Objective To explore the application model and value of artificial intelligence (AI) in interventional vascular surgery education. MethodsSupported by AI technologies, a teaching framework was established from three dimensions: personalized learning and assessment, surgical operation training, interdisciplinary collaboration, and lifelong learning. Combined with clinical cases, the teaching process was refined, use quantitative assessment and multimodal simulation training to achieve personalized teaching and clinical skills improvement. ResultsLearners’ data profiles can be generate by AI through dynamic capability evaluation, accurately deliver multimodal resources, and optimize personalized assessment. With VR/AR simulation and staged training, learners’ operation accuracy, hand stability, and complication management ability can be improved. The virtual multidisciplinary platform and intelligent literature recommendation enhanced interdisciplinary collaboration and knowledge updating. This model can improve teaching efficiency and assessment objectivity, yet faced challenges including data dependence, insufficient algorithm interpretability, and high cost. ConclusionsAI provides a personalized, precise, and standardized pathway for interventional vascular surgery education, effectively elevating teaching quality and clinical skills. Further efforts are needed to perfect data standards, optimize algorithms, and strengthen security specification to promote the safe and effective application of AI in medical education.