Artificial intelligence adoption and its influence on circular material use: An EU cross-country analysis

This research study examines the relationship between Artificial Intelligence (AI) adoption and Circular Material Use Rate across 27 EU member states (2021-2023). Using panel data econometrics and Random Forest machine learning, it analyzes the direct and non-linear effects of AI adoption on circular economy outcomes. Results show no statistically significant direct impact of AI on circular material use rate (CMUSE) when controlling for economic factors. Resource Productivity emerges as the strongest predictor, with GDP per capita playing a crucial moderating role. The Random Forest model explains 48.58% of CMUSE variance. The study provides evidence that AI investments should align with initiatives of increasement of resource efficiency and with economic development policies. The findings emphasize the need for tailored interventions considering technological readiness and economic capacity variations across EU states, contributing to sustainable development policy design.