Medical education is rapidly evolving from time-based, teacher-centered models toward competency-focused, learner-centered approaches that integrate technology, clinical simulation, workplace learning, and attention to learners' wellbeing and social accountability. Artificial intelligence (AI), broadly defined as computational methods that perform tasks that would normally require human intelligence, comprehensively and in a very short time. The landscape of medical education is undergoing a significant transformation, driven by the rapid integration of advanced clinical simulation and AI into medical curricula. This narrative review summarizes current global applications, opportunities, and challenges of AI in training the next generation of healthcare professionals. We examine how AI is evolving from a new tool to a core part of the educational system, enabling personalized learning through adaptive platforms, improving clinical reasoning via simulated environments, and offering objective metrics for assessment and feedback. Specific applications such as AI-powered virtual patients, natural language processing for communication skills training, and the analysis of surgical simulation data are discussed. Additionally, the review addresses important ethical issues, including data privacy, algorithmic bias, and the potential for dehumanizing medicine. It emphasizes the urgent need for international collaboration on curriculum development to ensure fair and effective integration of AI in medical education and health practices. While many challenges remain, the potential of AI to create a more efficient, standardized, and student-focused model of medical education worldwide is tremendous, promising to develop a new generation of physicians ready to handle the complexities of modern healthcare.
Elamin et al. (Wed,) studied this question.