Artificial Intelligence Adoption in the European Union

This paper investigates the macro-level determinants of Artificial Intelligence (AI) adoption among enterprises in the 27 member states of the European Union (EU-27) over the period 2021–2023. Drawing on data from the Digital Economy and Society Index (DESI) and Eurostat, the study employs a multiple linear regression model to assess the influence of four key variables: R&D expenditure, the share of large enterprises, the proportion of the population with above-average digital skills, and access to very high-capacity networks. All variables are log-transformed to enable elasticity-based interpretation. The findings indicate that all four factors are statistically significant and positively associated with AI adoption, with digital skills and VHCN coverage exhibiting the strongest effects. Notably, the inclusion of the share of large enterprises as an explanatory variable provides a novel contribution, underscoring the structural conditions that facilitate technology diffusion at scale. Complementary scatterplot analysis further illustrates these relationships and identifies outlier cases that deviate from general trends. The paper concludes by highlighting the importance of context-sensitive policy interventions that integrate infrastructure investment, skills development, and structural upgrading to support inclusive and effective AI adoption across the EU.