Autor: Bertín Octavio, Ciaschi Matías, Falcone Guillermo, Garganta Santiago, Gasparini Leonardo, Ramírez Leira Lucía
Institución: UNLP
Año: 2025
JEL: O33, J21
Resumen:
This paper examines how artificial intelligence (AI) adoption may affect labor markets in Latin America, focusing on inequality and poverty. Using household survey data from 14 countries, we apply four AI occupational exposure indices—the AIOE, C-AIOE, GBB, and GENOE—to assess which groups face greater risk. We validate these indices by comparing task profiles with those in high-income countries and adjust them for regional labor market features such as informality, wage structures, and union coverage. Results reveal significant heterogeneity: women, younger workers, the more educated, and those in formal employment face higher exposure to AI-driven changes. However, indices that incorporate task complementarities show less steep differences across income and education levels. Simulations suggest that displacement effects may lead to only moderate increases in inequality and poverty in the absence of mitigating policies.