Introduction: The incorporation of artificial intelligence (AI) into the supply management of sanitary requirements has managed to optimize a series of processes, such as the purchase of supplies, medicine, equipment, distribution management, inventory management, and prediction of demand, thus improving operational efficiency in the health sector. Objective: To identify AI applications in the supply management of health supplies and medical devices worldwide. Methodology: Systematic review, based on Moher’s [22] stages, of articles published between 2019 and 2024 in electronic databases such as PubMed, Web of Science, Scopus, and Scielo. AI applications are analysed according to the stages of the supply chain operations reference (SCOR) model. The articles are evaluated according to their methodological quality using the Mixed Methods Appraisal Tool (MMAT). Results: Eight relevant studies are selected that address the use of AI, machine learning (ML), deep learning (DL), the Internet of Things (IoT), and blockchain. AI and associated technologies are revealed to improve efficiency, traceability, and inventory management; optimize product delivery; and reduce risk. These advances are observed mainly in the planning, supplying, producing, and delivering stages of the SCOR model. Discussion: Although the implementation of AI in the medical supply chain has obvious benefits, challenges, such as the need to deepen the “return” stage, which is not sufficiently addressed in the studies reviewed, are identified in its application. Conclusions: The integration of AI in the supply chain of medical supplies facilitates more efficient and adaptable management, guaranteeing the continuity of supply and improving health sector operations. Future studies should focus on the “payback” stage and explore additional AI applications in this field.