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Manila Bulletin devider Business devider The Economy devider Philippines, developing Asia-Pacific lag in AI readiness—ADB study

Philippines, developing Asia-Pacific lag in AI readiness—ADB study

Published Apr 10, 2026 06:00 pm  |  Updated Apr 10, 2026 02:27 pm

The Philippines is among developing economies in Asia-Pacific that continue to lag behind advanced regional peers in artificial intelligence (AI) preparedness, limiting near-term gains due to gaps in infrastructure, skills, and innovation capacity, according to the Asian Development Bank (ADB).

In a special topic titled “AI Readiness and Economic Impacts in Asia and the Pacific”, published as part of its Asian Development Outlook (ADO) April 2026 report on Friday, April 10, the Manila-based ADB examined how AI preparedness, infrastructure capacity, and labor market readiness vary widely across economies in the region.

The report, written by Roshen Fernando and Ed Kieran Reyes of the ADB’s economic research and development impact department, highlighted a clear divide between advanced Asia-Pacific (AAP) economies and developing Asia-Pacific (DAP) economies, including the Philippines.

AAP economies—specifically Australia, Hong Kong, Japan, New Zealand, Singapore, and South Korea—cluster near the global frontier in AI readiness. They record an average score of 0.19 in the digital infrastructure component of the AI Preparedness Index (AIPI).

By contrast, many DAP economies—including the Philippines, Cambodia, India, Myanmar, and Papua New Guinea—score below 0.11, indicating significantly weaker digital infrastructure capacity. The report said this gap reflects binding constraints in computing capacity, digital connectivity, and data infrastructure, which create cascading barriers that limit AI diffusion across developing economies.

These constraints, the report added, restrict access to cloud-based services and limit the use of proprietary or local data for training AI models. As a result, firms in developing economies adopt AI more slowly, reducing the scale and speed of productivity gains across their economies.

Also, the report pointed to differences in human capital readiness, which determines whether firms can effectively absorb and apply AI tools. DAP economies average 0.13 on the human capital and labor market policies component of AIPI, compared with 0.17 in AAP economies, underscoring a further gap in workforce preparedness for AI adoption.

The report said these gaps constrain the adoption of AI technologies, limiting productivity gains and slowing economic transformation. As a result, estimated AI-driven productivity gains in DAP range from 0.2 percent to 6.9 percent, below levels seen in AAP.
It added that while AI could lift gross domestic product (GDP) growth across Asia-Pacific, gains in DAP are projected at a more modest 0.2 to 1.8 percentage points (ppts) by 2030, compared with 0.6 to 2.1 ppts in AAP. However, the report noted that DAP economies could benefit more over time through “catch-up” effects, provided investments in infrastructure, education, and institutions are strengthened.
The study also found that the distribution of AI-driven gains will vary by sector. Services are expected to see the largest productivity improvements, while agriculture is likely to benefit the least, with estimated productivity increases ranging from 0.1 percent to 4.5 percent.

Beyond infrastructure and skills readiness, the report also highlighted significant variation in labor market demand for AI-related competencies across the region. It cited job posting data showing that advanced economies like Singapore and South Korea exhibit higher and faster-growing demand for AI-related skills compared with developing economies like India, Malaysia, and the Philippines.

The report said these differences reflect varying levels of firm readiness and complementary organizational capabilities, which influence how quickly AI adoption is translated into productivity improvements across Asia-Pacific economies.

According to the ADB, policy reforms aimed at improving digital infrastructure, strengthening human capital, and enhancing innovation systems will be crucial to maximize AI’s economic potential while mitigating risks such as job displacement.

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Asian Development Bank (ADB) artificial intelligence (AI)
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