Knowledge Attitudes and Ethical Concerns About Artificial Intelligence Among Medical Students at Taibah University: A Cross-Sectional Study.

Background: Artificial Intelligence (AI) is increasingly relevant tool to medical education and healthcare. Understanding the readiness of future physicians for AI integration is essential for developing effective curricula and fostering responsible use of this technology. Methods: This cross-sectional study was conducted among 189 medical students at Taibah University using a validated, self-administered online questionnaire. The tool measured AI knowledge (7 items), attitudes (10 items), practices (7 items), and perceived barriers. Responses were captured on a 5-point Likert scale. Descriptive and inferential statistics, including one-way ANOVA, were used to analyze differences across academic years. Results: Out of 189 respondents, 53.97% (n=102) of students reported familiarity with basic AI concepts, and 5.66% (n=11) were aware of machine learning and deep learning. Only 11.21% (n=21) had received formal AI instruction, and 21.18% (n=40) had attended dedicated courses. 74.60% (n=141) believed AI would revolutionize education, yet 41.91% (n=79) expressed concerns about AI replacing teachers. 52.02% (n=98) used AI regularly for exam preparation. In comparison, only 11.64% (n=22) used it for Objective Structured Clinical Examination (OSCE) preparation Key barriers included ethical concerns (n=44 responses), risk of plagiarism (n=56), lack of knowledge (n=46), and limited access to tools (n=28). Conclusion: Medical students display cautious optimism about AI in education, with limited practical knowledge and concerns about ethical implications. Integrating structured AI education, training program, and ethical guideline is essential for preparing students for an AI-enhanced healthcare landscape.