Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness
A July 2026 ILO brief examining generative-AI exposure, observed labour-market disruption and preparedness across ASEAN.
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Decide whether this external resource fits your goal before leaving the platform.
You will leave with
How occupational exposure differs from actual adoption or job loss, and why infrastructure, skills, enterprise capacity, governance and social dialogue shape outcomes.
Time
about 2 hr
Before you begin
Basic understanding of occupations, percentages, regional variation and the difference between exposure and causal impact.
Do this now
First read why it was selected, how to use it, and its main limitation.
Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparednessHow occupational exposure differs from actual adoption or job loss, and why infrastructure, skills, enterprise capacity, governance and social dialogue shape outcomes.
It is the newest specific ILO AI-and-work publication identified in this review and brings current evidence rather than relying only on projected exposure.
Workers, educators, labour-policy teams, employers’ and workers’ organizations, and researchers.
Use as a dated regional case study; separate measured employment patterns from future scenarios and never generalize ASEAN findings to the whole world without comparison.
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02Source
03Scope
04Review
How occupational exposure differs from actual adoption or job loss, and why infrastructure, skills, enterprise capacity, governance and social dialogue shape outcomes.
Fit and purpose
Why the resource is here and what to know before beginning.
Why selected
It is the newest specific ILO AI-and-work publication identified in this review and brings current evidence rather than relying only on projected exposure.
Suitable for
Workers, educators, labour-policy teams, employers’ and workers’ organizations, and researchers.
Prerequisites
Basic understanding of occupations, percentages, regional variation and the difference between exposure and causal impact.
Use and access
How to plan the time, access, and practical requirements.
How to use it
Use as a dated regional case study; separate measured employment patterns from future scenarios and never generalize ASEAN findings to the whole world without comparison.
Language
English; the accompanying ILO news material is available in several regional languages, but publication-edition parity was not checked.
Access
The official publication page is public and links to the downloadable brief.
Accessibility
The downloadable brief, tables, annexes and language editions were not independently tested with assistive technology.
Interpretation and permissions
What frames the perspective, reuse, and the claims we make about it.
Perspective
International labour-policy perspective centered on ASEAN and the ILO’s decent-work mandate.
Rights
Check the publication’s exact ILO reuse notice before reproducing text, figures or tables; cite the 8 July 2026 edition.
Strengths
Combines exposure estimates with emerging labour-market evidence
Makes preparedness and policy choices central rather than assuming technological determinism
Limitations
The analysis is regional to ASEAN and cannot stand in for global labour markets
Recent observations may change as adoption spreads, while causal attribution remains difficult
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