Purpose – There is a lack of studies exploring how artificial intelligence (AI) enables operational excellence, which justifiesthe successful integration of AI and how it can be connected to circular economy (CE). Thisstudy aims to examine how AI-driven operational excellence enables resource utilization to facilitate the CE transition.

Design/methodology/approach – In total, 12 enablers were identified through literature, and using the FuzzyDEMATEL technique, their cause-effect analysis and prominence rating are conducted.

Findings – “Improved transparency, coordination and trust”, “improved forecast of demand and other uncertain supply chain (SC) parameters”, “accurate real-time information flow”, “decision support for specialized CEbased business models” and “improved eco-accounting of SC impacts” are identified as the most prominent enablers.

Originality/value – These enablers will help enterprises identify specific use cases of AI in CE-based business models, thereby accelerating adoption and improving resource utilization and circularity. The study’s findings will assist managers and practitioners in understanding the operational aspects of how AI contributes to enhanced resource circularity.