Adoption of artificial intelligence in European enterprises: a mathematical model based on socioeconomic and technological indicators - Antoniuk, Dmytro; Kolyada, Oleksandr (Management and Entrepreneurship: Trends of Development, 2024)
This study examines the factors influencing the adoption of Artificial Intelligence (AI) by enterprises across European countries, with a particular focus on the role of digital infrastructure and human capital. Using a linear regression model, the analysis explores the relationship between AI adoption and several key indicators, including the Digital Economy and Society Index (DESI), Human Development Index (HDI), Global Innovation Index (GII), Technology Readiness Index (TRI), and GDP per capita. The results reveal that DESI and HDI are the most significant drivers of AI adoption, highlighting the importance of digital ecosystems and educated workforces in facilitating AI integration. The model explains 64.9% of the variance in AI adoption, with DESI contributing to a 0.26% increase in AI adoption for every unit of improvement. HDI, representing the quality of human capital, plays an even larger role, suggesting that countries with higher levels of education and social development are better equipped to integrate AI into their industries. While innovation and technological readiness contribute to AI adoption, their effects are less pronounced compared to infrastructure and workforce readiness. GDP per capita, though positive, has only a marginal impact on AI adoption, indicating that economic strength alone does not guarantee widespread use of AI technologies. The study also provides a country-specific analysis, identifying Germany, Finland, and Ireland as leaders in AI adoption due to their strong digital and human resource foundations. Conversely, Bulgaria and Greece lag behind, primarily due to weaker digital infrastructure and lower levels of workforce readiness. Policy recommendations for these countries include targeted investments in digital infrastructure, education, and workforce training programs, as well as fostering public-private partnerships and supportive regulatory environments for AI development. The findings emphasize the critical role of digital infrastructure and human capital in driving AI adoption. Countries aiming to enhance their AI capabilities should focus on these key areas to remain competitive in the rapidly evolving global economy. JEL: A11, C45, O33, O52