Assessing Perceptions and Exposure to Artificial Intelligence Among Medical Educators and Clinicians in Saudi Arabia: A Cross-Sectional Study

Summary

This cross-sectional study explored perceptions of artificial intelligence among medical educators and clinicians in Saudi Arabia. Although strong interest was reported, formal AI training was limited, and reliance on informal sources was common, highlighting the potential need for structured AI education.

Abstract

Artificial intelligence (AI) is transforming healthcare through advances in diagnostics and decision-making, yet most studies have focused on medical students’ perceptions, with limited attention to medical educators and practicing clinicians. Understanding these perspectives is critical for developing curricula that prepare future physicians for AI-enhanced practice. This study investigated AI awareness, exposure, and perceived impact among medical educators, interns, residents, specialists, and consultants in Saudi Arabia. A cross-sectional study was conducted using a validated online survey distributed to several Saudi medical schools and hospitals. The survey collected demographic data, prior AI education, self-rated AI knowledge, and interest in AI. The participants also rated their ability to list clinically relevant AI applications, assessed AI’s expected influence on various specialties, and indicated whether training in AI concepts would be beneficial. Group differences were analyzed using chi-square tests, ANOVA, and logistic regression, controlling for age and sex. Among the 229 respondents (60 medical educators, 78 interns/residents, and 91 specialists/consultants), medical educators were more likely to report the ability to list AI benefits (63.3% vs. 38.5% and 39.6%) and to express ethical concerns about AI use in healthcare (76.6% vs. 51.3% and 51.6%) compared to the other groups. Only 32.3% reported receiving formal AI education, with most gaining knowledge through informal sources such as the media. Radiology and pathology were identified as the specialties most likely to be transformed by AI. Overall, perceptions of AI among medical educators and clinicians revealed a strong interest but limited formal training. Despite enthusiasm across all groups, the participants relied on informal sources and lacked foundational knowledge on AI. These findings highlight the potential importance of embedding structured AI education into medical curricula and residency training programs to support preparedness for AI-integrated clinical care.

Introduction

The term “artificial intelligence” (AI) was first introduced at the Dartmouth Conference in 1956 and is now globally regarded as a top technology¹. AI broadly refers to technologies capable of mimicking human intelligence² and is commonly categorized into four domains: natural language processing for speech and text recognition and generation; computer vision for interpreting images; machine learning based on neural networks; and knowledge-based systems that rely on semantic technologies or cognitive modeling³.

One of the most rapidly evolving applications o....

Protocol

Study modeling
Ethical approval for this study was obtained from the Institutional Review Board of King Abdulaziz University (Reference No. 500-23). Eligible participants included medical professionals aged 18 years or older (medical educators, interns, residents, specialists, and consultants) practicing in Saudi Arabia. Individuals who were not medical graduates or were not actively practicing were excluded. All participants provided informed consent prior to data collection, and their participation was entirely voluntary. An electronic informed consent statement was presented on the first page of the survey, and the participants were required ....

Results

Sample
This cross-sectional survey presents observational comparisons among naturally occurring participant groups, consistent with the study's exploratory nature. The sample comprised 229 participants (60 medical educators, 78 interns/residents, and 91 specialists/consultants). The groups did not significantly differ in terms of sex (47.6% male, p=0.088 between groups) or having had a formal AI education (32.3% with training, p=0.067 between groups). Interns and residents were significantly younger .......

Discussion

To our knowledge, this is one of the first studies in Saudi Arabia to examine how medical educators and practicing clinicians perceive AI. The strong reported interest aligns with the broader adoption of AI in healthcare, which has been documented in both clinical and educational settings¹⁸. This trend has been met with positive acceptance among medical educators, especially in the context of medical education, where tools such as ChatGPT have been recognized for their usefulness in tasks like sum.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Google Forms	Google LLC	N/A	Used to distribute and collect responses for the online survey
Microsoft Excel	Microsoft Corporation	N/A	Used for data organization and export prior to analysis
PubMed Database	U.S. National Library of Medicine	N/A	Used for literature review and retrieval of references
Questionnaire	Liu D, Sawyer J, Luna A, Aoun J, Wang J, Boachie L, Halabi S, Joe B Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study JMIR Med Educ 2022;8(4):e38325 URL: https://mededu.jmir.org/2022/4/e38325 DOI: 10.2196/38325	N/A	Validated questionnaire assessing perceptions of AI in medicine, adapted from a previously published study in JMIR Medical Education (2022)
R (Statistical Software)	R Foundation for Statistical Computing	N/A	Used for statistical analysis and data visualization