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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2512.23059 |
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| _version_ | 1866911647824609280 |
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| author | Mestre, Antoni Naya, Xavier Albert, Manoli Pelechano, Vicente |
| author_facet | Mestre, Antoni Naya, Xavier Albert, Manoli Pelechano, Vicente |
| contents | The diffusion of artificial intelligence, particularly generative models, is expected to transform labor markets in uneven ways across sectors, territories, and social groups. This paper proposes a methodological framework to estimate the potential exposure of employment to AI using sector based data, addressing the limitations of occupation centered approaches in the Spanish context. By constructing an AI CNAE incidence matrix and applying it to provincial employment data for the period 2021 to 2023, we provide a territorial and gender disaggregated assessment of AI exposure across Spain. The results reveal stable structural patterns, with higher exposure in metropolitan and service oriented regions and a consistent gender gap, as female employment exhibits higher exposure in all territories. Rather than predicting job displacement, the framework offers a structural perspective on where AI is most likely to reshape work and skill demands, supporting evidence based policy and strategic planning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_23059 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Inteligencia artificial y empleo en España: una aproximación territorial y de género a la exposición laboral Mestre, Antoni Naya, Xavier Albert, Manoli Pelechano, Vicente Computers and Society The diffusion of artificial intelligence, particularly generative models, is expected to transform labor markets in uneven ways across sectors, territories, and social groups. This paper proposes a methodological framework to estimate the potential exposure of employment to AI using sector based data, addressing the limitations of occupation centered approaches in the Spanish context. By constructing an AI CNAE incidence matrix and applying it to provincial employment data for the period 2021 to 2023, we provide a territorial and gender disaggregated assessment of AI exposure across Spain. The results reveal stable structural patterns, with higher exposure in metropolitan and service oriented regions and a consistent gender gap, as female employment exhibits higher exposure in all territories. Rather than predicting job displacement, the framework offers a structural perspective on where AI is most likely to reshape work and skill demands, supporting evidence based policy and strategic planning. |
| title | Inteligencia artificial y empleo en España: una aproximación territorial y de género a la exposición laboral |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2512.23059 |