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Artificial intelligence use, perceptions, and educational needs among medical undergraduates at a Sri Lankan medical faculty: a cross-sectional survey

Year: 2026

Type: article

Abstract: Background Artificial intelligence (AI) is rapidly transforming medicine, yet medical curricula, particularly in low- and middle-income countries, have not systematically integrated AI competencies. Understanding medical students' AI use, competence, and perceptions is essential for evidence-based curriculum development. Objective To investigate AI tool usage, self-rated AI competence, and attitudes towards AI in medical education, physician roles, and patient care among medical undergraduates at the Faculty of Medicine, Sabaragamuwa University of Sri Lanka (SUSL), and to compare findings across year groups and gender. Methods A cross-sectional online survey was conducted among Years 1–5 medical undergraduates at SUSL in May 2025. The questionnaire, adapted from previously published international surveys, assessed demographics, AI tool usage, self-rated competence, and 12 Likert-scale attitudinal items covering curriculum integration, physician roles, and patient care. Descriptive statistics, Kruskal–Wallis H-tests, Mann–Whitney U-tests, and chi-square tests were used for analysis. Results A total of 369 responses were analysed. AI adoption was almost universal (99.2%; 366/369). ChatGPT was the most frequently used tool (98.1%), followed by Google Gemini (34.9%), DeepSeek (20.2%), and Microsoft Copilot (6.2%). The main uses of AI were subject reference (89.3%), general information retrieval (72.9%), assignment assistance (50.8%), and writing improvement (39.6%). ChatGPT showed the highest self-rated competence, with 92.4% reporting good or higher competence. Among AI-supported medical applications, Medscape was used by 77.9% of respondents, followed by UpToDate (37.4%) and WebMD/WebMD Symptom Checker (15.4%). Most students agreed that AI could enhance learning in preclinical (85.1%), paraclinical (77.8%), and clinical (68.6%) subjects. Significant differences across year groups were observed for attitudes towards curriculum integration (Kruskal–Wallis H = 29.27, p < 0.001) and AI replacing physician tasks (H = 13.23, p = 0.010), with preclinical students expressing more favourable attitudes. Conclusions Medical undergraduates demonstrated near-universal AI adoption despite limited formal training. Preclinical students were more receptive to AI integration than clinical students. These findings support the integration of structured, ethically grounded AI education into undergraduate medical curricula to promote the safe, effective, and responsible use of AI in future clinical practice.

Source: BMC Medical Education

DOI: 10.1186/s12909-026-10496-0

Authors: A.M.S.U. Andadola, W.K.M.M.M. Walallawita, P.D.V.M. Perera, S.N.J.K. Mendis

Institution: Sabaragamuwa University of Sri Lanka

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Quality education, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,990