BACKGROUND: As artificial intelligence (AI) technologies become increasingly embedded in healthcare, the readiness of future physicians to adopt these tools is of growing concern. While prior studies have examined predictors of technology acceptance, less is known about the conditions that are essential, rather than merely influential, for medical students to form strong intentions to use AI-based health technologies (AIHTs) in clinical practice. This study addresses this gap by identifying both necessary and sufficient conditions for AI adoption intentions among medical students. METHODS: Drawing on the Consolidated Framework for Implementation Research and the COM-B model (Capabilities, Opportunities, Motivation-Behavior), the study surveyed 177 students at a Canadian medical school. Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) were applied to explore how students' familiarity with AIHTs, hands-on experimentation, perceived curricular importance, and beliefs about AI's role in future medical tasks influence their adoption intentions. RESULTS: The findings reveal that two conditions are necessary for strong AI adoption intentions: (1) a belief in the future relevance of AIHTs to medical tasks, and (2) a positive attitude toward the inclusion of AIHTs in the medical curriculum. The fsQCA further identifies two distinct "AI profiles" or configurations that are sufficient to foster strong adoption intentions, illustrating multiple pathways to readiness. CONCLUSION: These results highlight the importance of curricular design that not only builds technical familiarity but also fosters motivation and belief in AI's clinical relevance. The study offers practical insights for medical educators aiming to prepare students for a digitally integrated healthcare environment.
Ringeval et al. (Thu,) studied this question.