TY - JOUR
T1 - Robots & AI exposure and wage inequality
T2 - a within occupation approach
AU - Jaccoud, Florencia
N1 - Funding Information:
I am grateful to Filippo Bontadini, Tommaso Ciarli, Rinaldo Evangelista, Neil Foster-McGregor, \u00D6nder Nomaler, Fabien Petit, Guido Pialli, Ekaterina Prytkova, Matteo Tubiana, and Bart Verspagen for comments on previous versions of this paper. I am extremely thankful to Stijn Broecke, Sugat Chaturvedi, Tommaso Ciarli, Alexandre Georgieff, Deyu Li, Fabien Petit, Ekaterina Prytkova, and Jacopo Staccioli for kindly sharing the data on AI and/or robots exposure used in this paper. I am also grateful to the participants of the CORA 2024 Conference on Robots and Automation; Social Situation Monitor Research Seminar 2023 \u2018The future of work: artificial intelligence and its labor market and social impacts\u2019; the 10th Ph.D. Workshop in Economics of Innovation, Complexity and Knowledge, as well as the participants at the UNU-MERIT 2023 Research Week for the insightful comments that helped improve the paper. The author acknowledge the support by the European Union\u2019s Horizon 2020 research and innovation program under grant agreement No. 101004703 -PILLARS (Pathways to inclusive labor markets).
The data supporting the findings of this study are sourced from EUROSTAT and IFR. Due to licensing restrictions, these data are not publicly available and were accessed under a specific agreement for the purposes of this research project. However, the code used to generate the estimates is available upon request.
PY - 2025/12
Y1 - 2025/12
N2 - This paper examines the linkages between occupational exposure to recent automation technologies and inequality across 19 European countries. Using data from the European Union Structure of Earnings Survey (EU-SES), a fixed-effects model is employed to assess the association between occupational exposure to artificial intelligence (AI) and to industrial robots–two distinct forms of automation–and within-occupation wage inequality. The analysis reveals that occupations with higher exposure to robots tend to have lower wage inequality, particularly among workers in the lower half of the wage distribution. In contrast, occupations more exposed to AI exhibit greater wage dispersion, especially at the top of the wage distribution. We argue that this disparity arises from differences in how each technology complements individual worker abilities: robot-related tasks often complement routine physical activities, while AI-related tasks tend to amplify the productivity of high-skilled, cognitively intensive work.
AB - This paper examines the linkages between occupational exposure to recent automation technologies and inequality across 19 European countries. Using data from the European Union Structure of Earnings Survey (EU-SES), a fixed-effects model is employed to assess the association between occupational exposure to artificial intelligence (AI) and to industrial robots–two distinct forms of automation–and within-occupation wage inequality. The analysis reveals that occupations with higher exposure to robots tend to have lower wage inequality, particularly among workers in the lower half of the wage distribution. In contrast, occupations more exposed to AI exhibit greater wage dispersion, especially at the top of the wage distribution. We argue that this disparity arises from differences in how each technology complements individual worker abilities: robot-related tasks often complement routine physical activities, while AI-related tasks tend to amplify the productivity of high-skilled, cognitively intensive work.
KW - Artificial intelligence
KW - Inequality
KW - Occupations
KW - Robots
U2 - 10.1007/s40821-025-00306-w
DO - 10.1007/s40821-025-00306-w
M3 - Article
SN - 1309-4297
VL - 15
SP - 1035
EP - 1090
JO - Eurasian Business Review
JF - Eurasian Business Review
IS - 4
M1 - 102011
ER -