In response to the challenges posed by the profound integration of generative artificial intelligence(AI)into medical education,this consensus proposes a logically coherent,medically distinctive,forward-looking,and operable AI proficiency framework for medical educators(competency items of medical educators’ AI proficiency,CAIP-ME).Through systematic literature review,preliminary framework construction,multiple rounds of expert pre-study,and a structured Delphi method involving extensive consultations with 60 interdisciplinary experts,the core competency items and assessment standards for AI proficiency among medical educators were demonstrated and calibrated.The framework encompasses five core dimensions and 25 specific competency items.The five dimensions are value recognition and ethical foundation,technical understanding and tool application,teaching integration and innovative practice,learning assessment and precise empowerment,and professional development and ecosystem co-construction.Competency items are categorized into 11 foundational competency items essential for all educators and 14 developmental competency items for those pursuing excellence.Each competency item is described in terms of its conceptual definition and key behavioral manifestations,accompanied by observable assessment indicators.This consensus aims to provide a scientific basis for the professional development of medical educators and the faculty building in medical institutions,while establishing a key reference standard for educator competency development in the context of digital transformation in medical education.