<p>This systematic literature review synthesises recent peer‑reviewed research on Big Data analytics, Artificial Intelligence, Blockchain, and the Internet of Things within the context of the circular economy. The review is based on a search and screening process guided by the PRISMA framework, using studies retrieved from the Scopus database. The review identifies three principal patterns. First, Artificial Intelligence and the Internet of Things represent the most mature and widely deployed technologies. They are primarily utilised for real‑time monitoring, predictive maintenance, process optimisation, and traceability across circular value chains. In comparison, Blockchain and Big Data are emerging technologies that are incorporated less consistently. Second, the intensity and configuration of digital support vary significantly across different sectors. The manufacturing, electronics, and waste management ecosystems demonstrate the most advanced applications, whereas other resource‑intensive and public‑oriented sectors remain in experimental or fragmented stages. Third, five interdependent categories of barriers influence the large‑scale implementation of these technologies. These barriers are technological, economic, regulatory, operational, and cultural in nature. They not only constrain adoption but also indicate potential opportunities for policy intervention, capacity building, and the development of new circular business models. By integrating these insights, the paper presents a unified framework that explains how the combined use of Artificial Intelligence, the Internet of Things, Blockchain, and Big Data can achieve circular economy outcomes through enhanced information flows, material tracking, and improved coordination among stakeholders.</p>