Knowledge, Attitudes, and Practices [KAP] toward Artificial Intelligence in Medical Education among Medical Students and Teachers: A Cross-Sectional Survey

Artificial intelligence [AI] is shaping the delivery of teaching, learning, and clinical training. This is transforming Medical education rapidly. The application and awareness of AI in medical students and faculty from developing nations such as India have not been widely studied. This survey study was performed at Datta Meghe Institute of Higher Education & Research, Maharashtra. We tried to assess how students and teachers view and use AI in medical education. The pre-validated questionnaires were provided to participants. In total, 271 people [156 students and 115 teachers] responded to the Google form questionnaire. The study used Chi-square or Fisher’s Exact tests for categorical data and the Mann–Whitney U test for Likert-scale responses. Teachers had more formal training in AI, but students used AI-based educational tools more often [p < 0.001]. We concluded that students were generally more enthusiastic, trusting, and dependent on AI for learning. On the other hand, teachers were more cautious. They raised ethical concerns along with highlighting possible negative effects on clinical skills [all p < 0.001]. In case of unexpected clinical situations, both groups were uncertain about the reliability of AI. The findings suggest notable differences in perceptions of AI between students and teachers. This highlights the need for structured training in AI literacy and ethics for both groups. Both students and teachers show a clear difference regarding the use of AI in medical education. Structured AI training is still uneven, especially among students. AI should complement traditional teaching, not replace it.