The dual dynamics of AI adoption: Drivers and ethical awareness in European enterprises

This study examines the interactions between artificial intelligence (AI) adoption and the articulation of ethical concerns across 34 European countries. We combine the technology-organization–environment (TOE) framework with institutional theory to analyze how firm-level factors (such as enterprise size) and country-level variables (including innovation capacity, human capital specialization, and financial sector development) influence both AI uptake and awareness of issues such as bias, privacy, and transparency. Using Eurostat DES data (2021, 2023, 2024) and complementary national indicators, we apply fixed-effects regression models. By considering adoption patterns and ethical awareness from a single analytical perspective, the study provides a more integrated understanding of how organizations engage with AI and interpret the associated risks, which remains underexplored in previous empirical work. The results reveal a complex landscape: overall AI adoption remains low although fewer companies report never considering its use. Significant national variations exist, but key barriers include high costs, data quality issues, and a lack of expertise. Intriguingly, awareness of these ethical and technical challenges is stronger in countries with greater AI penetration, suggesting that increased adoption enhances awareness of the associated risks. Enterprise size also dictates the type of AI used: larger firms employ more advanced technologies, whereas smaller businesses focus on foundational applications. Statistical analysis confirms that large enterprises in innovative countries, which are supported by specialized human capital and robust financial markets, are most likely to adopt AI. Importantly, the findings reveal that the same structural conditions that encourage adoption also shape how firms perceive ethical considerations, reinforcing the claim that responsibility and uptake evolve jointly rather than in isolation. Policymakers must cultivate innovation, specialized human capital, and strong finance to ensure rapid uptake and responsible, sustainable AI use.