Perception and Practices of Artificial Intelligence for Medical Education Among Medical Students: A Cross-Sectional Study

Background: Artificial Intelligence (AI) is increasingly influencing the healthcare industry, making it crucial to assess the perceptions and practices of AI among future healthcare professionals. This study aimed to determine the attitudes of Indian medical students toward "AI in medicine," their support for structured AI instruction, and their views on its ethical implications. Methods: This was a cross-sectional study conducted over one month, from March 7th to April 6th, 2025, at ESIC Medical College, Kalaburagi , among medical students. Universal Sampling was used, and the study population was medical students from the college. Out of 550 eligible students, 321 participated . Data was collected using a predesigned, pretested, semi-structured questionnaire with sections covering general information, perception (10 questions, 5-point Likert scale), practices (10 questions), and the future of AI in medical education (6 multiple-choice questions, 5-point Likert scale). Results: The majority of participants were female (52.3%) and aged 18-20 years (54.2%). A large portion of students used technology for educational purposes either Always (40.5%) or Often (37.7%) . Online resources (63.6%) and Textbooks (72.3%) were the primary sources of information. 81% of students reported using AI , with ChatGPT (84.9%) and Meta AI (53.7%) being the most used platforms. Students primarily learned about AI tools through friends (48%) and social media (42%) . In terms of perception , 96.9% agreed that AI can enhance the quality of medical education by providing personalized learning experiences, and 81.6% viewed AI as a powerful tool for teaching-learning . 78.9% felt dedicated AI tools should be created for medical education. For academic purposes , AI was mainly used for assignment writing (66.8%) , solving questions (59.8%) , and summarizing topics (56%) . Concerning the future of AI , 88.7% agreed that ethical training on AI use should be mandatory in the curriculum, and 81.2% believed AI would play a central role in training students to diagnose diseases accurately. Conclusion: The study demonstrates that a large proportion of medical students actively use AI in their studies and have a positive perception of its potential to personalize learning and reduce study time. However, the findings also highlight a need for structured training on AI, as many students felt they were not properly trained and were concerned about the lack of human interaction and the risk of inaccurate information. Therefore, the study recommends the creation of dedicated AI tools for medical education and mandatory ethical training on AI use.