Key Details
The OECD Economics Department Working Paper, A Potential Boost from AI in Ageing Societies: Early Insights, examines how artificial intelligence could mitigate the economic effects of population ageing while identifying the institutional and labour-market conditions needed to realise these benefits.
Theme | Key Finding | Why It Matters |
|---|---|---|
Demographic ageing | Shrinking working-age populations are expected to slow long-term economic growth. | Productivity gains will become increasingly important. |
AI exposure | AI exposure follows a lifecycle pattern—automation is higher for younger workers, while augmentation is more common among older workers. | AI affects different age groups in different ways. |
Labour mobility | Job mobility and participation in training decline with age. | Older workers may find it harder to adapt to AI-driven changes. |
Business dynamism | Ageing societies tend to experience fewer new firms and slower technology diffusion. | Weaker innovation ecosystems could slow AI adoption. |
Policy priorities | Lifelong learning, labour-market flexibility and technology adoption are essential complements to AI. | Institutions will shape AI’s economic impact. |
Summary
Can AI Counter Demographic Ageing?
The OECD working paper, A Potential Boost from AI in Ageing Societies: Early Insights, examines whether artificial intelligence can help offset one of the defining economic challenges facing advanced economies: ageing populations. It concludes that AI has significant potential to raise productivity and ease labour shortages, but technology alone cannot compensate for demographic change. The scale of future gains will depend on how effectively workers, firms and institutions adapt.
AI Affects Workers Differently Across Their Careers
Using data from the OECD’s Programme for the International Assessment of Adult Competencies (PIAAC), the paper finds that AI exposure follows an inverted U-shaped lifecycle pattern. Younger workers are more exposed to automation, as they often perform routine, codifiable tasks, while older workers are more likely to experience augmentation, where AI complements judgement, experience and decision-making rather than replacing them. The report argues that understanding these differences is essential for designing effective workforce policies.
Institutions Will Determine Productivity Gains
The paper identifies several structural barriers that could limit AI’s economic benefits in ageing societies. Labour mobility declines with age, participation in training falls despite rising skill requirements, and ageing economies often experience weaker business dynamism, lower rates of firm entry and slower technology diffusion. It also highlights a longer-term risk that extensive automation of entry-level work could reduce opportunities for younger workers to acquire practical skills and workplace experience, potentially weakening future productivity.
Technology Alone Cannot Offset Demographic Change
The report concludes that AI’s long-term contribution to economic growth will depend on complementary policy reforms rather than technological progress alone. Lifelong learning systems, flexible labour markets, competitive business environments and stronger innovation ecosystems will determine whether ageing societies can translate AI adoption into sustained productivity gains and higher living standards.
What is AI Exposure?
AI exposure measures the extent to which the tasks performed in a job are likely to be affected by artificial intelligence.
Automation exposure refers to tasks that AI can perform or replace with limited human intervention, typically routine or highly codified activities.
Augmentation exposure refers to tasks where AI complements human capabilities by supporting judgement, decision-making, creativity or problem-solving rather than substituting for workers.
Policy Relevance
Although India currently has a younger workforce than most OECD economies, population ageing is expected to accelerate over the coming decades, making early investment in AI-ready skills and labour-market adaptation increasingly important.
The findings reinforce the need for the IndiaAI Mission to promote AI applications that augment workers’ productivity alongside automation, particularly in sectors such as healthcare, manufacturing, education and public services.
Lifelong learning and mid-career reskilling will become increasingly important as AI changes occupational requirements, extending skill development beyond formal education and early-career training.
The report highlights the importance of preserving pathways for entry-level learning as AI automates routine cognitive tasks, ensuring younger workers continue to acquire workplace experience and tacit knowledge.
India’s long-term AI strategy should be supported by competitive markets, business innovation and labour mobility so that productivity gains can spread across firms rather than remaining concentrated in a few sectors or enterprises.
As demographic and technological transitions increasingly interact, AI policy, labour policy and skill development strategies will need closer coordination rather than evolving as separate policy domains.
Follow the Full Report Here: OECD Economics Department Working Paper No. 1870 – A Potential Boost from AI in Ageing Societies: Early Insights