Artificial Intelligence-Driven Simulation Training in Medicine: A Contemporary Narrative Review

Artificial intelligence (AI) is increasingly transforming healthcare simulation training by enhancing learning experiences, optimizing skill acquisition, and providing personalized feedback. This review synthesizes current evidence on AI-driven simulation training across medical disciplines, exploring its applications, advantages, limitations, and future directions. Based on a comprehensive PubMed search identifying relevant literature, this review integrates the most significant contributions to provide a critical and integrative perspective. AI-driven simulation training enhances medicine by improving communication skills, surgical proficiency, diagnostic accuracy, and clinical decision-making. AI-powered tools provide real-time feedback, personalized learning, and standardized assessments across various healthcare disciplines. Despite its benefits, challenges such as data privacy, high costs, and ethical concerns hinder widespread adoption. Future efforts should focus on standardization, collaboration, and ethical integration to optimize AI’s role in medical training. AI-driven simulation training is transforming medicine by providing personalized, data-driven learning and enhancing skill development. While challenges like cost, data security, and ethics persist, ongoing research and collaboration can facilitate AI’s seamless integration. With continued advancements, AI holds the potential to improve competency and patient safety in healthcare training.

Keywords: Artificial intelligence, medical training, medicine, simulation training