AI and Economic Divergence in Asia
IMF Working Papers, August 7, 2026
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Bibliographic details
- Authors: Natasha X Che, Weining Xin, Taichi Yoshida
- Published: August 7, 2026
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9798229054348.001
Summary findings
- Using a small open economy overlapping generations model, the paper examines how AI can drive economic divergence across and within Asian economies.
- AI adoption may promise sizable productivity gains but could create temporary but potentially longlasting divergence across countries.
- Structurally-prepared advanced economies tend to adopt AI earlier and see immediate growth gains while emerging markets and developing economies (EMDEs) face delayed adoption and initial growth headwinds from rising costs of capital.
- Structural reforms that boost productivity and strengthen human capital not only accelerate adoption in EMDEs but also amplify the growth gains.
- Within countries, AI adoption could widen inequality across multiple dimensions:
- Across skill groups: high-skilled workers benefit disproportionately from complementarity with the more capital-intensive technology.
- Across generation: the shift of national income toward capital favors asset-rich older households relative to younger workers who rely primarily on labor income.
- Redistributive policies can help mitigate these distributional pressures, though they entail equity efficiency trade-offs that vary with country-specific fiscal and demographic conditions.
Model and approach
- Framework: small open economy overlapping generations model.
- Focus: interactions between AI adoption, capital intensity, productivity gains, and distributional outcomes across skill groups and generations.
Cross-country dynamics and policy implications
- Timing of adoption:
- Advanced economies: earlier AI adoption and immediate growth gains.
- EMDEs: delayed adoption and initial growth headwinds from rising costs of capital.
- Role of structural reforms:
- Reforms that boost productivity and strengthen human capital accelerate AI adoption in EMDEs.
- Such reforms amplify the growth gains from AI in EMDEs.
Within-country distributional effects and policy trade-offs
- Distributional impacts:
- Skill inequality: high-skilled workers gain disproportionately due to complementarity with capital-intensive AI technologies.
- Generational inequality: capital-biased income shifts advantage older, asset-rich households over younger, labor-dependent workers.
- Policy responses:
- Redistributive policies can mitigate distributional pressures.
- These policies involve equity-efficiency trade-offs that depend on country-specific fiscal capacity and demographic structure.
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