Knowledge, Attitudes, and Practices Related to Artificial Intelligence Among Medical Students and Academics in Saudi Arabia: A Systematic Review

Abstract

This systematic review aims to analyze the existing literature on artificial intelligence (AI) applications in medical education in Saudi Arabia, and it spanned the period from January 2020 to February 2025. The review focuses on the nature and scope of AI applications, evidence synthesis types, geographical distribution of authorship, quality of research, challenges encountered, and research gaps within Saudi Arabia. Studies were retrieved from the PubMed, Google Scholar, ProQuest, and Web of Science databases. The process followed the guidelines outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We included studies that explored knowledge, attitudes, and practices of AI among medical students and academics in Saudi Arabia. We first screened the titles and abstracts of the studies according to our inclusion criteria, and then reviewed the full texts of those that met the criteria. A standardized form was used to collect data, including author information, study population, research objectives, and key findings. The review identified key areas of focus, including personalized learning, interactive simulations, and real-time feedback in medical education. Most studies discussed the potential benefits of AI tools in improving student engagement and clinical decision-making skills. However, significant challenges were reported, such as insufficiencies in faculty training, data privacy concerns, and disparities in technological infrastructure. While the use of AI in medical education in Saudi Arabia has great potential, there are still significant challenges. There is a need for proper training for faculty and standardized AI curricula. More research is required to assess the long-term effects of AI on educational outcomes and find ways to overcome the current barriers to its successful implementation.

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