AI ADOPTION IN EUROPE: THE ROLE OF A TERTIARY-EDUCATED ICT WORKFORCE

Sylvester Robert Radomir
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Sylvester Robert Radomir: Lucian Blaga University of Sibiu

Revista Economica, 2025, vol. 77, issue 3, 46-55

Abstract: Artificial intelligence is spreading across European enterprises, but adoption remains uneven between countries. This paper examines whether the educational profile of ICT specialists helps explain these differences. Using harmonised Eurostat data for the 27 EU Member States over 2021-2023, we analyse how the percentage of enterprises using at least one AI technology relates to the share of ICT specialists with non-tertiary education (ED0-4) and tertiary education (ED5-8). We estimate linear mixed-effects models with country-specific random intercepts and an autoregressive error structure that reflects the persistence of national AI adoption rates. The results point to a clear and robust pattern. A higher share of tertiary-educated ICT specialists is strongly and significantly associated with a higher share of firms adopting AI, while the association for ICT specialists with non-tertiary education is positive but weak and statistically fragile. These findings suggest that the quality and depth of ICT expertise, rather than headcount alone, is central for firms ability to understand, implement, and scale AI solutions. We interpret the results through the lenses of absorptive capacity, skill-biased technological change, and complementarities between technology, skills, and organisational practices, and we outline implications for EU policies aiming to accelerate AI. Overall, the findings contribute to the growing empirical literature on digital transformation by highlighting the importance of advanced human capital for the successful diffusion of AI technologies. The analysis also provides new EU-wide evidence on how the educational structure of the ICT workforce shapes firms capacity to adopt and effectively integrate emerging digital technologies.

Keywords: ICT Workforce; AI Adoption; Educational Attainment; Human Capital; Absorptive Capacity (search for similar items in EconPapers)
JEL-codes: J24 O15 O33 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:blg:reveco:v:77:y:2025:i:3:p:46-55

DOI: 10.56043/reveco-2025-0024

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