Hitherto, the circular economy (CE) has been identified as another innovative tool for enhancing sustainability through effective management of wastes, optimum use of resources, and development of closed-loop systems. The adoption of CE models has revealed several opportunities for the adaptation of artificial intelligence (AI) to improve sustainable business process management (SBPM). In the spirit of this paper, the following will critically let us understand the application of AI in optimizing risks for effective CE practices: waste management and resource optimization, predictive maintenance, and efficient supply chain. It discusses how the use of Oracle artificial intelligence technologies, including machine learning, analytics, and computer vision, disrupt, define, and improve business processes to achieve sustainable performance. This paper reviews best practices of AI-based CE adopted across various sectors, as well as providing environmental, economic, and operational impact. Other issues which are explained include the technical, organizational, and ethical limitations which are also followed by future prospects of AI-driven CE models. This review also demonstrates how AI can play a role in increasing the speed of going green and the circular economy move.