Workers’ exposure to AI across development

Piotr Lewandowski, Karol Madoń and Albert Park
Authors registered in the RePEc Author Service: Karol Madoń

No 02/2025, IBS Working Papers from Instytut Badan Strukturalnych

Abstract: This paper develops a task-adjusted, country-specific measure of workers’ exposure to artificial intelligence (AI) across 103 countries, covering approximately 86% of global employment. Building on the AI Occupational Exposure index by Felten et al. (2021), we map AI-related abilities to worker-level tasks using survey data from PIAAC, STEP, and CULS. We then predict occupational AI exposure in countries lacking survey data using a regression-based approach. Our findings show that accounting for within-occupation task differences significantly amplifies the development gradient in AI exposure. About 47% of cross-country variation is explained by differences in task content, particularly among high-skilled occupations. We attribute these differences primarily to cross-country differences in ICT use intensity, followed by human capital and globalisation-related firm characteristics. We also document rising AI exposure over the past decade, driven largely by changes in task composition. Our results highlight the central role of digital infrastructure and skill use in shaping global AI exposure.

Keywords: tasks; AI; labor; technology; skills (search for similar items in EconPapers)
JEL-codes: J21 J23 J24 (search for similar items in EconPapers)
Pages: 56 pages
Date: 2025-03
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