applications Developers, Data Analysts and Scientists, as well as Human Resources Specialists, Sales and Marketing Professionals and specialized Sales Representatives in virtually all world regions. Region-specific roles expected to be in demand include Financial and Investment Advisers in East Asia and the Pacific and Western Europe; Information Security Analysts in Eastern Europe; Assembly and Factory Workers in Latin America and the Caribbean, Middle East and North Africa, South Asia and Sub-Saharan Africa; and Electrotechnology Engineers in North America.

Crucial to taking advantage of these emerging job creation opportunities across countries and regions will be the existence of a well-skilled local workforce and of national reskilling and upskilling ecosystems equipped to support local workers to keep abreast of technological change and shifting skills needs. As discussed in the section The Reskilling Imperative (see Figure 7), across all countries and regions, employers surveyed for this report expect that significant reskilling will be needed by a large share of the global workforce over the 2018–2022 period. The expected average timeframe required to retrain or upskill affected workers—either in order to equip the country’s workforce with the skills needed to seize new opportunities created by the trends and disruptions experienced by businesses operating in the country in question, or in order to avoid losing competitiveness due to the obsolescence of the workforce’s existing skillsets——ranges from 83 day for companies located in Switzerland to 105 days for companies located in France (Figure 11).

For governments and businesses alike, there is a significant opportunity in strengthening cross-sectoral multistakeholder collaboration to promote corporate reskilling and upskilling among employers in affected countries and regions. Responses by the companies surveyed for this report indicate that, currently, employers expect to primarily seek out the support of their own internal departments as well as private training providers to deliver required retraining and upskilling programmes over the 2018–2022 period. In contrast, across many regions, the least sought-after partners are local education institutions, government programmes and labour unions. This somewhat narrow field of envisaged collaboration partners highlights both an opportunity and a clear need for expanding the range of creative and innovative multistakeholder solutions.

A Look to the Recent Past

In Collaboration with LinkedIn

While the Future of Jobs Survey is designed to look to the near-term future based on the views of the leaders shaping the decisions affecting the future of work, it is equally important to develop a clear sense of recent trends and consider their projections into the future. The World Economic Forum’s data collaboration with LinkedIn helps trace trends in hiring for a range of roles across the period 2013–2017. This data reveals the recent past and the adaptation that has already occurred across roles, impacting the lives and livelihoods of a variety of professionals.

An average rate of change was calculated to reveal the share of hiring for each role from LinkedIn’s 653 codified occupations. LinkedIn analysts expressed the monthly hires of any one job as a proportion of all hires across jobs in each relevant industry within any one calendar month. A linear regression line was fitted to aggregate the generalized trend and to reveal multi-year trends that point to the prioritization of hiring across industries. The resulting lists of roles and scale of change are featured in Figures 9 and 10 and reveal, across industries and geographies, the roles that in the aggregate experienced the greatest upward or downward trend in demand from 2013–2017. The trends highlight business prioritization of new hires, namely the roles which employers believed to be the most appropriate investments to prepare their enterprises for success over the relevant period.

The data reveals that the Basics and Infrastructure industry has experienced a boom in real estate brokerage hires, but a decreasing relative demand for engineering roles and for technicians of various kinds. In the Consumer industry, the demand for Sales Managers was outpaced by demand for Marketing Managers and Software Engineers, while the inverse was true for the Energy industry cluster, where the demand for Managerial and Sales personnel has outpaced demand for Technicians and Engineers. A similar trend can be observed in the Information and Communication Technology industry. Here, relative demand for Systems Administrators has been outpaced by an increase in hires specializing in Experience Design and Marketing. In the Healthcare sector, more specialized roles in nutrition and mental health have experienced rising demand in contrast to generalist roles such as Nursing staff or Medical Officers. A slowdown in hiring trends within the Professional Services sector appears to have distinctively impacted creative, editorial and journalistic roles, all reflecting recent disruptions to the publishing industry. A downward trend among the hiring profile of journalistic professions has seen a matching increase in new hires across broader content writing roles.

Across all regions, digital, marketing and talent-related professions dominate the list of roles that have experienced upward hiring trends alongside marketing specialists, and professionals specializing in software engineering, Data Analysts, User Experience Designers and Human Resources Specialists.

The East Asia and the Pacific region has experienced falling demand for more traditional technical professions such as Engineering, and that trend is mirrored in the Middle East and North Africa region. In a similar fashion, historic hiring trends reveal a decline in hires of technical professions, such as Database Administrators and Electrical Engineers in South Asia. The Latin America and Caribbean and Sub-Saharan Africa regions saw a decline in new hires into roles focused on accounting, administrative activities and in supply chain specialization. Finally, Western Europe has experienced a slowdown in the relative hiring of creative professionals, reflecting recent disruptions in the publishing industry.

Figure 9: Top ten most emerging and declining roles between 2013–2017 as observed in hiring trends, by industry (rate of change)

Figure 10: Top ten most emerging and declining roles between 2013–2017 as observed in hiring trends, by region (rate of change)


The new labour market taking shape in the wake of the Fourth Industrial Revolution holds both challenges and opportunities. As companies begin to formulate business transformation and workforce strategies over the course of the 2018–2022 period, they have a genuine window of opportunity to leverage new technologies, including automation, to enhance economic value creation through new activities, improve job quality in traditional and newly emerging occupations, and augment their employees’ skills to reach their full potential to perform new high value-added work tasks, some of which will have never before been performed by human workers. The business case for such an ‘augmentation strategy’ is becoming increasingly clear—and, we expect, will receive progressively more attention over the coming years, including through upcoming work by the World Economic Forum’s Centre for the New Economy and Society.

At the same time, technological change and shifts in job roles and occupational structures are transforming the demand for skills at a faster pace than ever before. Therefore, imperative for achieving such a positive vision of the future of jobs will be an economic and societal move by governments, businesses and individuals towards agile lifelong learning, as well as inclusive strategies and programmes for skills retraining and upgrading across the entire occupational spectrum. Technology-related and non-cognitive soft skills are becoming increasingly more important in tandem, and there are significant opportunities for innovative and creative multistakeholder partnerships of governments, industry employers, education providers and others to experiment and invest in new types of education and training provision that will be most useful to individuals in this new labour market context.

As this new labour market takes shape over the 2018–2022 period, governments, businesses and individuals will also find themselves confronted with a range of wholly new questions. For example, as employment relationships increasingly shift towards temporary and freelancing arrangements, how can we ensure that individuals receive the support and guidance they need to acquire the right skills throughout their working lives? As employers are deconstructing traditional job roles and re-bundling work tasks in response to new technologies, how can they minimize the risks and best leverage new partnerships with resources such as online freelancers and talent platforms?45 And how can they best ensure such task re-bundling does not inadvertently lead to new forms of job polarization through ‘task segregation’, whereby specific groups of workers are disproportionately allocated the most or least rewarding work tasks?46

While it is beyond the scope of this report to attempt to provide comprehensive answers to all of the above questions, a range of immediate implications and priorities stand out for different stakeholders.

For governments, firstly, there is an urgent need to address the impact of new technologies on labour markets through upgraded education policies aimed at rapidly raising education and skills levels of individuals of all ages, particularly with regard to both STEM (science, technology, engineering and mathematics) and non-cognitive soft skills, enabling people to leverage their uniquely human capabilities. Relevant intervention points include school curricula, teacher training and a reinvention of vocational training for the age of the Fourth Industrial Revolution, broadening its appeal beyond traditional low- and medium-skilled occupations.47 Secondly, improvements in education and skills provision must be balanced with efforts on the demand side. Governments can help stimulate job creation through additional public investment as well as by leveraging private investments through blended finance or government guarantees. The exact nature of desirable investments will vary from country to country. However, over the coming years, there is enormous scope and a clear unmet need in creating the hard and soft infrastructure to power the Fourth Industrial Revolution—from digital communication networks to renewable and smart energy grids to smart schools and hospitals to improved care homes and childcare facilities.48 Thirdly, to the extent that new technologies and labour augmentation will boost productivity, incomes and wealth, governments may find that increased tax revenues provide scope to enhance social safety nets to better support those who may need support to adjust to the new labour market. This could be achieved through reforming and extending existing social protection schemes, or through moving to a wholly new model such as the idea of basic income and basic services. Learning from pilot schemes of this kind—in addition to those currently underway in places such as the Netherlands, various American and Canadian states, Kenya, India and Brazil—will be critical for all governments over the course of the 2018–2022 period.49

For industries, firstly, it will pay to realize that—as competition for scarce skilled talent equipped to seize the opportunities of the Fourth Industrial Revolution intensifies and becomes more costly over the coming years—there is an opportunity to support the upskilling of their current workforce toward new (and technologically reorganized) higher-skilled roles to ensure that their workforce achieves its full potential. Our findings indicate that, to date, many companies intend to mostly limit their skills training provision over the 2018–2022 period to employees performing today’s in-demand job roles, rather than thinking more long-term and creatively. Clearly, a more inclusive and proactive approach will be needed—to both increase the availability of future skills and address impending skills scarcity, and to enable a wider range of workers to share in the gains from new technologies and work more effectively with them through skills augmentation. Secondly, the need to ensure a sufficient pool of appropriately skilled talent creates an opportunity for businesses to truly reposition themselves as learning organizations and to receive support for their reskilling and upskilling efforts from a wide range of stakeholders. One promising model involves new forms of professional skills certification similar to existing schemes delivered by a range of companies in the information technology sector. By establishing objective and marketable credentials for a large variety of emerging job roles, such schemes could help improve the focus of corporate training programmes, increase labour market flexibility, and create clear skills and performance measures to help employers screen candidates and certified workers to command skills premiums.50 Thirdly, with the increasing importance of talent platforms and online workers, conventional industries, too, should be thinking strategically how these action items could be applied to the growing ‘gig’ and platform workforces as well.51

For workers, there is an unquestionable need to take personal responsibility for one’s own lifelong learning and career development. It is also equally clear that many individuals will need to be supported through periods of job transition and phases of retraining and upskilling by governments and employers. For example, lifelong learning is becoming a rich area of experimentation, with several governments and industries looking for the right formula to encourage individuals to voluntarily undergo periodic skills upgrading.52 Similarly, while a fully-fledged universal basic income may remain politically and economically unfeasible or undesirable over the 2018–2022 period, some variants or aspects of the idea—such as providing a ‘universal lifelong learning fund’ for individuals to draw on as needed—might receive increasing attention over the coming years.53 Solutions are likely to vary by country and to depend on local political, economic and social circumstances.

Ultimately, the core objective for governments, industries and workers alike should be to ensure that tomorrow’s jobs are fairly remunerated, entail treatment with respect and decency and provide realistic scope for personal growth, development and fulfilment.54 It is our hope that this new edition of the World Economic Forum’s Future of Jobs Report provides both a call to action and a useful tool for proactively shaping the future of jobs to realize this vision.

45 Jesuthasan, “You may not be a disrupter, but you might find opportunities in the gig economy”.

46 Chan, Curtis and Michael Anteby, “Task Segregation as a Mechanism for Within-job Inequality: Women and Men of the Transportation Security Administration”, , vol. 61, no. 2, 2016, pp. 184–216.

47 The Economist Intelligence Unit and ABB,, 2018.

48 Bain & Company,; PwC,

49 PwC, .

50 Bain & Company,.

51Taylor, Matthew, , Report for the UK Government, 2017.

52 “Singapore, for example, is experimenting with funding ‘individual learning accounts’, which adults use to support training courses throughout their lives. Germany’s Federal Ministry of Labour and Social Affairs is examining a similar scheme, as well as a modified form of “employment insurance” to fund skills upgrading throughout people’s lives”; see: The Economist Intelligence Unit and ABB,.

53 PwC, .

54 Taylor, .


References and Further Reading

Abdih, Yasser and Stephan Danninger, What Explains the Decline of the US Labor Share of Income? An Analysis of State and Industry Level Data, IMF Working Paper No. 17/167, International Monetary Fund, 2017.

Accenture, New Skills Now: Inclusion in the Digital Economy, 2017.
———, Creating South Africa’s Future Workforce, 2018.

Acemoglu, Daron, “Labor- and Capital-Augmenting Technical Change”, Journal of the European Economic Association, vol. 1, no.1, 2003, pp. 1–37.

Acemoglu, Daron and Pascual Restrepo, The Race between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment, NBER Working Paper no. 22252, National Board of Economic Research, 2016.

Acemoglu, Daron and Robert Shimer, “Productivity gains from unemployment insurance”, European Economic Review, vol. 44, 2000, pp. 1195–1224.

African Development Bank (AFDB), Asian Development Bank (ADB), European Bank for Reconstruction and Development (EBRD), and Inter-American Development Bank (IDB), The Future of Work: Regional Perspectives, 2018.

Alphabeta, The Automation Advantage: How Australia can seize a $2 trillion opportunity from automation and create millions of safer, more meaningful and more valuable jobs, 2017.

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, Organisation for Economic Cooperation and Development (OECD), 2016.

Asian Development Bank (ADB), Asian Development Outlook 2018: How Technology Affects Jobs, 2018.Autor, David, “Why Are There Still So Many Jobs? The History and Future of Workplace Automation”, Journal of Economic Perspectives, vol. 29, no. 3, 2015, pp. 3–30.

Autor, David, Frank Levy and Richard Murnane, Upstairs, Downstairs: Computer-Skill Complementarity and Computer-Labor Substitution on Two Floors of a Large Bank, NBER Working Paper No. 7890, National Bureau of Economic Research, 2000.

Avent, Ryan, The Wealth of Humans: Work and its Absence in the Twenty-first Century, Penguin, 2016.

Babcock, Linda, et al., “Gender Differences in Accepting and Receiving Requests for Tasks with Low Promotability”, American Economic Review, vol. 107, no. 3, 2017, pp. 714–747.

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