Abstract: OBJECTIVE To explore the innovative measures and effectiveness of applying artificial intelligence (AI) technology in infection prevention and control for nursing professionals, and to identify the main application scenarios, effectiveness and limitations of AI in this context. METHODS A scoping review was conducted by systematically searching PubMed, Embase, Web of Science, CINAHL, Cochrane Library, Scopus, EBSCO, CNKI, Wanfang Data, VIP and CBM databases. Literature was screened based on inclusion and exclusion criteria, followed by thematic analysis focusing on AI technology types, application scenarios, nursing professional involvement and effectiveness evaluation. RESULTS A total of 11 studies were included. The application scenarios of AI in infection prevention and control primarily encompassed disease prevention, detection, prediction, intervention and education. The application forms included perception layer, algorithm layer and decision/application layer. AI technology demonstrated the potential to improve the efficiency and quality of infection prevention and control, and optimize resource allocation. However, limitations such as insufficient technological maturity, high data dependency, limited sample representativeness and privacy-ethical risks were identified. CONCLUSIONS AI technology holds broad prospects in infection prevention and control. By developing collaborative innovation strategies led by nursing professionals and deeply integrating AI with nursing practice, its advantages can be better leveraged. Future research should focus on multi-center evidence-based studies to refine AI functions and assess sustainability in real-world applications.