Year: 2026 | Month: June | Volume: 16 | Issue: 6 | Pages: 256-266
DOI: https://doi.org/10.52403/ijhsr.20260629
Artificial Intelligence in Medical Education: A Cross-Sectional Study of Awareness, Perceptions, and Adoption Barriers among Undergraduate Medical Students in India
Anjani Kumar Srivastava1, Anjali Singh2, Aparnesh Pandey3, Ganesh Chandra Satapathy4
1Associate Professor, Department of Community Medicine, United Institute of Medical Sciences, United University, Prayagraj, Uttar Pradesh, India.
2Associate Professor, Department of Obstetrics and Gynecology, United Institute of Medical Sciences, United University, Prayagraj, Uttar Pradesh, India.
3Assistant Professor, Department of Community Medicine, United Institute of Medical Sciences, United University, Prayagraj, Uttar Pradesh, India.
4Professor, Department of Anesthesia, United Institute of Medical Sciences, United University, Prayagraj, Uttar Pradesh, India.
Corresponding Author: Anjani Kumar Srivastava
ABSTRACT
Background: Artificial intelligence (AI) is revolutionising healthcare, but its integration into Indian undergraduate medical curricula remains nascent. Understanding student perspectives is critical for effective pedagogical reform.
Objectives: This study aimed to assess AI awareness and knowledge, evaluate perceptions toward its integration in medical education, and identify perceived barriers to adoption among undergraduate medical students.
Methods: A cross-sectional, questionnaire-based study was conducted (January-March 2026) among 324 MBBS students (2nd to final year) at an Indian medical college. A structured, pre-validated questionnaire was used to evaluate awareness, usage patterns, perceptions, and barriers (5-point Likert scale). Descriptive statistics and chi-square tests were used for the statistical analysis, and the level of significance was set at p < 0.05.
Results: Participants (mean age 22.71 ± 1.59 years; 55.6% male) reported 77.5% prior AI exposure, though only 12.04% claimed high familiarity. AI chatbots were the primary tools used (92.3%). Students demonstrated favourable perceptions regarding AI’s utility in clinical decision-making and learning while largely rejecting the notion that it would replace educators. Key barriers included data privacy concerns and output reliability. Prior AI exposure significantly correlated with positive perceptions (x² = 11.948, p = 0.018). Most students advocated for formal AI training and ethical guidelines within the medical curriculum.
Conclusion: Indian medical students show positive attitudes toward AI but lack deep technical familiarity. To address ethical and infrastructural barriers, structured curricular integration focusing on foundational AI competencies is essential for preparing future physicians.
Key words: Artificial intelligence, medical education, students, attitude, technology adoption