Saudi Medical Students' Perceptions and Attitudes of Integrating Generative Artificial Intelligence Integration in Medical Education: A Cross‐Sectional Study
TL;DR
Saudi medical students express strong interest in GenAI—particularly for basic sciences and simulation—but perceive it as complementary rather than superior to human instruction, reflecting learner perceptions.
Abstract
ABSTRACT Background and Aims Generative Artificial Intelligence (GenAI) has catalyzed a transformation in medical education. Understanding learners' perceptions is essential to guide their responsible integration into curricula. Methods A cross‐sectional survey was administered to 1039 undergraduate medical students across Saudi Arabia. A purpose‐developed, pilot‐tested instrument (Cronbach's α = 0.71 for dichotomous items) assessed students' familiarity with computational language models, perceptions of their educational utility, and attitudes toward technology‐enhanced pedagogical approaches. Descriptive statistics, Kolmogorov–Smirnov testing for normality, and multivariable binary logistic regression (two‐sided, α = 0.05) were performed using IBM SPSS Statistics v28.0. Results Among 1039 participants (64.3% male; median age 22 years [IQR 20–24]), 57.2% (595/1039) reported familiarity with computational language models in medical education, and 70.1% (728/1039; 95% CI: 67.2–72.9) supported curricular integration. A strong majority (86.4%; 898/1039; 95% CI: 84.2–88.4) anticipated impact on the future of medical education. While 73.4% (763/1039; 95% CI: 70.6–76.0) perceived benefit for basic science education, only 41.6% (432/1039; 95% CI: 38.6–44.6) recognized utility in clinical skills training. Only 29.8% (310/1039; 95% CI: 27.0–32.7) considered these tools superior to human instruction. Key concerns included distrust in output reliability (52.6%; 547/1039; 95% CI: 49.5–55.7) and awareness of reference fabrication (64.0%; 665/1039; 95% CI: 61.0–66.9). Conclusion Saudi medical students express strong interest in GenAI—particularly for basic sciences and simulation—but perceive it as complementary rather than superior to human instruction. Findings reflect learner perceptions, not measured educational effectiveness. Implementation should prioritize reliability, ethical use, and preservation of humanistic competencies.