East Asia is a driving force of global economic and technological development. While many of its economies are at the forefront of AI competitiveness in adoption and literacy, they face a shrinking workforce due to an ageing population with declining birth rates.
As part of the broader effort under the AI Opportunity Fund: Asia-Pacific, an initiative led by AVPN with support from Google.org and the Asian Development Bank, a comparative policy study was developed in partnership with the Institute for Future Government to identify effective strategies and lessons to address the growing silver divide across the Asia-Pacific region. The study draws on insights from AVPN’s AI for All landscape report, which finds that mature workers are 1.6 times more likely to express concerns about AI trustworthiness and twice as likely to cite language barriers as a key challenge. We take a closer look at three key markets for this comparative policy study – Japan, South Korea, and Hong Kong.
Our analysis revealed that all three economies recognise the urgency of reskilling older workers, yet each faces unique challenges and requires tailored solutions due to distinct socio-economic contexts.
Challenges
- Japan has the world’s oldest population, with nearly 30% of its population aged 65 and above. Despite multiple government skilling initiatives supported by its strong national vision of Society 5.0, gaps remain between actual training uptake among older workers and policy momentum due to strong cultural resistance and lack of incentives.
- Both South Korea and Hong Kong are classified as super-aged societies, with more than 20% of their populations aged 65 and above, and many older adults retiring early or working in low-income or low-skilled jobs.
- South Korea has the highest poverty rate among older persons in OECD countries. However, the current AI workforce policy lacks maturity and efforts to integrate the ageing population, compounded by structural barriers such as seniority-based pay and insufficient lifelong learning systems, which make hiring older workers relatively expensive and less attractive to employers.
- Hong Kong lacks a dedicated AI-and-ageing policy and limited government support to drive skilling for the older workforce. Gaps in digital literacy and language ability further limit their participation in existing training programmes.
Strategic Recommendations
- Japan: Recommendations include improving its data collection and evaluation processes to enable disaggregated insights, aligning skilling content with relevance, providing support and incentives for the private sector, and enhancing labour market mobility to promote skilling urgency and benefits.
- South Korea: The study recommends establishing a National AI Workforce Development Committee to ensure inter-ministerial coordination, implementing structural reforms to the seniority-based wage system toward a performance-based compensation system, scaling up the creation of community AI learning centres, and developing industry-specific transition programmes based on existing modules. Long-term goals are to develop a unified competency framework, implement outcome-based financing evaluation, and institutionalise lifelong learning.
- Hong Kong: The study advocates a multi-tiered approach across six levels: policy, government, organisational, management, programme, and societal, with urgent priority on establishing a dedicated AI Workforce Development Strategy for the Special Administrative Region to enable cross-bureau coordination and infrastructure investment, thereby promoting community-centric solutions and programmes.
Proactive efforts are urgently needed to reskill and integrate older workers in the AI-driven economy with targeted strategies.
Overall, it highlights the need for effective government coordination in policy design and implementation of AI skilling programmes, structural reforms to modernise outdated labour and compensation frameworks, and nationwide community-based interventions to promote lifelong learning.
The Fund continues to engage policymakers and cross-sector leaders to advance effective reskilling strategies for mature workers, ensuring that no one is left behind in an AI-enabled just transition.
