The transition from a linear to a circular economy (CE) emphasizes sustainable production and consumption by promoting resource efficiency, reuse, and recycling. This systematic literature review explores how artificial intelligence (AI) technologies, particularly machine learning (ML), can enhance various stages of CE, including raw material extraction, product design, manufacturing, distribution, and waste management. A total of 14 peer-reviewed studies published between 2020 and 2024 were analyzed, identifying key applications and trends in AI-driven CE practices. Findings highlight that AI optimizes processes such as sustainable concrete design, CO2 tracking across supply chains, smart water distribution networks, and automated waste sorting. Although AI presents significant opportunities to increase resource efficiency and reduce waste, challenges remain, such as high computational requirements and the need for quality data. This review underscores the potential of AI as a critical enabler of circular strategies, while also pointing to the importance of further research to address current limitations.