The International Labour Organisation has released a comprehensive study examining the relationship between generative artificial intelligence and labour markets across Southeast Asia, revealing that the technology's reach extends across nearly a quarter of the region's workforce. According to ILO estimates for 2025, approximately 22.9 per cent of total employment in ASEAN—equivalent to some 80 million workers—operates within occupational categories showing more than minimal potential exposure to generative AI systems. This finding comes as governments and businesses throughout the region grapple with the accelerating pace of technological change and its implications for millions of livelihoods.
Yet the scale of immediate employment disruption remains far more limited than headlines might suggest. The detailed analysis distinguishes between workers with varying degrees of AI exposure, revealing a more nuanced picture than blanket warnings about automation might imply. Only 3.3 per cent of the region's workforce—roughly 11.7 million individuals—currently work in occupations classified as facing the highest exposure to generative AI. Meanwhile, approximately two-thirds of ASEAN employment remains concentrated in occupational categories with no identified exposure to the technology whatsoever. This breakdown suggests that while transformation is underway, the immediate threat to employment stability remains concentrated in particular sectors rather than representing an economy-wide crisis.
The geographical distribution of AI exposure across ASEAN reveals significant disparities in technological readiness and economic composition. Singapore emerges as the clear leader, with 42.2 per cent of its workforce employed in occupations showing more than minimal AI exposure—a reflection of the city-state's position as a global technology hub and its highly service-oriented economy. The Philippines follows with 28.1 per cent exposure, a pattern partly attributable to its thriving business process outsourcing and information technology sectors. Indonesia, the region's most populous nation, records 21.7 per cent exposure, while Vietnam and Thailand exhibit comparable rates of 20.8 per cent and 20.6 per cent respectively. These variations underscore how economic structure and development level shape vulnerability to technological disruption across the region.
Interestingly, the actual adoption of generative AI tools remains patchy and concentrated in technology-intensive sectors, even where occupational exposure appears substantial. This disconnect between theoretical exposure and practical implementation suggests that the anticipated transformation of work is still in its nascent stages. Office and administrative roles, despite their measured susceptibility to AI capabilities, have witnessed comparatively limited uptake of these tools to date. This gap between potential and actual implementation offers a critical window for policymakers and employers to shape the trajectory of AI adoption before it accelerates beyond the capacity for managed transition.
Demographic analysis reveals concerning disparities in how AI exposure is distributed across different population groups. Women emerge as disproportionately exposed, being more than twice as likely as men to work in occupations facing high generative AI exposure. This pattern reflects the persistent concentration of women in clerical, administrative, and professional service roles—positions where AI capabilities may provide either unprecedented opportunities for advancement or significant displacement risks, depending on how implementation proceeds. Conversely, young workers between 15 and 24 years old exhibit broadly similar exposure levels to their adult counterparts, suggesting that age alone does not determine vulnerability to technological disruption in the ASEAN context.
The ILO report emphasises that despite the widespread potential for labour market transformation, tangible evidence of substantial job losses across ASEAN remains absent. This observation carries important implications for regional policymakers considering their regulatory responses to AI development. The absence of catastrophic disruption to date does not eliminate the need for proactive preparation; rather, it indicates that the region still possesses agency in determining how AI integration unfolds. The critical period appears to be now, before widespread adoption locks in particular implementation patterns and before workers face sudden dislocation without adequate support systems.
A pronounced preparedness gap emerges when examining ASEAN nations' capacity to manage AI's impact on labour markets. Singapore stands apart as possessing a genuinely competitive global AI ecosystem, combining sophisticated digital infrastructure, robust availability of technical talent, and a coordinated whole-of-government strategic approach to implementation. Other ASEAN members lag considerably behind in this integrated capacity, creating risks of uneven benefits and concentrated disruption. This divergence raises questions about whether regional cooperation mechanisms might help accelerate capability development in less-advanced economies, or whether the gap will widen further.
To harness the potential benefits of AI while mitigating employment risks, the ILO identifies several strategic priorities for ASEAN nations. Human-centred governance structures must place worker welfare at the centre of policy deliberation, ensuring that AI development serves broader social objectives rather than narrow corporate interests. Inclusive skills development programmes require substantial expansion, targeting both immediate upskilling needs and longer-term reskilling initiatives, with particular attention to closing opportunities for women and younger workers who face distinct barriers to accessing training. Supporting micro, small and medium enterprises—which constitute the backbone of employment across much of ASEAN—to overcome barriers to AI adoption remains critical, as these firms risk being left behind in technological transition.
Knowledge exchange and coordinated human resource development across ASEAN's eleven member states represents another essential component of the region's response. Current disparities in preparedness suggest that countries further advanced in AI adoption can share lessons learned while others remain at earlier implementation stages. Formal mechanisms for this exchange could accelerate capability building and help avoid repeated mistakes across the region. Such cooperation becomes particularly important given that ASEAN's economic integration through mechanisms like the ASEAN Economic Community creates interconnected labour markets where disruption in one country may have ripple effects throughout the region.
The pathway forward requires balancing genuine enthusiasm for AI's productivity-enhancing potential against realistic concerns about employment transition. The ILO's findings suggest that ASEAN possesses both the time and the capacity to shape AI implementation in ways that deliver broader benefits rather than concentrated harm. However, this window for managed transition appears time-limited. As adoption accelerates beyond its current early stages, the scope for deliberate policy choice will narrow. Governments, businesses, and international organisations must therefore act decisively to establish governance frameworks, develop worker capabilities, and foster inclusive dialogue about the future of work in Southeast Asia before technological momentum overwhelms the possibility of intentional planning.
