<p>Artificial Intelligence (AI) has emerged as a transformative force, driving significant advancements across various domains, including healthcare, finance, manufacturing, and environmental sustainability. By leveraging AI enhances decision-making, optimizes complex processes, and improves operational efficiency, making it an indispensable tool in modern industries. Given these substantial advantages, organizations across all sectors should actively adopt AI-driven methodologies to enhance performance, reduce costs, and promote long-term sustainability. One critical area where AI can make a profound impact is the circular economy, a sustainable economic model that emphasizes resource efficiency, waste minimization, and the continual reuse of materials. As global resource scarcity and environmental degradation intensify, the need for smarter, data-driven solutions to optimize resource utilization and improve recycling processes becomes increasingly urgent. AI technologies can significantly enhance circular economy (CE) practices by enabling more efficient material recovery, reducing waste, and supporting closed-loop production systems. Numerous researchers have explored the potential of AI in advancing CE initiatives, demonstrating its ability to facilitate smarter waste management, energy efficiency, and sustainable product design. However, despite the growing academic interest, the existing research remains fragmented, with studies scattered across different disciplines and lacking a cohesive structure. This fragmentation hinders a comprehensive understanding of the field’s evolution, key research themes, and future opportunities. To address this gap, this study conducts a comprehensive and systematic bibliometric analysis to map the intellectual structure of AI applications in the circular economy, identifying core research areas, influential publications, and emerging trends. Our analysis examines 691 records extracted from the Web of Science database, encompassing contributions from 2878 researchers between 2012 and 2024. Using advanced bibliometric techniques we uncover the evolution of this interdisciplinary field, highlighting pivotal studies, collaborative networks, and underexplored research avenues. The findings of this study provide valuable insights for academics, policymakers, and industry practitioners, offering a structured overview of AI’s role in advancing the circular economy. By identifying key trends and knowledge gaps, this research contributes to a more systematic understanding of how AI can be harnessed to foster sustainability, optimize resource flows, and accelerate the transition toward a circular economic model. Ultimately, this study not only consolidates existing knowledge but also paves the way for future research directions in this rapidly evolving domain. </p>