The rapid advancement of Artificial Intelligence (AI) and Digital Twin (DT) technologies has invigorated the field of Structural Health Monitoring (SHM) with novel technical dynamism. By constructing high-fidelity virtual models of physical structures, DT technology, when integrated with AI, enables real-time reflection of structural health status and predictive analytics. The deep integration of these two technologies can significantly improve the accuracy and decision-making efficiency of SHM. To systematically review the research progress and application status of integrated DT and AI technology in SHM, this paper first elaborates on the fundamental concepts of DT and AI and their application value in the field of SHM. Then comprehensively discusses the research status of SHM and early warning technology integrating DT and AI from five dimensions: Onshore Engineering Structures, Underground Engineering Structures, Highway and Bridge Structures, Offshore Engineering Structures, and Disaster Early Warning and Assessment of Engineering Structures. Finally, it summarizes the current research progress and prospects future development directions, aiming to provide a valuable reference for subsequent research and engineering practice in this fields.