Tech disruption: Will AI take jobs away from Asia's youth?

Jong-Wha Lee

Artificial Intelligence is advancing at a breathtaking pace, and so are fears about its impact on jobs, especially for young people entering the labour market. The tasks generative AI can increasingly perform — writing computer code, summarising documents, analysing data and handling customer inquiries — are precisely those that often provide young workers with their first foothold in the workforce.

However, warnings by tech leaders that entry-level white-collar jobs will be largely wiped out within a few years run well ahead of available evidence. While AI is beginning to affect certain entry-level roles, its impact remains limited and uneven, with few signs of economy-wide displacement.

In the US, for example, a recent study found no broad decline in employment associated with AI exposure. What did fall was employment among 22-25-year-olds in highly exposed occupations: it now stands 19% below where it would be if it had kept pace with young workers in less-exposed sectors. Weaker hiring, rather than layoffs, drove this shift.

Even this evidence should be interpreted cautiously. While entry-level hiring in AI-exposed occupations began weakening around 2022, before ChatGPT was released to the public, this probably reflected rising interest rates, post-pandemic adjustments and remote work trends rather than the rise of AI, which had limited capabilities at the time.

Moreover, though the decline in entry-level hiring by tech firms since 2024 might be attributable to AI, demand for tech workers outside the technology sector remains strong. Where AI usage primarily complements workers rather than substituting for human labour, employment levels remain stable or are actively rising.

More broadly, recent US data do not point to a youth-employment crisis. The unemployment gap between 20-24-year-olds and the overall workforce is near a multi-decade low. In short, not every job is exposed to AI, and exposure does not automatically imply displacement.

This is even more evident outside the US. A recent World Bank study found that in high-income countries, online job postings in occupations vulnerable to AI substitution declined by 5.8% relative to less-substitutable roles since ChatGPT was launched. In middle- and low-income countries, the decline was statistically insignificant. Lower AI adoption, weaker digital infrastructure and a larger share of manual work limit AI's immediate potential for job displacement in developing economies.

Across Asia, AI's labour-market effects differ sharply from country to country. In South Korea, youth employment fell disproportionately in industries with high AI exposure between 2022 and 2025, while employment among workers in their 50s increased. But as in the US, it is impossible to isolate AI's role from broader economic, demographic and structural changes.

The ASEAN economies face moderate exposure to AI. The International Labour Organisation estimates that occupations with more than minimal exposure to generative AI accounted for 22.9% of ASEAN employment in 2025, though only 3.3% of the workforce was in jobs with the highest exposure. While there are signs of weaker employment growth among young workers in certain exposed entry-level jobs, there is no widespread deterioration in labour-market outcomes for this cohort.

In China, rapid AI deployment is creating displacement pressures across sectors, from taxi drivers to white-collar professionals. While this could compound challenges for young entrants to the labour force, China's high youth unemployment predates the AI boom, driven by slowing economic growth, private-sector weakness and skills mismatches.

In India, by contrast, risks are concentrated in the large information technology and business services sectors. Although industry leaders dispute claims of mass AI-driven layoffs, workforce reductions at major IT firms have occurred. Cross-country evidence suggests that economies specialising in digitally deliverable services may face greater employment pressure over time.

Japan presents a very different picture. With rapid population ageing causing severe labour shortages, AI appears less like a threat and more like a solution. Generative AI adoption remains relatively limited, suggesting that expanding productive use and worker training is far more pressing than preventing job loss.

Across the region, greater efforts are needed to ensure young people have the tools required to engage productively with AI. Modernising education and training programmes is essential. Educational institutions must teach AI skills and digital literacy alongside human skills that are harder to automate, such as analytical reasoning, critical judgment, communication, creativity and teamwork. AI must enhance learning, not replace it.

For those already in employment, firms must offer regular retraining opportunities. As an OECD study demonstrated, retraining, worker consultations and clear workplace guidelines go a long way toward harnessing AI-driven productivity gains. As routine entry-level tasks are automated, companies must also provide internships, apprenticeships and work-based learning pathways.

The ultimate challenge is to use AI to build human capital rather than undermine it. Recent research indicates that greater AI exposure in South Korea is associated with improvements in adult numeracy, with evidence pointing to larger gains among younger workers.

However, no amount of AI training can replace robust labour-market institutions and sound economic policies. While specifics will vary by country, labour regulations should make it easier for firms to recruit and train young workers. Macroeconomic stability, investment, entrepreneurship and healthy market competition remain essential to generating productive employment.

AI will almost certainly transform Asian labour markets, and young workers may feel the initial impact. Yet the transition is unlikely to be as dramatic as some tech leaders suggest. In any case, the best defence against AI-induced disruption lies in acquiring the skills, experience and opportunities needed to harness the technology effectively.

(Prof Lee Jong-Wha is a former chief economist at the ADB and a former senior adviser for international economic affairs to the president of South Korea)