Generative AI and jobs
A Refined Global Index of Occupational Exposure
Bibliographic Data
| ID | 19912536 |
|---|---|
| Authors | Paweł Gmyrek (0000-0002-6328-1394), Janine Berg (0000-0002-2609-4768), Karol Kamiński (0000-0002-9465-2581), Filip Konopczyński, Agnieszka Ładna, Balint Nafradi (0000-0001-9543-2970), Konrad Rosłaniec, Marek Troszyński (0000-0002-3653-4018), International Labour Organization Research Department |
| Year | 2025 |
| Publication date | 2025-01-01 |
| Open Access | Yes |
| Type | BOOK |
| Venue | Generative AI and jobs (SOURCE_BOOK) |
| Publisher | ILO (PUBLISHER) |
| DOI | 10.54394/hetp0387 |
| OpenAlex | W4410554463 |
| ISBN | 9789220421840 |
| Language | EN |
| Citations received | 3 |
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
Generative grammar · Artificial Intelligence · Computer Science · Digital Economy and Work Transformation
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |