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Abstract: This study investigates the relationship between the proportion of employed ICT specialists in the workforce and the adoption of artificial intelligence (AI) technologies by enterprises across 27 European Union countries during the period 2021–2023. The primary aim is to assess whether a higher share of ICT professionals is associated with increased AI adoption and to determine if this relationship varies by the educational attainment of the workforce. In particular, the study distinguishes between two educational groups: individuals with lower educational attainment (levels ED0–4, comprising less than primary to post-secondary non-tertiary education) and those with tertiary education (levels ED5–8).
Data were collected for each country over three years, with observations comprising country, year, the percentage of ICT specialists, and the corresponding rate of AI adoption by enterprises. To rigorously analyze the panel data structure, we employed mixed-effects models using SPSS’s REML estimation method. The models incorporated a subject-level random effect for countries and a repeated measure for year, assuming a first-order autoregressive (AR(1)) covariance structure to account for temporal dependencies in AI adoption. The fixed effect of ICT specialists was estimated separately for the two educational groups.
For the lower education group, the mixed model revealed a positive trend between the proportion of ICT specialists and AI adoption; however, the fixed effect was only marginally significant, suggesting that while there is a tendency for increased ICT specialization to be linked with higher AI adoption, the evidence is not robust at conventional significance levels. In contrast, the analysis for the tertiary education group demonstrated a strong and statistically significant positive association.
These preliminary results indicate that while a general positive relationship exists between the proportion of ICT specialists and AI adoption, this association is considerably more pronounced among individuals with tertiary education. The findings suggest that advanced educational qualifications may enhance the ability of the ICT workforce to foster AI innovation in enterprises. This research contributes to the broader discourse on the human capital dimensions of digital transformation and underscores the potential role of educational attainment in driving technological change within organizations.
Key words: ICT workforce, AI adoption, Educational attainment, Human capital.
JEL classification: J24; O33; O15
