Use of Artificial Intelligence in Anatomy

Artificial intelligence (AI) and related digital technologies (virtual reality, augmented reality, virtual dissection tables, adaptive learning systems) are increasingly applied to undergraduate anatomy education to address limitations of conventional teaching (cadaver availability, time constraints, variable teaching quality) and to enhance spatial understanding and clinical integration.This narrative review synthesizes contemporary literature on AI-based anatomy education, searching PubMed/PMC, Google Scholar and institutional guidance (years 2000-2025).Inclusion criteria were studies, reviews and reports addressing AI/VR/AR/VDT/3Dmodels for undergraduate anatomy learning; non-English and animal-only reports were excluded.Key outcomes examined were spatial comprehension, retention, examination performance, student engagement and reported harms or limitations.Across systematic reviews, randomized and observational studies, and institutional reports, AI-assisted tools consistently improved learner engagement and 3-D spatial understanding and provided valuable radiology-anatomy integration; however, evidence for superiority in long-term knowledge retention and high-stakes exam performance is mixed, and heterogeneity in study designs and outcome measures is substantial.Barriers include cost, infrastructure, faculty training and risk of reduced cadaver exposure.We conclude that AI is a powerful adjunct to-but not a replacement for-cadaveric dissection; structured, evidence-based integration with clear learning objectives is recommended.