Integration of Artificial Intelligence into Medical Student Learning: A Cross-Campus Analysis of Student Use and Perceived Educational Impact

Abstract Background: Artificial intelligence (AI) is increasingly used by medical students to support their learning. Despite its growing use, how students incorporate AI into their studies and what educational benefits they perceive remain unclear. This study examined the prevalence, patterns, and perceived educational benefits of AI use among osteopathic medical students across three campuses. Methods: Existing data from a cross-sectional survey of first- and second-year osteopathic medical students were analyzed across the Philadelphia, Georgia, and South Georgia campuses of the Philadelphia College of Osteopathic Medicine (PCOM). The questionnaire assessed AI use, frequency, platforms utilized, educational applications, perceived educational benefits, and self-reported understanding of AI. Descriptive statistics were used to characterize responses, with additional inferential analyses examining differences in AI use and associations between frequency of use and perceived educational benefit. Results: Among 160 respondents, 145 (90.6%) reported using AI to support medical-school learning. ChatGPT was the most used platform. AI was most frequently used to clarify difficult concepts, generate practice questions, and summarize educational material. Students reported particularly favorable perceptions of AI for conceptual understanding, study efficiency, and overall learning quality, while perceived benefits for retention and clinical reasoning were less pronounced. Greater frequency of AI use was associated with greater perceived educational benefit. Conclusions: AI was widely integrated into the learning practices of surveyed preclinical osteopathic medical students. Students primarily used and valued AI for conceptual understanding and learning efficiency, with less emphasis on clinically oriented applications. These findings highlight the need for medical schools to develop educational strategies and guidance supporting responsible, evidence-informed AI use. Longitudinal studies incorporating objective academic and clinical outcomes are needed to determine whether perceived benefits translate into measurable improvements in learning.