Faculty perspectives on artificial intelligence’s adoption in the health sciences education: a multicentre survey - Al Zahrani, Eidan M.; Elsafi, Salah H.; Al Musallam, Lenah D.; Alharbi, Abdulwahab H.; Aldossari, Hala M.; Alomar, Ahmed M.; Alkharraz, Zeyad S. (Frontiers in Medicine, 2025)
IntroductionThe integration of artificial intelligence technology into healthcare education has been hampered by a number of difficulties. This study aimed to investigate the faculty’s familiarity and perception towards AI applications in medical education concerning various demographic and professional characteristics.MethodsThis observational study used a validated questionnaire distributed to health sciences colleges’ faculty in Saudi Arabia from January 1 to April 30, 2025.ResultsKnowledge rates among the 293 participating faculty were moderate across all groups with an overall average of 58.9%. Knowledge varied significantly with increasing years of experience and academic qualification (p = 0.000). In general, positive perception rates were generally high across all groups, with an overall average of 74.8%. Only 33.7% reported agreement on the reliability and accuracy of AI-generated outputs. A large proportion of the participants (72.3%) reported disagreement that AI use poses ethical concerns in medical education. Faculty opinions on the impact of AI on academic integrity varied.DiscussionThis study shows that there are still significant gaps in general knowledge, formal training, and ethical understanding, despite the supportive perception score of the health science faculty towards AI integration in medical education. Despite a general lack of knowledge and a lack of curricular content on AI applications, the results show considerable support for incorporating AI into medical education. Institutional readiness for the integration of AI in medical education is strongly influenced by obstacles, including a lack of knowledge, a shortage of skilled faculty, and fear of career threat.