A comparative study of the relationships between AI use, employment, economic performance, and sustainability in the EU countries
DOI: https://doi.org/10.3846/jbem.2026.27157Abstract
The swift adoption of artificial intelligence (AI) across EU economies has sparked heightened debate among scholars and policymakers about its association with labor market dynamics, economic outcomes, and sustainability objectives. This research investigates the cross-sectional links between enterprise-level AI adoption and key socio-economic indicators across EU countries, including total employment, the proportion of highly educated science and technology workers, GDP per capita, and the Sustainable Development Goals Index (SDGI). Using a comparative and multi-method approach, the study combines exploratory factor analysis, general linear model estimations, and cluster analysis to identify structural patterns and group countries with similar digital and developmental traits. Results show consistent links between AI adoption and higher economic performance, as well as a larger share of science and technology professionals. The relationships with overall employment and sustainability indicators are weaker but still present. The cluster analysis reveals diverse yet cohesive national profiles, reflecting differences in digital readiness, human capital, and institutional factors across the EU. The study’s primary contribution is to combine employment structures, economic performance, and sustainability into a comprehensive cross-sectional framework, providing a detailed comparison of AI-related patterns across the EU. Its findings provide policymakers with a solid empirical foundation for assessing how the diffusion of AI supports inclusive growth and sustainability goals.
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artificial intelligence, employment, education level, economic performance, sustainability, EU countriesHow to Cite
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