Artificial intelligence literacy among U.S. rural medical education students: perceptions, readiness, educational needs, and barriers

Abstract

Artificial intelligence is increasingly integrated into healthcare. However, formal training in medical education remains limited, especially among Rural Medical Education students. This study examined students’ perceptions of artificial intelligence, their readiness to use it, their educational needs, and barriers to integrating it into the curriculum. A cross-sectional anonymous survey was conducted among Rural Medical Education students at the University of Illinois College of Medicine, Rockford. Data collection took place between December 11, 2024, and January 30, 2025. The survey was distributed to 88 enrolled students across four years of medical training. The questionnaire assessed perceptions of artificial intelligence in healthcare, self-reported readiness, educational needs, and barriers. Descriptive statistics and exploratory ordinary least squares analyses identified factors linked to a composite readiness score. With a 59% response rate, students generally view artificial intelligence as a supportive tool rather than a replacement for physicians. Most agreed that it can support clinical decision-making. However, they also expressed concerns about bias and unintended consequences. Although 50% reported formal education in the field, overall exposure was limited. Most students reported minimal (50%) or moderate (36%) exposure, and familiarity with healthcare applications remained low. Self-reported readiness to use artificial intelligence in key clinical tasks was limited. Only 2%-15% of respondents reported high readiness, depending on the task. Familiarity with healthcare applications of artificial intelligence was the only significant factor associated with readiness (B = 0.428, p < 0.001). Students expressed strong interest in hands-on, clinically relevant, and ethically grounded training, particularly in AI fundamentals and clinical applications. However, limited curricular time (63%), ethical concerns (51%), and restricted access to relevant tools (49%) were key barriers. This study provides the first assessment of perceptions, readiness, educational needs, and barriers related to artificial intelligence among Rural Medical Education students in the United States. Although students are receptive to artificial intelligence, their readiness remained limited, particularly for healthcare-specific applications. Familiarity with healthcare applications of artificial intelligence, rather than prior general exposure, was associated with readiness, which remained low across training years. Integrating structured, clinically relevant, and longitudinal training in artificial intelligence into Rural Medical Education curricula may better prepare future rural physicians to use the technology responsibly and effectively.