軍事医学教育における人工知能能力の埋め込み：縦断的フレームワーク

Artificial intelligence (AI) is rapidly transforming healthcare delivery, logistics, and operational decision-making across the Military Health System (MHS). Artificial intelligence-enabled tools now influence diagnosis, documentation, casualty prediction, mission planning, evacuation prioritization, and force health protection in both garrison and deployed environments. Despite this accelerating change, AI education in undergraduate medical education (UME) remains fragmented and largely confined to electives or isolated workshops, creating a readiness gap for future military medical officers. Current approaches do not provide students with the skills necessary to interpret AI-enabled decision-support tools, recognize algorithmic bias, or apply these technologies in austere, bandwidth-limited settings where command authority and operational priorities may shape clinical judgment. This commentary proposes a longitudinal, competency-based framework for integrating AI education across the pre-clerkship, clerkship, and post-clerkship phases of UME. Grounded in the updated 2024 Foundational Competencies for Undergraduate Medical Education, the framework embeds AI-related sub-competencies within existing domains-Patient Care, Systems-Based Practice, Interpersonal and Communication Skills, Professionalism, and others-rather than establishing AI as a standalone topic. A scaffolded progression rooted in Competency Based Medical Education enables students to build foundational knowledge during pre-clerkship, apply AI tools in clinical documentation and decision-making during clerkship, and refine ethical judgment, privacy awareness, and operational readiness as they prepare to transition to graduate medical education. Successful implementation will require intentional curriculum design, faculty development, IT governance, and alignment with existing military training pipelines, including operational medicine field exercises. Embedding AI across the curriculum has direct implications for force readiness. Military medical officers who can evaluate AI outputs, integrate algorithmic tools in austere environments, and communicate uncertainty to patients and line leadership will be better prepared to support casualty care, mission planning, and operational decision-making in large-scale combat operations. Early assessed and sustained competency ensures both patient safety and mission success in future landscapes of war.