Workers’ Exposure to Artificial Intelligence Across Development Stages

Piotr Lewandowski, Karol Madoń and Albert Park
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Piotr Lewandowski: Institute for Structural Research
Karol Madoń: Institute for Structural Research
Albert Park: Asian Development Bank

No 836, ADB Economics Working Paper Series from Asian Development Bank

Abstract: This paper develops a task-adjusted, country-specific measure of workers’ exposure to artificial intelligence (AI) across 108 countries. Building on Felten et al. (2021), we adapt the artificial intelligence occupational exposure (AIOE) index to worker-level data from the Programme for the International Assessment of Adult Competencies (PIAAC) and extend it globally using comparable surveys and regression-based predictions, covering about 89% of global employment. Accounting for country-specific task structures reveals substantial cross-country heterogeneity: workers in low-income countries exhibit AI exposure levels roughly 0.8 United States (US) standard deviations below those in high-income countries, largely due to differences in within-occupation task content. Regression decompositions attribute most cross-country variation to information and communications technology intensity and human capital. High-income countries employ the majority of workers in highly AI-exposed occupations, while low-income countries concentrate in less exposed ones. Using two PIAAC cycles, we document rising AI exposure in high-income countries, driven by shifts in within-occupation tasks rather than employment structure.

Keywords: job tasks; occupations; AI; technology; skills (search for similar items in EconPapers)
JEL-codes: J21 J23 J24 (search for similar items in EconPapers)
Pages: 32
Date: 2026-01-30
New Economics Papers: this item is included in nep-ict, nep-ifn and nep-lma
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