A Qualitative Analysis of the Current State of Artificial Intelligence in Medical Education

Abstract

Artificial intelligence (AI) is transforming healthcare and medical education, offering opportunities to enhance learning, diagnostic reasoning, and personalized instruction. However, its integration into undergraduate medical education (UME) remains a challenge, necessitating a balance between technological advancements and ethical considerations. This study investigates best practices for incorporating AI into UME curriculum through a qualitative thematic analysis of recent literature. Key themes identified include AI’s potential to improve medical student performance, ethical concerns related to privacy and bias, and the need for expanded AI education to allow for curricular integration. While AI offers significant benefits in medical training, challenges such as academic integrity, patient confidentiality, and the risk of over-reliance on AI highlight the necessity for structured, ethical, and evidence-based AI education. The findings underscore the importance of developing comprehensive curricula that equip future physicians with the knowledge and critical thinking skills required to navigate AI-assisted healthcare responsibly.