Knowledge and attitudes about artificial intelligence and its applications among Chinese endodontic practitioners: a cross - sectional survey

Abstract

Artificial intelligence (AI) has been increasingly applied in dentistry, including cariology and endodontics. However, evidence remains limited regarding endodontic practitioners’ AI literacy, perceptions, clinical usage, and barriers to AI integration. This study aimed to investigate AI literacy, usage patterns, attitudes, and perceived challenges among endodontics practitioners in China. A cross-sectional survey was conducted from July to September 2025 using an expert-reviewed and pilot-tested questionnaire administered via Wenjuanxing. The questionnaire collected demographic characteristics, knowledge of AI, current AI usage, attitudes toward AI applications, and perceived implementation challenges. A mixed purposive-snowball sampling strategy was employed for participants recruitment. Data from 224 respondents were analyzed using descriptive statistics, chi-square tests, and ordinal logistic regression ( p < 0.05). A total of 224 valid responses were obtained from practitioners across 24 provinces in China, including general dentists (36.2%) and endodontists (63.8%). Overall, 41.5% of respondents reported using AI tools in their professional activities, primarily for supportive tasks such as literature mining (56.7%), data processing (46.7%), and virtual simulation teaching (35.6%). Only 14.3% had participated in AI-related clinical or research projects. At the institutional level, 38.2% of respondents reported AI implementation in their workplace, while only 20.3% reported the presence of a comprehensive AI ethics frameworks. Most respondents (72.8%) expressed positive expectations regarding AI development in dentistry. Root canal anatomy identification (85.7%), caries detection (83%), and periapical lesion detection (82.6%) were rated as the most promising applications. Insufficient clinical validation (63.5%) and unclear ethical accountability (40.5%) were identified as the primary barriers. Chinese endodontic practitioners show positive expectations toward AI but limited clinical implementation. Current professional needs are concentrated in imaging-related applications and root canal treatment, highlighting the need for structured AI education, robust clinical validation, and clear ethical frameworks to support responsible integration of AI into endodontic practice.