EXPRESS: Artificial intelligence perceptions and experiences among first and second year medical students

BACKGROUND: Artificial intelligence (AI) tools, particularly large language models, are increasingly accessible to medical learners. Early attitudes toward AI may shape how students incorporate these tools into learning and professional development. This study captured first- and second-year medical students' AI familiarity, prior use, and perceptions during orientation week, providing a snapshot of incoming student attitudes. METHODS: A cross-sectional survey was administered to first- and second-year medical students (N = 157) at a single U.S. medical school in August 2024. Data on demographics, AI familiarity, prior use, and perceptions were collected using multiple choice and five-point Likert scale items. Descriptive statistics, Chi-squared analyses, and Fisher's exact tests were used to compare responses between cohorts. RESULTS: Of 108 responses, most students reported slight (42.6%) or moderate (37%) AI familiarity. ChatGPT was the most recognized (95.4%) and used (84.3%) tool. First-year students were significantly more likely than second-year students to have used AI previously, to have used AI during medical school applications, and to plan AI use in medical school (all p < 0.001). Students expressed optimism about AI integration but raised concerns about accuracy (76.9%), clinical thinking (67.6%), and ethics (63%). Over 60% rated ethical AI training as very or extremely important, and 57.4% were uncomfortable with AI=mediated assessment. CONCLUSION: Pre-clinical students anticipate a growing role for AI in medical education and favor structured, workshop-based ethical training. These findings can inform timely curricular planning as AI technologies continue to evolve.