Generative Artificial Intelligence (AI) in Medical Education: A Narrative Review of the Challenges and Possibilities for Future Professionalism

Abstract

The rapid emergence of generative artificial intelligence (AI) is reshaping the landscape of medical education and healthcare. Unlike traditional AI, which focuses on classification or prediction, generative AI can create novel content-such as clinical notes, patient education materials, and simulated interactions-based on large-scale data. This capacity offers significant opportunities for personalized learning, clinical efficiency, and patient engagement. However, the integration of generative AI also introduces complex challenges, including ethical ambiguity, misinformation, accountability, data privacy risks, and potential erosion of critical thinking skills. These risks are especially salient in educational settings, where future physicians are still developing their professional identities. In this narrative review, we examine the dual role of generative AI as both a transformative tool and a source of ethical and professional disruption. We analyze its benefits and challenges across educational and clinical domains and argue that the traditional model of medical professionalism must evolve in response. Drawing on international literature and diverse cultural contexts in medical education, we propose a redefined framework for AI-era professionalism-one that integrates technological fluency with enduring humanistic values such as empathy, integrity, and accountability. This review offers AI-integrated medical professionalism to prepare future physicians to use generative AI responsibly, ethically, and in service of patient-centered care.

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