The International Labour Organisation has published a comprehensive assessment of generative artificial intelligence's potential impact on ASEAN labour markets, finding that the technology will touch the working lives of almost 80 million people across the region's 11 member states. The findings, contained in a report titled "Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness," provide a more nuanced picture than early doomsday predictions about mass technological unemployment. While the scale of exposure is substantial, the research indicates that actual job displacement remains limited thus far, suggesting the region still has a window of opportunity to prepare its workforce for this transformation.
According to the ILO's 2025 estimates, approximately 22.9 per cent of total employment in ASEAN—equivalent to nearly 80 million workers—operates in roles with more than minimal exposure to generative AI capabilities. However, the proportion facing the most acute risk proves significantly smaller. Only 3.3 per cent of the ASEAN workforce, roughly 11.7 million workers, occupy positions classified as having the highest level of exposure to generative AI disruption. This distinction is important for policymakers and workers alike, as it suggests that while AI will reshape labour markets broadly, the concentration of immediate disruption risk remains manageable and focused on particular occupational categories rather than economywide.
The geographic distribution of AI exposure across ASEAN reveals stark contrasts in sectoral composition and economic structure. Singapore leads considerably, with 42.2 per cent of its workforce in occupations showing more than minimal AI exposure, reflecting its status as a financial and technology hub. The Philippines follows at 28.1 per cent, a figure that underscores the country's significant services and information technology sector orientation. Indonesia records 21.7 per cent exposure, Vietnam 20.8 per cent, and Thailand 20.6 per cent. These variations illustrate how countries with larger agricultural bases and manufacturing sectors experience lower overall exposure than those with developed service economies. Meanwhile, approximately 67 per cent of employment across ASEAN remains concentrated in occupational areas with no identified exposure to generative AI, providing a substantial buffer against immediate sector-wide disruption.
Despite growing discussion of AI's transformative potential, actual adoption remains in its infancy across much of the region. The technology is concentrated primarily within digitally intensive industries and has achieved only limited penetration in office and administrative roles, despite these areas theoretically facing high exposure to AI applications. This gap between exposure potential and actual deployment suggests that companies remain cautious about implementation, perhaps due to cost considerations, skill gaps, or uncertainty about return on investment. For Malaysian readers particularly, this measured adoption pace offers time to develop workforce strategies, invest in education, and establish regulatory frameworks before disruption becomes acute.
A striking finding concerns the gender dimensions of AI exposure. Women are more than twice as likely as men to work in occupations classified as having high generative AI exposure. This disparity stems from women's greater concentration in clerical, administrative, and professional roles—positions where AI tools show particular applicability. The phenomenon mirrors historical patterns of technological change that have sometimes displaced women from administrative roles, raising concerns about whether current skilling and reskilling initiatives adequately address this demographic's specific needs. Young workers aged 15 to 24 and older adult workers show broadly similar exposure levels, suggesting that age alone is not a primary determinant of AI vulnerability, though the quality of preparation varies substantially by cohort.
The report underscores what it characterises as a significant "preparedness gap" across the region, with nations pursuing divergent strategies toward AI integration and workforce adaptation. Singapore stands apart as a globally competitive AI ecosystem, boasting advanced digital infrastructure, readily available technical talent, and a coordinated whole-of-government approach to AI implementation. The city-state's position reflects years of intentional investment in digital capabilities and human capital development. Other ASEAN nations, while making progress, lag considerably behind in infrastructure sophistication and institutional coordination. This uneven landscape means that without deliberate regional cooperation and knowledge sharing, certain countries risk falling further behind economically while their workforces bear the adjustment costs.
Employment in highly exposed occupations has continued expanding across ASEAN even as the technology remains relatively nascent. This counterintuitive trend suggests that demand for workers in roles with potential AI exposure continues to grow, even as displacement anxiety rises. The report characterises the current situation as one of significant potential for labour market transformation without yet visible widespread disruption. This characterisation matters because it implies that the region is not facing an imminent crisis but rather a gradual, ongoing transition that requires careful management. The window for proactive policy intervention remains open, but it is narrowing as adoption accelerates.
The ILO identifies several critical priorities for ensuring that AI development benefits ASEAN workers equitably rather than concentrating gains among technology owners. Human-centred governance frameworks must place worker protection and development at the centre of AI policy rather than treating labour concerns as secondary to innovation. The region must dramatically expand upskilling and reskilling programmes, with particular attention to women and young people who face distinct vulnerabilities. Micro, small and medium enterprises—which employ substantial portions of ASEAN's workforce—require targeted support to overcome barriers to AI adoption, ensuring they are not left behind by larger, technology-forward competitors.
Regional coordination offers significant untapped potential. Knowledge exchange mechanisms and coordinated human resource development strategies across ASEAN member states could prevent a race-to-the-bottom scenario where countries compete for investment by relaxing labour protections or wage standards. Singapore's advanced AI ecosystem, for instance, could serve as a model for other nations while accounting for their different developmental stages. Malaysia, with its diverse manufacturing and services sectors, occupies an interesting middle position—advanced enough to implement AI selectively but with sufficient traditional employment to require careful transition planning. The country's policy choices in the coming months will significantly influence whether AI adoption generates broadly shared prosperity or concentrated disruption.
Looking forward, the ILO's findings suggest that ASEAN faces not an unavoidable catastrophe but a choice about how to manage technological change. The region's 80 million exposed workers are not facing imminent mass displacement, but they do require education systems prepared to teach AI literacy, social protection systems robust enough to support transitions, and economic policies that channel productivity gains toward wage growth rather than pure capital accumulation. Singapore's head start in AI preparedness creates both opportunity—through knowledge transfer—and risk—that other nations may fall permanently behind. For Malaysia and its ASEAN neighbours, the report's cautiously optimistic assessment carries an implicit warning: the narrow window for proactive preparation will not remain open indefinitely.
