Abstract: To systematically investigate the process by which the integration of artificial intelligence and the Internet of Things (AIoT) drives supply chain resilience to evolve from segmented management to integrated full-lifecycle collaboration, a systematic review is conducted on the research progress of AIoT-empowered supply chain resilience. First, theories of supply chain risk, resilience, and collaborative management are systematically reviewed, and an analytical framework is constructed for risk transmission pathways and strategies for pre-event prevention and post-event response. Second, using Web of Science and Engineering Village as data sources, 720 relevant publications are identified after screening. CiteSpace is employed to analyze publication trends, collaboration networks, and keyword co-occurrence, and it is found that the 720 publications form 17 thematic clusters. AIoT, through its four core mechanisms-data sensing and fusion, joint forecasting and risk sharing, distributed decision-making, and dynamic coordination-builds a progressive closed loop of "data visibility, collaborative cognition, joint decision-making, and feedback learning." In contrast to existing studies that mostly focus on a single technology or a single supply chain stage, supply chain resilience and complex product lifecycle collaboration are incorporated into a unified analytical framework, and the complete pathway through which AIoT bridges cross-stage information flows, coordinates heterogeneous resources, and enables multi-actor value co-creation is systematically revealed.