Transformation and Reinvention: A Comprehensive Analysis of Frontiers and Trends in AI-Empowered Medical Education by 2025

Abstract

In 2025, the rapid iteration of generative artificial intelligence (AI) and large language models (LLMs) has profoundly reshaped the ecosystem of medical education. This review systematically synthesizes the latest advances in AI-enabled medical education through an analysis of more than 150 core articles published in 2025 and indexed in the PubMed database. The paper first evaluates the current state of AI literacy among medical students and educators worldwide, revealing a pervasive “cognition–practice” misalignment. It then examines innovative application models of AI in curriculum integration, the development of intelligent educational tools (e.g., virtual patients and personalized tutoring systems), and AI-enhanced assessment and feedback mechanisms. Ultimately, the review examines key ethical challenges, including algorithmic bias, academic integrity, and data privacy. The findings suggest that future medical education should establish a human-centered framework of human–AI collaboration, with particular emphasis on cultivating physicians’ critical thinking and humanistic values. This review aims to provide both theoretical foundations and practical guidance for the development of a new paradigm in intelligent medical education.

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