Assessing Perceptions and Exposure to Artificial Intelligence Among Medical Educators and Clinicians in Saudi Arabia:...

Artificial intelligence (AI) is transforming healthcare through advances in diagnostics and decision-making, yet most studies have focused on medical students' perceptions, with limited attention to medical educators and practicing clinicians. Understanding these perspectives is critical for developing curricula that prepare future physicians for AI-enhanced practice. This study investigated AI awareness, exposure, and perceived impact among medical educators, interns, residents, specialists, and consultants in Saudi Arabia. A cross-sectional study was conducted using a validated online survey distributed to several Saudi medical schools and hospitals. The survey collected demographic data, prior AI education, self-rated AI knowledge, and interest in AI. The participants also rated their ability to list clinically relevant AI applications, assessed AI's expected influence on various specialties, and indicated whether training in AI concepts would be beneficial. Group differences were analyzed using chi-square tests, ANOVA, and logistic regression, controlling for age and sex. Among the 229 respondents (60 medical educators, 78 interns/residents, and 91 specialists/consultants), medical educators were more likely to report the ability to list AI benefits (63.3% vs. 38.5% and 39.6%) and to express ethical concerns about AI use in healthcare (76.6% vs. 51.3% and 51.6%) compared to the other groups. Only 32.3% reported receiving formal AI education, with most gaining knowledge through informal sources such as the media. Radiology and pathology were identified as the specialties most likely to be transformed by AI. Overall, perceptions of AI among medical educators and clinicians revealed a strong interest but limited formal training. Despite enthusiasm across all groups, the participants relied on informal sources and lacked foundational knowledge on AI. These findings highlight the potential importance of embedding structured AI education into medical curricula and residency training programs to support preparedness for AI-integrated clinical care.