Medical education; Faculty development; Artificial intelligence literacy; Competency framework; Expert consensus (Preprint)

Abstract

<sec> <title>UNSTRUCTURED</title> In response to the profound challenges posed by the deep integration of generative artificial intelligence (AI) into medical education, this consensus statement presents, for the first time, a coherent, medically distinctive, forward-looking, and actionable AI literacy framework for medical educators. Developed through systematic literature review, preliminary framework construction, multiple rounds of expert pre-consultation, and a structured Delphi method involving 60 interdisciplinary experts, the framework identifies and validates core competencies and their observable indicators. It comprises five key dimensions and 25 specific competencies , namely: (1) Value Awareness and Ethical Foundations, (2) Technical Understanding and Tool Application, (3) Pedagogical Integration and Innovative Practice, (4) Learning Assessment and Precision Empowerment, and (5) Professional Development and Ecosystem Co-Construction. The 25 competencies are categorized into 11 "foundational competencies" -- essential for all medical educators -- and 14 "developmental competencies" for those pursuing excellence. Each competency is defined by its conceptual scope and key behavioral indicators, accompanied by observable assessment metrics. This consensus aims to provide a scientific foundation for faculty development in medical education and establish a critical reference standard for building educator capacity amid the ongoing digital transformation of medical education. </sec>

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