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.

翻译：人工智能特别是生成式模型的扩散，预计将以不均衡的方式重塑各行业、地域和社会群体的劳动力市场。本文提出一种基于行业数据估算就业受人工智能潜在影响的方法框架，以解决西班牙语境下以职业为中心的研究方法的局限性。通过构建人工智能CNAE影响矩阵，并将其应用于2021年至2023年省级就业数据，我们对西班牙全境人工智能影响进行了地域与性别维度的分层评估。结果显示稳定的结构性规律：大都市区和服务业主导区域的受影响程度更高，且存在持续的性别差距——所有地域的女性就业均表现出更高的受影响水平。该框架并非旨在预测岗位替代，而是从结构视角揭示人工智能最可能重塑工作内容与技能需求的领域，从而为循证决策与战略规划提供支撑。