Navigating AI with pedagogical purpose: Toward an anatomy‐centered framework for AI ‐enhanced learning

Artificial Intelligence (AI) has emerged as a transformative force in medical education, enabling customized, feedback‐rich, and immersive learning experiences. Anatomy education, as a discipline that is simultaneously visual, spatial, and clinically foundational, occupies a distinctive position within this technological landscape. Although current literature addresses AI's potential benefits and ethical concerns in medical and anatomical contexts, a critical gap exists regarding pedagogical frameworks specifically tailored to anatomy education. Most existing AI frameworks have been developed for general educational contexts and have not been articulated for discipline‐specific domains such as anatomy. This article identifies and explores this pedagogical gap by proposing an Anatomy‐AI Integration Framework that situates AI technologies within the cognitive, psychomotor, and affective demands of anatomy education. Drawing from existing literature, clinical education frameworks, and advances in AI‐assisted simulation, we present a roadmap to guide AI integration that is pedagogically intentional, clinically relevant, and grounded in systematic analysis of anatomy's unique learning demands. The Anatomy‐AI Integration Framework comprises four domains: Theoretical Grounding, Competency Alignment, Embodied Learning, and Ethical Engagement, with a comprehensive validation pathway to move from conceptual model to evidence‐based practice.