Cambodia Among ASEAN’s Least AI-Ready Members, ILO Brief Says

The International Labour Organization’s new ASEAN brief centers on one number: 22.9% of ASEAN employment, equivalent to nearly 80 million workers, sits in occupations with more than a minimal degree of exposure to generative AI. The brief’s other variable is preparedness, and the report says it may matter more than exposure alone.

Titled the July 2026 brief on ASEAN labour markets, “Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness,” the brief was published in July 2026. Cambodia’s AI readiness ranks among the lowest in the bloc, the ILO says, alongside Laos, Myanmar and Timor-Leste. For Cambodia, the report states, lower exposure combined with limited readiness could reduce its ability to translate future AI adoption into productivity gains and quality job creation.

The 80-Million Headline

The 22.9% figure is built on 2025 employment estimates and groups every ASEAN occupation with more than a minimal degree of potential exposure to GenAI. It is a wider net than the highest-exposure category the brief also publishes. Of the bloc’s total employment, only 3.3% sits in that top band, the ILO says, equal to 11.7 million workers.

Around 67% of ASEAN employment remains in occupations with no identified exposure to generative AI at all, the brief finds. “The potential for labour market transformation is significant, but widespread disruption is not yet visible,” the report states. Adoption across the region sits at an early and uneven stage, concentrated in technology-intensive occupations, with comparatively limited uptake in office and administrative roles despite those jobs carrying high exposure. Employment in highly exposed occupations has continued to expand across ASEAN.

Preparedness, Not Exposure

A few paragraphs in, the report makes its key distinction. “While these countries may initially face lower levels of exposure to GenAI, they also risk capturing fewer of the potential benefits associated with AI-driven productivity growth,” the report says, speaking of the four least-ready members. The wording recasts lower exposure as a smaller share of the eventual gains, not protection from them. The brief’s title names the same trade-off: significant exposure, limited disruption, uneven preparedness. Preparedness, the report concludes, may be a more important factor than exposure alone.

Singapore stands at the top of the readiness stack the brief draws up. The report credits the city-state with “advanced digital infrastructure, strong talent availability and a whole-of-government approach to implementation strategy.”

A middle group, including the Philippines, Malaysia, Thailand, Brunei, Indonesia and Vietnam, has “established many of the foundations needed for AI adoption” but “continues to face important gaps in areas such as advanced skills, research capacity, computing infrastructure, innovation ecosystems and access to finance,” per the brief. The five ASEAN countries with available data cluster between Singapore’s top of the exposure scale and Thailand’s mid-range position. The Philippines’ share, the second-highest in the bloc, is the subject of a separate the Philippines GenAI exposure report.

Cambodia, Laos, Myanmar and Timor-Leste at the Bottom

Cambodia’s reading in the ILO brief draws on the country’s 2023 Labor Force Survey. The report groups Cambodia with Laos, Myanmar and Timor-Leste as countries with “relatively low levels of AI readiness, reflecting limitations in digital infrastructure, institutional capacity and technological capabilities.”

The ILO does not publish a per-country exposure figure for those four. What the brief does publish is a structural diagnosis: each of the four “may initially face lower levels of exposure to GenAI” while also “risk[ing] capturing fewer of the potential benefits associated with AI-driven productivity growth.” For Cambodia, lower exposure combined with limited readiness could reduce its ability to translate future AI adoption into productivity gains and quality job creation, per the report. The brief recommends that Cambodia invest in “digital infrastructure, skills development and governance capacity” to change that trajectory.

Where the Exposure Lands on Women

The exposure numbers break sharply by gender. Across ASEAN, 4.8% of women were employed in occupations with high GenAI exposure in 2025, compared with 2.3% of men, the brief finds. Women are more than twice as likely as men to work in roles the report flags as high-exposure.

The reason, the brief says, is occupational segregation: women are concentrated in clerical, administrative and professional roles, the same jobs the GenAI exposure index scores most heavily. In Cambodia, Indonesia, the Philippines and Vietnam, wage workers with significant GenAI exposure earn notably more than those with minimal or no exposure, the ILO notes, an indicator the brief reads as a productivity or skill premium. That premium sits on the same jobs the gender gap pulls more women into. The exposure is also where the wage upside is, on the same four economies.

The gender gap is most pronounced in Thailand and the Philippines, where women are around three to four times more likely than men to work in occupations highly exposed to GenAI, the brief says. Similar, smaller gaps appear across most other ASEAN countries. Young workers aged 15 to 24 and adult workers show broadly similar levels of exposure, the report adds.

The brief recommends upskilling and reskilling programs that focus specifically on women and youth. “Particular attention should be given to women, given their concentration in more exposed occupations and the barriers they face in entering STEM education and related fields,” the report says.

The Wage Premium Signal

In four of ASEAN’s lower-middle-income economies (Cambodia, Indonesia, the Philippines and Vietnam), wage workers in occupations with significant GenAI exposure earn notably more than those with minimal or no exposure, the ILO says. The brief reads that gap as a productivity or skill premium tied to GenAI-exposed roles. For Cambodia, the data points to a productivity opportunity that the country’s current readiness may not be able to capture.

Higher wages in exposed occupations suggest a real AI-related productivity opening, the brief notes, in countries where the digital and institutional groundwork is in place. The ILO’s diagnosis is that Cambodia’s readiness, in digital infrastructure, institutional capacity and technological capabilities, may limit whether the country can capture it. The wage premium exists in the data, but the report’s recommendation is to build the foundations first. The Cambodia section of the brief ends with a list of what needs to change: digital infrastructure, skills development and governance capacity.

What the Report Asks ASEAN to Build

The brief lays out five policy priorities for the region. They share a common thread: the gains from GenAI depend on investments that sit outside the technology itself. ILO economist and lead author Christian Viegelahn frames the underlying point in a single line: “Harnessing the benefits of GenAI requires more than access to technology.”

The five recommendations, in the report’s order, are listed below. The brief’s full title signals the trade-off the recommendations are designed to close: significant exposure, limited disruption, uneven preparedness. ASEAN’s labor and social protection ministries are explicitly named in the governance recommendation. The recommendations apply across the bloc, with specific weight on Cambodia and the three other low-readiness members.

1. Human-centered AI governance structures, with labor and social protection ministries at the table
2. Inclusive labor market policies and education, with focus on women and youth
3. Support for micro, small and medium enterprises (MSMEs) to overcome AI adoption barriers
4. Sustained investment in digital infrastructure, skills and the innovation ecosystem
5. Stronger regional cooperation on knowledge exchange and workforce development

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.

The quote comes from Christian Viegelahn, ILO economist and lead author of the brief. The ILO is hosting a public webinar on the findings on 15 July 2026, from 2 pm to 3 pm Bangkok time.

Frequently Asked Questions

What does the ILO report on generative AI in ASEAN find?

The brief, “Generative AI and labour markets in ASEAN: Significant exposure, limited disruption, uneven preparedness,” was published in July 2026. It estimates 22.9% of ASEAN employment, nearly 80 million workers, sits in occupations with more than a minimal degree of GenAI exposure, with 3.3% of employment, or 11.7 million workers, in the highest-exposure category.

Which ASEAN countries are least prepared for AI?

Cambodia, Laos, Myanmar and Timor-Leste. The report cites “limitations in digital infrastructure, institutional capacity and technological capabilities” and says these countries “may initially face lower levels of exposure to GenAI” but “also risk capturing fewer of the potential benefits associated with AI-driven productivity growth.”

Which ASEAN country has the highest GenAI exposure?

Singapore, at 42.2% of total employment in occupations with more than minimal GenAI exposure. The Philippines follows at 28.1%, Indonesia at 21.7%, Vietnam at 20.8% and Thailand at 20.6%, the ILO says.

How does the gender gap in AI exposure break down?

4.8% of women in ASEAN were in occupations with high GenAI exposure in 2025, compared with 2.3% of men, per the brief. The gap is most pronounced in Thailand and the Philippines, where women are around three to four times more likely than men to work in highly exposed jobs.

What does the ILO recommend ASEAN countries do next?

Build human-centered AI governance, expand upskilling and reskilling for women and youth, support MSMEs in AI adoption, invest in digital infrastructure and skills, and strengthen regional cooperation on knowledge exchange and workforce development.