Knowledge, perception, and use of artificial intelligence among nuclear medicine technologists in Saudi Arabia: A multiregional multicenter study

Objective This study aimed to assess knowledge, perceptions, and clinical use of artificial intelligence (AI) among nuclear medicine technologists in Saudi Arabia, evaluate their AI education and training, and identify factors associated with AI use in clinical practice. Methods A multicenter cross-sectional study was conducted among nuclear medicine technologists working in public and private healthcare institutions across Saudi Arabia. Data on the participants’ demographic characteristics, AI education and training, AI use, and perceptions of AI were collected using a structured online questionnaire. Descriptive statistics, χ 2 tests, and binary logistic regression analyses were performed. Results Positive perceptions of AI were observed among the 174 participants. Half (50.0%) of the participants agreed that AI improves workflow efficiency, 47.1% agreed that it improves diagnostic accuracy, and 46.0% agreed that AI supports clinical practice. Only 23.0% had formal AI education, and 16.1% had received AI-related training. Most participants reported either rare (60.9%) or no (9.8%) AI use in clinical practice. Logistic regression analysis demonstrated that formal AI education was independently associated with higher AI use (odds ratio = 5.76, 95% confidence interval [2.52, 13.18], p < 0.001), whereas the association between AI training and AI use was attenuated after adjustment for age and gender (adjusted odds ratio = 2.47, 95% confidence interval [0.95, 6.41], p = 0.062). Conclusion Nuclear medicine technologists in Saudi Arabia demonstrated positive perceptions toward AI despite limited formal AI education and AI implementation. Formal AI education exhibited the strongest association with higher AI use, highlighting the importance of integrating AI education into nuclear medicine curricula and professional development programs.