<p>The rapid emergence and global spread of infectious diseases pose significant challenges to public health. In recent years, artificial intelligence (AI) technologies have shown great potential in enhancing our ability to prevent, detect, and control infectious disease outbreaks. However, as a growing interdisciplinarity field, a gap exists between AI scientists and infectious disease biologists, limiting the full potential of AI in this field. This review provides a comprehensive overview of the applications of AI in infectious diseases, focusing on the progress along the four stages of outbreaks: pre-pandemic, early pandemic, pandemic, and periodic epidemic stages. We discuss AI methods in early detection and risk assessment, outbreak surveillance, diagnosis and control, and understanding pathogenic mechanisms. We also propose the primary limitations, challenges, and potential solutions associated with AI tools in public health contexts while examining crucial considerations for future enhanced implementation. By harnessing the power of AI, we can develop more precise and targeted strategies to mitigate the burden of infectious diseases and improve global health.</p>