Readiness towards the Use of Artificial Intelligence in 
\nMedicine and Associated Factors among Undergraduate 
\nMedical Students at a Public Medical School in Sarawak, 
\nMalaysia

Introduction: Artificial intelligence (AI) is transforming healthcare and medical education, requiring future healthcare professionals to integrate AI effectively into clinical practice. Understanding the readiness of medical students to adopt AI is essential for curriculum development. However, the readiness of medical students in Sarawak, Malaysia, towards AI in medicine and the significant factors influencing it remain underexplored.
\nAim/Purpose/Objective: This study aimed to assess the readiness of undergraduate medical students at a public medical school in Sarawak, Malaysia, towards AI in medicine 
\nand to identify the factors significantly associated with their readiness. 
\nMethod: A quantitative cross-sectional survey study was conducted from October 2023 
\nto August 2024, involving 185 undergraduate medical students from year one to year five 
\nat a public medical school in Sarawak. A convenience sampling method was employed. 
\nData were collected using a validated questionnaire adapted from the Medical Artificial 
\nIntelligence Readiness Scale for Medical Students (MAIRS-MS), covering four domains 
\n(cognition, ability, vision, and ethics) and related variables. Descriptive statistics were used 
\nto assess AI readiness, and statistical analyses were performed to identify significant factors 
\nassociated with readiness (p < 0.05).
\nResults: The mean overall AI readiness score was 69.92%. Domain-specific mean scores 
\nwere: vision (75.6%), ethics (73.48%), ability (72.56%), and cognition (63.82%). Gender, 
\nyear of study, and AI training were significantly associated with higher AI readiness. Male 
\nstudents scored higher in ability (p = 0.001). Year four students had higher scores in ability 
\n(p = 0.041) and total AI readiness (p = 0.049). Students with AI training scored higher in 
\nvision (p = 0.039) and ethics (p = 0.045).
\nConclusion: Undergraduate medical students from this study showed moderate readiness 
\nfor AI in medicine. Gender, year of study, and AI training were significant associated factors. 
\nEarly integration of targeted AI training is recommended to further enhance their readiness 
\nfor an AI-driven healthcare system.
\nKeywords: Artificial intelligence; readiness; medicine; medical students; medical 
\neducation