Asia’s Graying Workforce: Can AI be the Silver Lining?

An elderly woman seeks help with her bills—highlighting the urgent need and opportunity to empower older adults through accessible digital tools and AI-driven support systems. Photo credit: ADB.

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AI and digital innovation can help extend working lives, strengthen pensions, and build more resilient systems for the aging population.

Introduction

Asia and the Pacific faces a dual challenge: rapid population aging and the disruptive impact of artificial intelligence (AI). By 2050, 81 million—one in five people—will be 65 or older, straining pension systems already under pressure.

Currently, 40% of older adults lack access to any form of pension. Meanwhile, the rise of generative AI and automation could worsen pension challenges by displacing workers and reducing the pool of contributors. In East Asia and the Pacific, up to 90% of jobs could face AI displacement. This convergence of aging and technological disruption calls for urgent policy actions and better data to guide responses.

The Demographic Shift and Growing Pension Pressures

Although the region’s total population continues to grow, the share of children has nearly halved since 1990—signaling fewer young people entering the workforce. The working-age population is projected to level off after decades of increase, while the elderly population is increasing rapidly (Figure 1). By 2050, around 20% of the region’s population will be aged 65 or older, more than double their share in 2020.

Figure 1. Population Distribution by Age Group and Share of Elderly in Asia and the Pacific (1990–2025)

Source: Asian Development Bank estimates using data presented in Table 2.1.3 of Key Indicators for Asia and the Pacific 2025; and data from the United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects 2024.

This demographic deficit—where older adults outnumber working-age individuals—creates serious economic and social challenges. Pension, healthcare, and long-term care systems are under growing strain as demand rises but resources remain limited. With fewer young people joining the workforce, the pool of contributors is shrinking—placing greater fiscal pressure on governments.

Figure 2. Proportion of Population Above Statutory Pensionable Age Receiving Pension in Asia and the Pacific

Notes: Figures shown are based on available data for ADB member economies. Each datapoint corresponds to the latest available data in the presented time period.
Source: Asian Development Bank visualization using data presented in Table 1.1.2 of Key Indicators for Asia and the Pacific 2025.

Only a few economies have achieved 100% pension coverage based on SDG 1.3.1.b, and data gaps make it difficult to assess and address current levels. Effective pension coverage for older persons varies widely: only 34% of economies in Asia and the Pacific have reached full coverage, and limited data availability continues to hinder comprehensive assessment. This is especially alarming, as many economies—despite having smaller elderly populations and larger workforces—rank low in global assessments of retirement income systems.

AI and Automation: A Double-Edged Sword

Generative AI is transforming the job market, affecting both routine and complex tasks across industries and adding complexity to the pension crisis. While AI can augment some occupations, it could also displace many. In East Asia and the Pacific, only 10% of jobs involve tasks complementary to AI—leaving up to 90% at risk of disruption.

As AI adoption grows, displaced workers may turn to informal employment—which already accounts for about 66% of workers in Asia and the Pacific, and even higher among youth (82%) and older adults (83%). These jobs often lack stable income and pension contributions, further eroding retirement system finances. The result is a shrinking pool of contributors and rising number of beneficiaries—intensifying long-term sustainability challenges.

AI’s Potential as a Silver Lining

Despite the risks, AI could present new opportunities for a more inclusive and resilient development. For the graying workforce, AI and digitalization can enhance productivity, support longer working lives, improve pension coverage, and advance health outcomes.

Productivity and work. Automation and robotics can help older workers stay active in physically demanding roles. By taking on routine or strength-intensive tasks, AI allows seniors to focus on higher-value work, reducing fatigue and injury risks. It can also offset age-related physical and cognitive decline by supporting decision-making and enhancing productivity—creating a more inclusive and sustainable work environment.

Health and well-being. AI applications in healthcare—ranging from diagnostics, personalized treatments to efficient care management—can improve health outcomes and support aging populations. Wearables and smart devices assist with health tracking, fall detection, medication reminders, and chronic disease management, promoting independent living and mobility. Virtual assistants, meanwhile, offer companionship and emotional support—helping reduce loneliness, anxiety, and cognitive decline.

Pension systems. AI and digital tools are transforming pension systems. As noted in ADB’s Asian Development Policy Report 2025, digitalization can reduce inequality and expand access to financial systems. Applied to pensions, digital platforms improve efficiency, reduce manual errors, cut costs, and enhance compliance. They also support secure, scalable, and real-time services.

Financial inclusion. Digital finance innovations can extend pension coverage to self-employed and informal workers. Mobile apps and platforms make it easier to access information and manage retirement savings. Personalized pension planning tools can further boost user engagement—helping users understand risk tolerance and make more confident retirement decisions.

Building Smarter Statistical Systems for a Smarter Future

Effective policy responses require reliable data on how AI affects jobs, and which workers are most at risk. However, most labor surveys were developed before the rise of generative AI and lack details on job tasks and skills. Global estimates suggest up to 800 million jobs could be displaced by automation by 2030, but region-specific data for Asia and the Pacific remain limited.

To close these gaps, the Asian Development Bank’s Data Division is working with national statistics offices in Bhutan, Georgia, and the Philippines to collect more detailed data on job tasks and skills. These efforts aim to identify vulnerable groups—particularly older workers—and support more targeted, evidence-based policies.

Strengthening data on aging and productivity
Traditional workforce metrics of workforce participation and productivity no longer capture the realities of aging populations. As older adults increasingly remain in or return to the workforce—whether by choice or necessity, new data are needed to measure health, productivity, and potential for extended working lives. An ADB report estimates that additional work capacity among older adults could yield productivity gains of about 1.5% of gross domestic product.

ADB's technical assistance project, Challenges and Opportunities of Population Aging in Asia: Improving Data and Analysis for Healthy and Productive Aging, addresses these data gaps by developing internationally comparable, panel survey-based databases on aging; and (ii) coordinating cross-country studies to provide governments with useful information toward reforms in health and social security programs.

Household surveys should also incorporate measures of functional capacity and work capability among older adults—similar to the China Health and Retirement Longitudinal Survey (CHARLS) model, a national survey that aims to understand the implications of the country’s rapidly aging population.

Measuring digital literacy and AI readiness
AI adoption depends heavily on digital literacy. Studies have shown that individuals who have higher digital competence are more likely to use and evaluate AI-based technologies. A recent study also shows digital literacy—not age—is the strongest predictor of AI use.

Adoption also varies across industries. In manufacturing, AI uptake is driven by digital skills, company size, and research and development intensity. Firms that are more research-intensive and knowledge-based are more likely to implement AI. In electronics, technology infrastructure and knowledge sharing are key enablers, although privacy and security concerns also influence adoption. Education and healthcare sectors are increasingly embedding AI and digital literacy into the curricula and professional development, reflecting the growing need for sector-specific competencies.

Turning Challenge into Opportunity

Asia’s aging future and the expansion of AI adoption are inevitable. The convergence of demographic deficit and AI advancement presents a challenge for Asia and the Pacific’s pension systems, labor markets, and social protection. Addressing these requires responsive, data-driven policy solutions that strengthen pension models, modernize labor data, and prepare workers through continuous upskilling.

The region is at a critical juncture. Artificial intelligence has the potential to either deepen existing weaknesses of the pension system or serve as a silver lining that transforms demographic challenges into opportunities. However, the window for action is narrowing, and delayed reforms risk turning manageable pressures into more serious challenges that might be significantly harder to solve.

Note: For more related statistics on poverty, refer to ADB's Key Indicators for Asia and the Pacific 2025.

Arturo Martinez, Jr.
Senior Statistician, Economic Research and Development Impact Department, Asian Development Bank

Art Martinez works on poverty measurement theory and Sustainable Development Goals indicator compilation, particularly poverty statistics and big data analytics. Prior to joining ADB, he was a research fellow at the University of Queensland in Australia where he also got his PhD in Social Statistics.

Christian Leny Hernandez
Consultant, Asian Development Bank

Leny Hernandez is a monitoring and evaluation specialist dedicated to advancing development initiatives through data-driven insights. She focuses on evidence-based policymaking and improving data availability to support effective strategies. Her experience includes work with ADB, Department of Economy, Planning, and Development, and United Nations Development Programme. She holds a master’s degree in development studies from the International Institute of Social Studies (Netherlands) and a bachelor's degree in human ecology from the University of the Philippines Los Baños.

Christian Flora Mae Soco
Consultant, Economic Research and Development Impact Department, Asian Development Bank

Christian Flora Mae Soco contributes to research and initiatives focused on gender and poverty. Prior to joining ADB, she worked as a data analyst specializing in health claims data analysis. She holds a Bachelor of Science in Statistics degree from the University of the Philippines Visayas.
 

Mar Andriel Umali
Consultant, Economic Research and Regional Cooperation Department, Asian Development Bank

Mar Andriel Umali is an economics and statistics specialist. He is involved with research on poverty and inequality, gender, and financial inclusion. He completed his PhD in Economics at the Crawford School of Public Policy, Australian National University. 

Mildred Addawe
Consultant, Economic Research and Development Impact Department, Asian Development Bank

Mildred Addawe contributes to research aimed at generating gender statistics and creating granular poverty maps. Before joining ADB, she was a statistical specialist at the Philippine Statistics Authority, where she worked on poverty and human development measurement. She earned her bachelor’s degree from the University of the Philippines Los Baños. 

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