Generative Artificial Intelligence in Medical Education: Opportunities, Challenges, Professional Implications and a Four-Pillar Readiness Framework for Responsible Integration

Generative artificial intelligence (GenAI) is rapidly transforming medical education by introducing new opportunities for personalized learning, simulation-based training, automated feedback, and clinical decision support. Large language models and multimodal AI systems are increasingly used by both students and clinicians, with recent reports showing adoption rates of 49–89% among medical students and approximately 66–71% among physicians. These technologies may improve accessibility, learner autonomy, and educational efficiency; however, their rapid integration also raises important concerns related to reliability, hallucinations, algorithmic bias, academic integrity, privacy, and ethical accountability. Beyond these technical limitations, growing evidence suggests that excessive reliance on GenAI may promote cognitive offloading, weaken independent reasoning, and contribute to cognitive fatigue. Additional concerns include the potential for “dehumanisation drift,” in which reduced human interaction may negatively influence empathy, professional identity formation, and relational competence. This review critically examines the educational opportunities, cognitive risks, ethical challenges, and professional implications of generative AI in medical education. To support responsible implementation, we propose a Four-Pillar Readiness Framework for Responsible GenAI Integration (4PRF), emphasizing student readiness, faculty readiness, institutional readiness, and professional readiness. The future of medical education should not be defined by the replacement of physicians with AI, but by responsible human–AI collaboration that preserves critical thinking, ethical judgment, and the humanistic foundations of medicine.