Generative AI and Jobs: A Refined Global Index of Occupational Exposure
Paweł Gmyrek et al. (ILO) · 2025
국제노동기구(ILO)가 생성형 AI가 일자리에 미치는 영향을 직업별로 다시 계산한 2025년 보고서입니다. 세계 노동자 네 명 가운데 한 명이 생성형 AI의 영향을 받는 직업에서 일하고, 사무직이 가장 크게 영향을 받으며, 고소득 국가와 여성의 일자리에서 노출이 더 큽니다. 대부분의 직업에는 사람이 해야 하는 일이 있어 일자리가 없어지기보다 일의 내용이 바뀔 가능성이 크다고 결론짓습니다.
출처 Gmyrek et al. (2025), ILO Working Paper, 140 · 라이선스 CC BY 4.0 · 원문
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1장 · Abstract
This study updates the ILO’s 2023 Global Index of Occupational Exposure to Generative AI (GenAI), incorporating recent advances in the technology and increasing user familiarity with GenAI tools. Using a representative sample from the 29,753 tasks in the Polish occupational classification system and a survey of 1,640 people employed in each 1-digit ISCO-08 groups, we collect 52,558 data points regarding perceive potential of automation for 2,861 tasks. We then compare this input with a survey and several rounds of Delphi-style discussions among a smaller group of international experts. Based on this process, we create a repository of knowledge about task automation that goes beyond national specificities and use it to develop an AI assistant able to predict scores for tasks in the technical documentation of ISCO-08.
Our 2025 scores are presented in a revised framework of four progressively increasing exposure gradients, with a new set of global estimates of employment shares exposed to GenAI. Clerical occupations continue to have the highest exposure levels. Additionally, some strongly digitized occupations have increased exposure, highlighting the expanding abilities of GenAI regarding specialized tasks in professional and technical roles.
Globally, one in four workers are in an occupation with some GenAI exposure. 3.3% of global employment falls into the highest exposure category, albeit with significant differences between female (4.7%) and male employment (2.4%). These differences increase with countries’ income (9.6% female vs 3.5% male in Gradient 4 in HICs), and so does the overall exposure (11% of total employment in LICs vs 34% in HICs). As most occupations consist of tasks that require human input, transformation of jobs is the most likely impact of GenAI. Linking our refined index with national micro data enables precise projections of such transformations, offering a foundation for social dialogue and targeted policy responses to manage the transition.
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