Generative artificial intelligence (GenAI) is set to affect the working lives of nearly 80 million people across ASEAN, but the technology has not yet produced the large-scale job losses often assumed in public debate, according to a new study by the International Labour Organization.
The report, Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness, estimates that 22.9 per cent of total employment in the region sits in occupations with more than minimal potential exposure to GenAI. Yet only 3.3 per cent of ASEAN’s workforce, or about 11.7 million workers, falls into the highest-exposure category.
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The distinction matters. Exposure does not automatically mean replacement. In many jobs, GenAI is more likely to alter tasks, compress workflows, or change skill requirements than eliminate roles outright. Around 67 per cent of ASEAN employment remains in occupations with no identified exposure to the technology, reflecting the region’s still-heavy dependence on agriculture, manufacturing, services, and informal work.
“The potential for labour market transformation is significant, but widespread disruption is not yet visible,” the report notes.
Singapore leads, but the exposure gap is regional
Among the nine ASEAN economies with available data, Singapore has the highest share of workers in occupations with more than minimal GenAI exposure, at 42.2 per cent of total employment. The Philippines follows at 28.1 per cent, reflecting its large services, business process outsourcing, and IT-enabled services base.
Indonesia stands at 21.7 per cent, Vietnam at 20.8 per cent, and Thailand at 20.6 per cent. The findings point to a familiar split in Southeast Asia: economies with larger formal services sectors and deeper digital adoption face earlier exposure, while those with bigger agricultural and informal workforces may see slower direct effects but also risk falling behind in productivity gains.
For Singapore, the finding is unsurprising. The city-state has spent years building AI governance frameworks, research capabilities, enterprise adoption schemes, and public-sector AI deployment. Its exposure is high because its workforce is more concentrated in professional, technical, administrative, and managerial roles — the very categories where GenAI tools can most easily automate or augment cognitive tasks.
The Philippines presents a different issue. Its BPO sector has long been one of the country’s main employment engines and a major export earner. GenAI’s ability to handle customer support, summarisation, transcription, and basic content generation puts pressure on lower-value work, even if higher-complexity services may remain resilient. This is not an immediate cliff edge, but it is a warning for a sector built on labour-cost arbitrage.
Startups face an adoption market, not just a disruption story
For Southeast Asia’s technology sector, the ILO report is less a story about robots taking jobs than about uneven enterprise adoption. GenAI use remains concentrated in technology-intensive occupations, while uptake is still comparatively limited in office and administrative roles despite their high exposure.
That gap creates a commercial opening for startups building AI workflow tools, vertical software, compliance systems, customer service automation, education technology, and human resources platforms. It also creates a harder question: whether small businesses can absorb these tools without widening the productivity divide between digitally mature firms and everyone else.
Southeast Asia’s internet economy remains large enough to support this shift. Google, Temasek, and Bain & Company estimated the region’s internet economy at US$263 billion in gross merchandise value in 2024, with revenue reaching US$89 billion. But the benefits of AI adoption are unlikely to spread evenly across a region where micro, small, and medium enterprises still account for the bulk of firms and employment.
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The competitive landscape is already crowded. Global platforms such as OpenAI, Microsoft, Google, Anthropic, and Meta are embedding GenAI into workplace software used by regional companies. At the same time, Southeast Asian and Asia-focused players in customer engagement, voice AI, workflow automation, and sector-specific software are trying to localise products for language, regulation, and enterprise budgets. Companies such as WIZ.AI, Kata.ai, Yellow.ai, and regional system integrators are competing for the same automation budgets that banks, insurers, retailers, and contact centres are now reassessing.
Gender exposure is a policy problem
The ILO study also identifies a significant gender gap. Women in ASEAN are more than twice as likely as men to work in occupations with high GenAI exposure, largely because they are concentrated in clerical, administrative, and professional roles.
This finding complicates the common assumption that AI disruption will primarily hit male-dominated technical or industrial jobs. In the near term, it may instead affect office-based roles where women are heavily represented, including administrative support, routine documentation, customer operations, and clerical functions.
Young workers aged 15 to 24 and adult workers show broadly similar exposure levels, according to the report. That suggests the challenge is not limited to new labour-market entrants. Reskilling policies will need to cover mid-career workers as well, especially those in roles where GenAI changes the value of routine knowledge work.
Christian Viegelahn, ILO economist and lead author of the report, said the outcome will depend less on the technology itself than on institutional choices.
“Harnessing the benefits of GenAI requires more than access to technology,” he said. “Productivity gains depend on investments in human capital and social protection. Ultimately, future labour market outcomes will depend less on exposure alone than on the policy choices to build the preparedness and resilience of workers, enterprises and institutions.”
Preparedness may decide who benefits
The ILO report argues that ASEAN’s priority should be human-centred governance, broader access to skills training, support for MSMEs, and stronger knowledge exchange across member states. That agenda is not new, but GenAI makes it more urgent.
The risk for Southeast Asia is not simply job destruction. It is a two-speed labour market in which Singapore and digitally advanced firms use AI to raise productivity, while smaller companies and lower-income workers face task displacement without the tools, training, or social protection to adjust.
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For founders and investors, the next phase of the AI market in ASEAN will depend on whether products can move beyond pilots and productivity claims into measurable enterprise adoption. For policymakers, the test is whether AI strategies translate into worker-level preparedness rather than headline infrastructure announcements.
The ILO’s message is sober: GenAI is already relevant to tens of millions of ASEAN workers, but disruption is not predetermined. The region still has time to shape the outcome. Whether it does so will depend on execution, not rhetoric.
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