The application of artificial intelligence (AI) technology in healthcare-associated infection prevention and control deepens continuously. It demonstrates a potential for achieving precise prevention and control of infection through data integration, model construction, and dynamic analysis, and provides scientific support for optimization of decision-making in relevant departments. However, the application of related technologies still faces multiple challenges, such as data quality, system compatibility, and adaptation to actual scenarios, which limits its comprehensive promotion in clinical settings. Based on this, this study systematically summarizes the research progress of AI application in infection prediction, diagnosis support, behavior optimization, and resource management in recent years, deeply analyzes its key technical advantages and limitations, and proposes improvement strategies for existing problems and future development directions, with a view to providing theoretical support and practical refe-rences for the intelligent transformation of infection prevention and control in hospitals in China.