The shift toward a circular economy has become an essential focus for sustainable development, where the goal is to minimize waste and make the most of resources. In this context, Artificial Intelligence (AI) and the Internet of Things (IoT) play pivotal roles in transforming traditional supply chain management (SCM) practices into more efficient, sustainable, and environmentally friendly systems. This paper explores the integration of AI and IoT in green supply chain management (GSCM) to facilitate the circular economy paradigm. AI technologies, such as machine learning, predictive analytics, and optimization algorithms, work synergistically with IoT-enabled sensors and devices to provide real-time data, enhance decision-making processes, and streamline operations from production to recycling. By utilizing real-time monitoring, data-driven insights, and predictive modeling, businesses can reduce waste, improve resource utilization, and ensure the circular flow of materials. The paper discusses the potential benefits of AI and IoT in reducing carbon footprints, enhancing recycling processes, and fostering sustainable consumption and production patterns. Additionally, it highlights the challenges and barriers faced by organizations in adopting these technologies, such as high initial costs, data security concerns, and technological complexity. Case studies and examples from various industries are presented to demonstrate the practical application of AI and IoT in green SCM, ultimately contributing to a circular economy that aligns with global sustainability goals. The study concludes with a forward-looking perspective on the future potential of AI and IoT in driving green supply chains toward a more sustainable and circular global economy.