Abstract Medical AI education remains fragmented, specialty-skewed, and lacks longitudinal structure, particularly for generalist physicians. Through an integrative review of 23 peer-reviewed articles (2016–2025), we identified three structural gaps: short-term interventions without reinforcement, procedural-field bias, and consistent under-representation of the Affective domain. We present AI-PACE (Psychomotor, Affective, Cognitive, Embedded), a Bloom’s Taxonomy-grounded framework organizing AI competencies longitudinally across undergraduate, graduate, and continuing medical education.
McGrath et al. (2026) studied this question.