A systematic review identified 14 studies on the integration of Artificial Intelligence (AI) in medical education from databases including PubMed and Scopus. After screening 150 studies, researchers assessed methodologies such as scoping reviews and qualitative case studies. The studies, spanning countries like the USA, India, and Germany, demonstrated AI’s applications in admissions, diagnostics, and teaching. Key themes included stakeholder perceptions, curricular innovations, and ethical challenges, highlighting the importance of integrating AI literacy and ethics within teaching frameworks. A risk of bias assessment revealed variability in methodological rigor, with most studies showing moderate risk due to incomplete reporting. Despite widespread interest, practical implementation barriers were noted, particularly in low- and middle-income countries. The findings led to the development of a Comprehensive Framework for Integrating AI in Medical Education, tailored for diverse contexts, emphasizing ethical preparedness and curriculum redesign. This framework aims to guide structured, evidence-based AI education in medical training.
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