Evaluation of cognition, perception, and opinion among faculties and postgraduate medical students regarding artificial intelligence tools in health education and research. A cross-sectional survey. - Panda, Adyasha Anindita; Panda, Dr. Suvendu Kumar; Dash, Dr. Snehasini; Behera, Jayanti Prava (Student’s Journal of Health Research Africa, 2026)
Introduction Artificial intelligence (AI) has substantial transformative potential in enhancing diagnostics, treatment, disease monitoring, health-care delivery, education, and research. Despite these advantages, AI has not yet been formally integrated into the medical curriculum. Therefore, the present study aimed to evaluate the cognition, perception, and opinion of medical teaching faculty members and postgraduate (PG) students regarding the application of AI in medical education and research. Methods This cross-sectional survey was conducted among faculty members and PG residents of MKCG Medical College and Hospital, Berhampur, from September 2024 to December 2024. A structured questionnaire comprising 20 items covering cognition, perception, and opinion was administered. A total score of 100 was allotted, with 5 points assigned to each correct response. Analytical statistics were performed using the Chi-square test to assess associations between scores and sociodemographic variables. A p-value <0.05 was considered statistically significant. Results Most participants were aged 25–40 years (87%) with male predominance (57%). The Department of Pharmacology contributed the largest share (30%), while only 30% had prior exposure to AI-related CME. Cognition item 6 showed the highest correct response rate (71.6%). In the perception domain, 40% strongly agreed across items, and opinion responses demonstrated agreement ranging from 30% to 80%. The mean cognition score was low (22.46 ± 8.63/50), whereas perception (19.44 ± 3.15) and opinion (20.70 ± 2.21) scores were satisfactory. Significant associations were observed only with designation (PGs vs faculty; p = 0.02) and prior AI exposure (p = 0.04). Conclusion: At present, faculty members and postgraduate students have limited knowledge of artificial intelligence but show favourable perceptions toward its integration into medical education and healthcare practice. Recommendation: Integrating artificial intelligence education into the postgraduate medical curriculum through structured programs and workshops will enhance knowledge and promote responsible AI use in clinical practice, research, and medical training.