Integrating AI to medical education: Readiness, knowledge and expectations of pre-clinical academics of the Faculty of Medicine, University of Colombo

Abstract

Artificial intelligence (AI) transforms medical education with personalized, evidence-based, and innovative approaches. The pre-clinical education of MBBS, whilst the most theory-intensive, represents the transition from teacher-led to self-directed learning, where AI integration can smoothen the transition. Successful AI integration in medical education requires not only technical feasibility but also the knowledge and positive mindsets of academics and students. This study aimed to assess the readiness, knowledge, perceptions, and expectations of pre-clinical academic staff on AI tools in medical education at the Faculty of Medicine, University of Colombo (FOM, UOC). A descriptive cross-sectional study was conducted with an online self-administered questionnaire for academic staff members of the Basic Sciences Stream (Anatomy, Biochemistry and Physiology Departments) at FOM, UOC. The questionnaire inquired about the demographics, ICT proficiency, knowledge, perceptions, readiness, and expectations on AI tools in medical education. The response rate was 48.2%, and 57.1% were males. Mean age was 42.9 years. with 50% professors and 43% having _ >20 years of experience. ICT proficiency was moderate (mean 3.43/5), with association being significant with male gender (p=0.045) but not with age (p=0.24). Despite 86% being aware of AI use in medical education, only 28.6% had used AI tools such as ChatGPT and Gemini in teaching. Interest was high (71.4% rated "very interested"), while confidence was moderate (mean 2.64/5) in adopting AI. Improved teaching efficiency (100%) and learning outcomes (85.7%) were the main expectations of adopting AI. They recognized ethical and equity challenges, with 75%saying experts must supervise AI. Over 75% expected AI will revolutionize medical education and requested institutional support, including workshops (100%) and technical assistance (92.8%). Pre-clinical academic staff at FOM, UOC exhibit strong enthusiasm for AI integration but limited hands-on experience and moderate confidence, highlighting the need for targeted training, institutional policies, and technical support to achieve effective implementation.