A sobering assessment from the International Labour Organisation reveals that generative artificial intelligence stands poised to reshape the employment landscape for nearly 80 million workers across the ASEAN region, even as the immediate threat of mass job losses remains contained. The latest ILO study, released in July, provides the most comprehensive examination to date of how AI adoption will ripple through the economies of Southeast Asia's 11 nations, offering both reassurance and urgent warnings about regional readiness.
According to ILO projections for 2025, approximately 22.9 per cent of total employment across ASEAN—representing close to 80 million people—work in occupations with meaningful exposure to generative AI. This figure encompasses jobs where AI tools could fundamentally alter how tasks are performed, augment worker capabilities, or potentially automate significant portions of daily responsibilities. Yet the headline figure masks a more nuanced reality: only 3.3 per cent of the workforce, or 11.7 million workers, occupy roles classified as facing the highest degree of AI exposure where transformative change appears most imminent. The remaining two-thirds of ASEAN's employed population continue working in sectors where generative AI presents minimal to no identifiable threat, suggesting that large swathes of the regional labour force remain insulated from immediate technological disruption.
The exposure to AI is unevenly distributed across the region, with digital-economy powerhouses pulling far ahead of their neighbours. Singapore leads decisively, with 42.2 per cent of its workforce positioned in occupations with more than minimal AI exposure—a reflection of its status as a global technology hub and service-oriented economy. The Philippines follows at 28.1 per cent, driven substantially by its thriving business process outsourcing and information technology sectors. Indonesia trails at 21.7 per cent, Vietnam at 20.8 per cent, and Thailand at 20.6 per cent. These disparities highlight a fundamental challenge for ASEAN policymakers: while some nations are charging toward an AI-enabled future, others risk being left behind without deliberate intervention.
Despite the vast numbers potentially affected, the ILO findings offer a reassuring counterpoint to doomsday narratives about AI-driven unemployment. Current evidence points to "significant exposure" combined with "limited disruption," suggesting that the technology's disruptive potential has not yet materialised into widespread job losses. Employment in highly exposed occupations has continued to expand even as companies experiment with generative AI tools, indicating that AI adoption has operated more as a complement to human work than a wholesale replacement mechanism. This pattern aligns with historical technological transitions, where initial fears of mass displacement have typically given way to labour market adjustments, though often with painful distributional consequences for particular groups.
GenAI adoption across ASEAN remains inchoate and concentrated in narrow sectors. Technology-intensive occupations show the highest uptake, while the uptake in office and administrative roles—occupations statistically identified as highly exposed—remains surprisingly modest. This gap between theoretical exposure and actual implementation suggests that barriers to adoption persist: limited AI literacy among management, infrastructure constraints, concerns about data security, and workforce resistance may all be playing roles. For Malaysia and other regional economies, this window of limited disruption offers critical time to prepare citizens and institutions for transitions that seem inevitable but need not be catastrophic.
Among demographic groups, generational exposure presents a startling pattern. Young workers aged 15 to 24 and their adult counterparts show broadly comparable levels of vulnerability to AI, suggesting that age offers little protective advantage. The finding undermines assumptions that digital natives automatically possess advantages in an AI-augmented workplace. Gender, however, emerges as a far sharper dividing line. Women are more than twice as likely as men to be employed in occupations classified as highly exposed to generative AI—a consequence of their overrepresentation in clerical, administrative, and professional services roles that AI can readily automate or fundamentally alter. This disparity carries troubling implications for regional gender equality: unless deliberate interventions are mounted, AI adoption may widen existing gender wage gaps and occupational segregation patterns across ASEAN.
The region's preparedness for managing these transitions is deeply uneven, revealing what the ILO describes as a significant preparedness gap. Singapore stands apart as a globally competitive AI ecosystem, combining state-of-the-art digital infrastructure, abundant AI talent, and a whole-of-government coordination strategy that weaves AI adoption into broader economic planning. Most other ASEAN nations lack comparable institutional capacity, leaving them vulnerable to haphazard technology adoption driven by individual firms rather than coordinated national or regional frameworks. This disparity threatens to amplify existing economic divergences within Southeast Asia, potentially widening the gap between Singapore's innovation-led economy and its neighbours.
To prevent AI-driven disruption from becoming a source of regional instability and inequality, the ILO prescribes a multipronged policy framework centred on human-centred governance. The foundation must be inclusive skills development, requiring massive expansion of upskilling and reskilling programmes tailored not to abstract notions of the future workforce but to the concrete needs of existing workers. Women and youth must receive particular attention given their heightened exposure. Simultaneously, micro, small, and medium enterprises—the backbone of ASEAN employment—require targeted support to overcome the knowledge gaps and capital constraints that prevent them from adopting AI in productive ways. Regional knowledge sharing and coordinated human resource development across ASEAN member states could prevent a race to the bottom in wages and working conditions as countries compete for AI investment.
For Malaysia specifically, the findings underscore both opportunity and obligation. As a middle-income economy with substantial service and technology sectors, Malaysia faces AI exposure comparable to Vietnam and Thailand, positioning it to capture productivity gains from intelligent automation. Yet Malaysia's preparedness remains uncertain, with no indication of comprehensive national AI governance frameworks or large-scale reskilling initiatives comparable to Singapore's efforts. The window for building institutional capacity and upskilling the workforce remains open but is narrowing. Without deliberate action, Malaysia risks becoming a passive recipient of technological change rather than an active shaper of how AI transforms its labour markets. The ILO report thus functions as both reassurance and urgent call: disruption is not yet here, but the time to prepare is now.
