Assessing the Readiness for Artificial Intelligence Integration Into Healthcare Among Medical Students in Sumatra, Indonesia

Introduction: Artificial Intelligence (AI) is increasingly applied in healthcare as it helps healthcare workers to improve the quality of care. Medical students should prepare themselves with the competence to properly and ethically use AI, especially in areas with socioeconomic challenges and limited educational resources. This study assessed medical students’ current readiness in healthcare in Sumatra. Methods: This cross-sectional study was conducted on medical students in Sumatra from November ۲۰۲۴ to February ۲۰۲۵. AI readiness was evaluated using the MAIRS-MS questionnaire. Data were analyzed using chi-square for bivariate tests and multivariate logistic regression to identify significant predictors of readiness. Results: Overall, ۱,۰۵۳ respondents from ۲۲ universities in Sumatra were included in this study. Nearly ۷۴.۷% lacked formal AI training, and ۹۰.۹% relied on general tools like ChatGPT. The overall AI readiness mean was ۷۴.۳۶ (±۱۴.۰۳). Students received the highest score in ethics (۱۰.۹۶±۲.۴۶) and ability (۲۸.۲۰±۵.۵۷), but the lowest score in cognition (۲۴.۴۸±۵.۹۲). Prior AI training was the primary predictor for overall readiness (OR=۱.۹۰; ۹۵% CI: ۱.۴۴–۲.۶۱). Coding experience significantly boosted cognitive readiness (OR=۱.۸۴; ۹۵% CI: ۱.۳۳–۲.۵۴), while public university affiliation was strongly associated with higher vision (OR=۲.۲۰; ۹۵% CI: ۱.۷۰–۲.۸۶) and ethical readiness (OR=۲.۱۰; ۹۵% CI: ۱.۶۳–۲.۷۲). Conclusion: Medical students in Sumatra revealed moderate-to-high readiness, particularly in ethics and technical interest, yet lacked foundational cognitive proficiency. Structured curricula, hands-on practice, and early programming exposure are essential. Formal AI training is the key predictor to bridge this "literacy paradox" and ensure effective, ethical clinical integration.