OCDE - Skills in the AI age No 60

OECD Artificial Intelligence Papers Skills in the AI age No. 60OECD Artificial Intelligence Papers

Skills in the AI age

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SKILLS IN THE AI AGE © OECD 2026

This paper was approved and declassified by the Digital Policy Committee (DPC) on 27 March 2026.

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used in the occupation across all expert responses weighted by the skills or abilities’ importance in the occupation as rated by the ONET database. Occupations are SOC-2 digit (2018). 4 LinkedIn categorises AI skills into two mutually exclusive groups: “AI engineering” and “AI literacy” skills. AI talent refers to “AI engineering” skills. LinkedIn members are considered having an AI talent if they have explicitly added at least two AI engineering skills to their profile an d/or they are (or they have been) employed in an AI job. 5 The AI exposure measure developed by (Felten, Raj and Seamans, 2021 [33]) assesses the extent to which an occupation is likely to be affected by artificial intelligence based on the tasks it involves, rather than on whether AI is currently used in that occupation. The measure links information on AI capabilities with detailed descriptions of occupational tasks from the ONET database. Oc cupations receive a higher exposure score when a larger share of their tasks overlaps with capabilities that current AI systems can perform or support, such as processing text, analysing information, or recognising patterns. Importantly, a high AI exposure score does not imply that workers in these occupations are being rep laced by AI or that they require specialised AI skills. Instead, it indicates that AI has greater potential to transform or augment the way work is performed within those occupations.OECD Artificial Intelligence Papers Skills in the AI age No. 60 As general-purpose technologies like the steam engine and electricity once revolutionised society, artificial intelligence (AI) is likewise doing so today. By enhancing productivity, stimulating economic growth and creating new job opportunities, AI could significantly enhance human work and the labour market. However, AI also presents challenges such as job displacements if the transition to using it is not properly managed. The effects of AI on employment differ across sectors, regions and cities, as well as across skill levels. Adapting to this shift requires developing new skills that align with evolving labour market demands. Policymakers play an essential role in ensuring workers are equipped to thrive in an AI-driven economy. This paper examines how AI is transforming labour markets, shifting skill requirements and the policy responses

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SKILLS IN THE AI AGE © OECD 2026

As general-purpose technologies like the steam engine and electricity on ce revolutionised society, artificial intelligence (AI) is likewise doing so today. By enhancing productivity, stimulating economic growth and creating new job opportunities, AI could significantly enhance human work and the labour market. However, AI also presents challenges such as job displacements if the transition to using it is not properly managed. The effects of AI on employment differ across sectors, regions and cities, as well as across skill levels. Adapting to this shift requires developing new skills that align with evolving labour market demands. Policymakers play an essential role in ensuring workers are equipped to thrive in an AI-driven economy. This paper examines how AI is transforming labour markets, shifting skill requirements and the policy responses needed to harness AI’s transformative potential while mitigating its social and economic risks.

Abstract4 

SKILLS IN THE AI AGE © OECD 2026

The ongoing digital transformation of the economy and society holds many promises to spur innovation,

regions and cities, as well as across skill levels. Adapting to this shift requires developing new skills that align with evolving labour market demands. Policymakers play an essential role in ensuring workers are equipped to thrive in an AI-driven economy. This paper examines how AI is transforming labour markets, shifting skill requirements and the policy responses needed to harness AI’s transformative potential while mitigating its social and economic risks.

and the policy responses needed to harness AI’s transformative potential while mitigating its social and economic risks.

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SKILLS IN THE AI AGE © OECD 2026

The ongoing digital transformation of the economy and society holds many promises to spur innovation, generate efficiencies and improve services, and in doing so boost growth. Digital technologies empower people by increasing access to information and enabling new forms of social engageme nt. Yet such benefits come with other challenges as digital transformation changes the nature and structure of organisations, markets and communities, and raises concerns about equity and inc lusion. Realising the opportunities and addressing the challenges is not automatic and may require policy action to make digital transformation boost growth and improve well-being. The OECD-Korea Digital Society Initiative (DSI), under the auspices of the OECD Digital Policy Committee (DPC) and supported by Korea, aims to help advance the DPC’s work on the societal aspects of digital transformation, including its implications for human rights, by integrating relevant ex pertise from across the DPC and its data infrastructures. The DSI provides insights into the impacts of dig ital transformation and digital technology development on society, and a venue for countries to discuss, exchange and explore policy case studies on related issues. The DSI focuses on three priority areas: digital inclusion and divides; safety; and trust. These themes were chosen as key areas to advance individu al and societal well-being in today’s highly digital societies. This paper represents an output of the DSI. It contributes to a better understanding of key trends in the digital transformation of societies across OECD Member countries and partner economies and it identifies innovative policy practices to maximise the opportunities of digital technologies for people and society and to minimise the related risks. This paper was written by Elif Köksal-Oudot under the guidance of Molly Lesher and the direction of Audrey Plonk and Jerry Sheehan . Statistical expertise from Giorgia Bergamo and Bénédicte Rispal is gratefully

to minimise the related risks. This paper was written by Elif Köksal-Oudot under the guidance of Molly Lesher and the direction of Audrey Plonk and Jerry Sheehan . Statistical expertise from Giorgia Bergamo and Bénédicte Rispal is gratefully acknowledged. The paper benefited from feedback from Stijn Broecke, Andrew Paterson, Glenda Quintini, Angelica Salvi Del Pero and Lea Samek. Mark Foss, Andreia Furtado and Alice Weber provided editorial and communication support. Acknowledgements 5

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Table of contents Disclaimers 2

Abstract 3 Acknowledgements 4 Reader’s guide 7 Acronyms 7 Abbreviations 8 Executive summary 9 Main findings 9 1 Introduction 11 2 AI has a transformative impact on businesses, work and digital societies 12 Firm-level AI adoption has widespread implications for society 12 AI is transforming jobs and labour markets 14 Jobs with greatest exposure to AI are not necessarily those with a high risk of automation 14 3 Individuals need a wide range of skills to thrive in digital societies 18 A mix of foundational, ICT and complementary skills are needed to thrive in digital environments 18 AI skills are in high demand, but workers with AI skills are still a small part of the overall workforce 19 Bridging skills gaps is an important societal imperative 20 4 The role of policies to shape skills for the AI age 22 Investing in the quality, equity and labour market relevance of education and training systems 22 Training ICT professionals through both formal education and lifelong learning 23 Encouraging employer-led training 24 Promoting AI literacy 26 Providing tailored support for displaced workers 27 Ensuring the right mix of skills for all 28 5 Conclusion 29 References 30 Notes 346 

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FIGURES

Promoting AI literacy 26 Providing tailored support for displaced workers 27 Ensuring the right mix of skills for all 28 5 Conclusion 29 References 30 Notes 346 

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FIGURES Figure 1. Adoption of AI technologies in businesses has been increasing 13 Figure 2. High-skill, white collar occupations are among those with the highest exposure to AI 15 Figure 3. The occupations most at risk of automation are different than those most exposed to AI 16 Figure 4. Economies are competing for AI talent 19 Figure 5. In some countries, almost a third of job vacancies are highly exposed to AI 20 BOXES Box 1. Korea’s “Artificial Intelligence & Digital (AID) 30+” project 24 Box 2. Germany’s funding of continuing vocational training and training (CVET) for employees 25 Box 3. Estonia’s national “AI Leap” initiative 27 Box 4. Canada’s “AI4Good Lab” programme 28 7

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Acronyms AI Artificial intelligence AID Artificial Intelligence and Digital (Korea) AZAV Accreditation and Approval Ordinance for Employment Promotion (Germany) CPF Individual Learning Account (France) CPIA Provincial Centres for Adult Education (Italy) CVET Continuing vocational education and training (Germany) EU European Union ICT Information and communication technologies ISCO International standard classification of occupations SMEs Small and medium-sized enterprises GenAI Generative artificial intelligence MOOCs Massive open online courses OECD Organisation for Economic Co-operation and Development PIAAC Programme for the International Assessment of Adult Competencies (OECD) PISA Programme for International Student Assessment (OECD) VET Vocational education and training

Reader’s guide8 

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Abbreviations This report uses ISO codes for countries and economies in figures. ARG Argentina

PISA Programme for International Student Assessment (OECD) VET Vocational education and training

Reader’s guide8 

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Abbreviations This report uses ISO codes for countries and economies in figures. ARG Argentina AUS Australia AUT Austria BEL Belgium BGR Bulgaria BRA Brazil CAN Canada CHE Switzerland CHL Chile CRI Costa Rica CZE Czechia DEU Germany DNK Denmark ESP Spain EST Estonia FIN Finland FRA France GBR United Kingdom GRC Greece HKG Hong Kong (China) HRV Croatia HUN Hungary IDN Indonesia IND India IRL Ireland ISL Iceland ISR Israel ITA Italy JPN Japan KOR Korea LTU Lithuania LUX Luxembourg LVA Latvia MEX Mexico NLD Netherlands NOR Norway NZL New Zealand POL Poland PRT Portugal ROU Romania SAU Saudi Arabia SGP Singapore SVK Slovak Republic SVN Slovenia SWE Sweden TUR Republic of Türkiye URY Uruguay USA United States ZAF South Africa 9

SKILLS IN THE AI AGE © OECD 2026

Artificial intelligence (AI) is emerging as a transformative general-purpose technology, reshaping economies and societies in ways comparable to past industrial revolutions. By en hancing productivity, improving decision making and enabling innovation, AI holds significant potential to boost economic growth and improve working conditions. At the same time, its diffusion raises concer ns about labour market disruptions, widening inequalities and uneven access to opportunities. In this context, ensuring that individuals and economies are equipped with the right skills is critical to harness AI’s benefits while managing its risks. AI adoption by firms has accelerated rapidly in recent years, driven in part by the emergence of generative

disruptions, widening inequalities and uneven access to opportunities. In this context, ensuring that individuals and economies are equipped with the right skills is critical to harness AI’s benefits while managing its risks. AI adoption by firms has accelerated rapidly in recent years, driven in part by the emergence of generative AI tools. Businesses increasingly use AI technologies to automate routine tasks , optimise resource allocation and improve the quality of goods and services. These developments can raise productivity and create more engaging and higher-value work for employees. However, adoption remains unev en across firms, sectors and countries. Larger firms and younger, more innovative enterprises ten d to lead in AI uptake, while small and medium-sized enterprises face barriers related to cost, infrastructure and skills shortages. Without targeted policy interventions, these disparities risk reinforcing existing productivity gaps and limiting the diffusion of AI benefits across the economy. This paper first sheds light on the transformative impacts of AI on busi nesses, work and digital societies. It then outlines the skills needed to prosper in the AI age. Finally, it discusses the role of policies to help ensure that workers have the right mix of skills today and in the future. Main findings AI adoption is accelerating, with differences across firms • AI uptake is rising rapidly, increasing from around 7% to 20% of firms b etween 2021 and 2025 in OECD countries, driven in part by the diffusion of generative AI tools. • Larger firms and start-ups are more likely to adopt AI due to greater financial resourc es and innovation capacity, respectively. • Small and medium-sized enterprises (SMEs) face persistent barriers to AI uptake, including costs, lack of infrastructure and shortages of skilled workers. • Skills shortages are a key constraint on AI diffusion, ranked among the top barriers to adoption by firms. AI is transforming jobs, but not necessarily destroying them • AI affects labour markets through three main channels: i) automation of existing tas ks, ii) creation of new tasks and occupations and iii) improving productivity. These effects coexis t, and the net impact on employment depends on their relative balance.

firms. AI is transforming jobs, but not necessarily destroying them • AI affects labour markets through three main channels: i) automation of existing tas ks, ii) creation of new tasks and occupations and iii) improving productivity. These effects coexis t, and the net impact on employment depends on their relative balance. • Evidence suggests AI often complements rather than substitutes human labour, c ontributing to productivity gains and job creation. • However, job displacement remains a risk, particularly for workers in routine and repetitive roles. Executive summary10 

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Exposure to AI differs from risk of automation • High-skill occupations are the most exposed to AI, including managers, profession als and engineers. However, these occupations are less likely to be automated, as they rely on non-routine cognitive and social skills. • In contrast, lowand middle-skill jobs face higher automation risks, particularly in sectors involving routine manual or cognitive tasks. • In 2022-2024, around one-quarter of workers were already exposed to generative AI, a nd this share is expected to grow significantly. Individuals need a wide range of skills to thrive in digital societies • Foundational skills (literacy, numeracy, scientific knowledge) enable al l people to participate in a digital economy and society. • Information and communication technologies (ICT) skills (basic to advanced technic al competencies) help workers meet evolving job requirements and thrive in the digital age. Advanced AI skills (e.g. machine learning, data science) are in high demand, but workers with such skills remain rare (around 1% of the workforce). • Complementary skills such as critical thinking, creativity, and collaborati on enable highperformance work practices and a strong ability to continue learning. They become increasingly important as they enable effective interaction with AI systems and adaptation to changing tasks. Governments can help shape skills for the AI age To make the most of benefits from AI technologies while mitigating the risks, go vernments must put into action agile policies that work in tandem as follows:

important as they enable effective interaction with AI systems and adaptation to changing tasks. Governments can help shape skills for the AI age To make the most of benefits from AI technologies while mitigating the risks, go vernments must put into action agile policies that work in tandem as follows: • Strengthen education and training systems by improving quality, equity and labour market relevance of education and integrating AI literacy, digital skills and critical thinking across curricula; • Expand lifelong learning opportunities by promoting continuous upskilling and reskilling across the life course by developing flexible, modular and online training pathways and str engthening recognition of prior learning systems; • Develop the ICT and AI talent pipeline by expanding formal education programmes in AI and digital fields, providing short, targeted reskilling programmes for adults and aligning tra ining provision with evolving labour market needs; • Promote AI literacy for all by equipping workers with basic skills to use, understand and critically assess AI and broadening access to AI learning beyond specialists; • Encourage employer-led training by supporting firms through financial incentives, subsidies and co-financing schemes, fostering partnerships between employers and education providers and aligning workplace training with technological change; and • Strengthen policy co-ordination and partnerships by fostering collaboration between governments, industry and education systems and using labour market data and skills forecasting to guide policy. 11

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Artificial intelligence (AI) 1 is reshaping economies and societies, much like transformative technol ogies such as the steam engine and electricity did in earlier generations. As a general-purpose technology, AI has the potential to boost productivity, drive economic growth, create new jobs and en hance the work of people (Calvino, Haerle and Liu, 2025 [1]). At the same time, AI raises the risk of job displacement and widening existing disparities if the transition to using it is not managed effectively (OECD, 2023[2]). The impact of AI on jobs varies across sectors, occupations and skills. Some workers benefit from AI’s

widening existing disparities if the transition to using it is not managed effectively (OECD, 2023[2]). The impact of AI on jobs varies across sectors, occupations and skills. Some workers benefit from AI’s ability to automate routine tasks (e.g. reducing the time to accomplish tasks with the same or even higher quality), allowing them to focus on higher-value tasks that cannot yet be automated. In other cases, AI may replace jobs entirely, particularly those involving a high degree of predicta ble and repetitive tasks. Importantly, the widespread availability of generative AI (GenAI) tool s may considerably alter the way in which workers undertake different tasks. Having the skills to adapt to changing tasks and jobs is a crucial element of being able to thrive in the world of work in the AI age. With the ri ght skills, workers stand to benefit from emerging job opportunities created by AI, provided the risks are addressed in tande m. In such a heavily data-driven world, the pace of technological change is fast and often disruptive. In this context, policymakers have a responsibility to help equip workers with the sk ills needed to thrive in their jobs and in society more broadly . This paper first sheds light on the transformative impact of AI on businesses, work and digital societies. It then outlines the skills needed to prosper in the AI age. Finally, it discusses the role of policies to help ensure that workers have the right mix of skills today and in the future. 1 Introduction12 

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AI adoption by firms can help reduce costs and boost productivity, supporting inc reased competitiveness. However, it also has far-reaching societal implications for individuals as consumers and workers. Firm-level AI adoption has widespread implications for society AI adoption by firms can transform the approach to operational efficiency, decision-making processes and consumer engagement. AI technologies, including machine learning, natural lang uage processing, computer vision and predictive analytics, enable businesses to automate routine ta sks, optimise resource allocation and enhance productivity (Brynjolfsson, 2017[3]; Calvino and Fontanelli, 2023[4]; Filippucci et al.,

computer vision and predictive analytics, enable businesses to automate routine ta sks, optimise resource allocation and enhance productivity (Brynjolfsson, 2017[3]; Calvino and Fontanelli, 2023[4]; Filippucci et al., 2024[5]). For example, AI-powered predictive maintenance is transforming the manufacturing industry by reducing downtime, lowering maintenance costs and enhancing operational efficiency (Lalwani, 2025[6]). AI can also help companies improve product or service quality (OECD, 2023[2]), enabling workers to benefit simultaneously through improved job quality and satisfaction. Indeed, AI could reduce or eliminate dangerous or tedious tasks, and create more complex and interesting ones instead. It c an boost worker engagement, giving them greater autonomy and even improving their mental health. S ome workers may also benefit from higher wages if there is a higher demand for specific skills on the job market. Additionally, AI has proven to be instrumental in enhancing workplace wellness and ergonomics (Fiegler-Rudol et al., 2025[7]). AI technologies can automate physically demanding and repetitive tasks, reducing the risk of burnout and improving employee well-being (García-Madurga et al., 2024 [8]). Recent evidence also shows that GenAI tools could significantly enhance productivity , both at individual and organisational levels, with relevant aggregate implications (Calvino, Reijerink and Samek, 2025[9]). In OECD Member countries with available data, businesses have significantly increased their uptake of AI in recent years. As measured in ICT usage surveys, use of AI in these busines ses grew from around 7% to 20% between 2021 and 2025 (Figure 1). This increase is likely driven by the adoption of “generalpurpose” GenAI tools, such as ChatGPT and Copilot, which were made available as of 2022.

2 AI has a transformative impact on businesses, work and digital societies 13

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Figure 1. Adoption of AI technologies in businesses has been increasing

2 AI has a transformative impact on businesses, work and digital societies 13

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Figure 1. Adoption of AI technologies in businesses has been increasing Adoption rates of AI by enterprises with ten employees or more, in the business sector (excluding financial services), 2025 (or most recent)

Note: For Brazil, data refer to 2021 and 2024. For Canada, Japan and Switzerland, data refer to 2021 and 2023. For Korea, data refer to 2021 and 2024 with a change in the questionnaire structure in 2022.

Source: OECD (2026[10]), ICT Access and Usage (dataset),

https://oe.cd/dx/ict-access-usage. AI uptake in firms differs considerably by age, sector and size. Younger firms, including start-ups, have a strong tendency to use AI. Indeed, start-ups are often at the forefront of radical innovat ions, especially during the emergence of new technological paradigms such as AI. As a result, the propen sity of young firms to adopt AI often surpasses that of older firms (Calvino and Fontanelli, 2023 [4]). A recent OECD taxonomy also reveals significant heterogeneity across sectors with r espect to AI human capital, AI innovation, and exposure to and use of AI (Calvino and Fontanelli, 2023 [4]). Sectors such as information technology ( IT) services score high along all the dimensions considered. Others, such as pharmaceuticals, exhibit considerably more heterogeneity (high AI human capital but low AI innovation). Without targeted and effective support to develop the skills needed to work with AI, workers and businesses will not be able to seize its benefits, while disparities in job opportunities, job quality, wages and productivity may widen. With respect to size breakdowns, larger firms with greater financial and technical resources appear more likely to adopt AI (Calvino and Fontanelli, 2023[4]). SMEs often report barriers related to cost,

may widen. With respect to size breakdowns, larger firms with greater financial and technical resources appear more likely to adopt AI (Calvino and Fontanelli, 2023[4]). SMEs often report barriers related to cost, expertise and infrastructure among the reasons for not adopting AI technologies . Lack of skills is the second most common barrier to adoption of AI reported by firms in finance and manufacturing (after costs) in the OECD AI surveys of employers and workers (OECD, 2023 [2]). Similarly, half of SMEs not using GenAI tools report lack of skills as a barrier (OECD, 2025 [11]). Other major deterrents include concerns about legal and regulatory issues (e.g. concerns about ineffective protection and enforcement of copyright and other intellectual property), data privacy, and manipulated and deliberately mislea ding content online (Bianchini and Lasheras Sancho, 2025[12]).

0 10 20 30 40 50 % 2025 202114 

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AI is transforming jobs and labour markets AI is increasingly recognised as a transformative force in labour markets, dr iving significant shifts in job creation, skills demand and overall workforce dynamics. While concerns about job displacement persist, research suggests that AI also creates numerous opportunities for employment growth and ec onomic resilience. One study, for example, argues that AI technologies can lead to net job gains by complementing human labour rather than substituting it, thereby creating new tasks and industries (OECD, 2023 [2]). Building on research by Lane and Saint-Martin (2021 [13]) within the OECD’s Artificial Intelligence in Work, Innovation, Productivity and Skills (AI-WIPS) programme, OECD (2023 [2]) identifies different types of impacts of AI on employment. In one scenario, AI affects labour demand by automati ng certain tasks, complementing humans in completing existing tasks but also creating new ones. When AI automates tasks previously done by humans, it may replace human labour. In parallel, AI may create new tasks that require

impacts of AI on employment. In one scenario, AI affects labour demand by automati ng certain tasks, complementing humans in completing existing tasks but also creating new ones. When AI automates tasks previously done by humans, it may replace human labour. In parallel, AI may create new tasks that require human labour, leading workers to undertake alternative tasks compared to previous ones. Finally, A I may complement workers, uniformly improving human productivity in all assigned tasks. In this scenario, AI neither replaces workers in the completion of tasks nor creates new tasks; it allows workers to perform the same tasks more efficiently. The three channels are not mutually exclusive, and all may be present at the same time. The implications for labour demand depend on which effects dominate. The creati on of new tasks should lead to increases in labour demand. In particular, the creation of new tasks results in a reinstatement effect that creates new jobs and leads to more employment (OECD, 2023 [2]). These jobs can come from anywhere, but literature usuall