Artificial Intelligence Awareness And Perceptions Among Surgeons In Saudi Arabia :A Cross-Sectional Observational Study

Abstract

Background
Artificial Intelligence (AI) simulates the human decision-making using the algorithms and has growing applications in healthcare, including surgery. Saudi Arabia is advancing AI adoption, yet many physicians, especially surgeons, remain unfamiliar with its use. Understanding surgeons’ awareness and perceptions is crucial for successful integration. This study addresses the gap by evaluating the surgeons' knowledge, attitudes, and readiness to adopt AI in surgical practice.

Methodology
This is a cross-sectional study assessed AI awareness and perceptions among surgeons in Saudi Arabia using an online questionnaire distributed via Google Forms. Data is cleaned in Excel and analyzed via IBM SPSS 29.0.0.

Results
Among 386 surgeons, most were under 40 years (170, 44.0%) and had <10 years of experience (161, 41.7%). AI was perceived to enhance diagnostic accuracy by 165 (42.7%) and treatment planning by 172 (44.6%). Only 72 (18.6%) were very/extremely familiar with AI, and 211 (54.7%) remained neutral toward adopting AI. Interest in AI strongly correlated with the awareness (p < 0.001) with those very interested having the highest awareness scores (36.12). Significant predictors of higher perception included the younger age (p < 0.001), less experience (p < 0.001), Central region practice (p = 0.004), and training in KSA (p = 0.030). The familiarity also correlated with the willingness (r = 0.497, p < 0.001), and decision-making (r = 0.444, p < 0.001). Half of the participants (n = 193, 50%) had high overall awareness, while 95 (24.6%) had a low awareness level.

Conclusion
The study reveals that there is moderate awareness and the positive perception of AI among Saudi surgeons, especially among the younger, less experienced ones in the Central region. Higher interest links to greater awareness, which highlights the need for the targeted education, institutional support, and national strategies for effective AI integration.