Objective To investigate the current status of knowledge, attitudes, and clinical demands regarding artificial intelligence (AI) applications in stomatology among medical staff in public healthcare institutions in Huairou District, Beijing, and to analyze the influencing factors and provide evidence for the promotion and application of AI technology in the field of stomatology.

Methods A cross-sectional survey design was employed, and a sampling survey was conducted among medical staff in public healthcare institutions in Huairou District, Beijing, using an online questionnaire from December 11 to 24, 2025. The questionnaire covered demographic characteristics, AI knowledge, attitudes and behavioral intention, and perceived barriers to promotion. Multiple linear regression models were employed to explore factors influencing knowledge, attitudes and behavioral intention.

Results A total of 616 valid questionnaires were collected. Multivariate linear regression revealed that age, job categories, working in a tertiary hospital, and having received AI training were independent factors for the knowledge dimension (P < 0.05). For the attitude dimension, independent factors were gender, other job categories, tertiary hospital, CDC setting, and having AI training (P < 0.05). For the behavioral intention dimension, gender and having received AI training were independent predictors(P < 0.05). Regarding promotion, only 24.68% of participants were aware of AI‑driven personalized health education. The main perceived barriers were immature technology (61.53%), high equipment cost (58.28%), and low patient acceptance (54.87%). The most desired strategies were operational training (76.95%) and clinical practice guidelines (74.68%).

Conclusion The overall knowledge of AI applications in stomatology among medical staff in public healthcare institutions in this district need to be improved, although their attitudes are positive and their behavioral intentions are strong. AI‑related training is a key modifiable factor for improving knowledge, attitudes, and behavioral intentions. Future promotion efforts should prioritize training, along with technology validation, cost control, and regulatory development, to facilitate the effective integration of AI in stomatological diagnosis and treatment.

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