Acquired immunodeficiency syndrome (AIDS) is one of the major public health challenges in China, and the current prevention and control efforts have shifted towards the "prevention first" precision intervention. Artificial intelligence (AI) offers new opportunities to reform traditional prevention modes. This paper summarizes the advances in the application of AI in AIDS prevention, focuses on analyzing the current situation of technologies, including machine learning and deep learning, in research and development of tools for risk prediction and intelligent intervention, explores the existing challenges such as interpretability, data privacy, and algorithm fairness, looks forward to the future direction, with a view to providing reference for promoting the deep integration of AI and AIDS prevention field.