Perceptions, Readiness and Willingness of Dentists to Adopt Artificial Intelligence in Clinical Dental Practice: A Cross-Sectional Study

Abstract

Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with applications in radiographic interpretation, disease detection, treatment planning, and clinical decision support in dentistry. Despite promising advancements, translation of AI from research settings to routine clinical dental practice remains limited. Adoption depends largely on dentists’ knowledge, perceptions, readiness, and willingness to integrate AI into daily practice. This study was conducted to assess the perceptions, readiness, and willingness of dentists to adopt artificial intelligence in clinical dental practice and to identify factors influencing AI adoption.

Methodology: A cross-sectional questionnaire-based study was conducted among 220 registered dental practitioners (BDS and MDS) practicing in academic, private, and government settings. A validated, self-administered questionnaire assessed awareness, exposure, perceptions, readiness, willingness, and perceived barriers related to AI adoption. Data were analyzed using descriptive and inferential statistics, with p < 0.05 considered statistically significant.

Results: Awareness of AI in dentistry was significantly higher among MDS practitioners (79.5%) compared to BDS practitioners (60.6%) (p = 0.02). However, actual use of AI-based decision-support tools was minimal in both groups. MDS practitioners demonstrated significantly higher agreement that AI improves diagnostic accuracy (56.4% vs 42.3%; p = 0.04) and is feasible for routine practice in India (48.7% vs 35.2%; p = 0.04). Willingness to use AI if available was significantly greater among MDS practitioners (48.7%) compared to BDS practitioners (33.8%) (p = 0.03). High cost, poor infrastructure, and medico-legal uncertainty were the most frequently reported barriers.

Conclusion: Dentists demonstrated positive perceptions and moderate readiness toward AI adoption; however, actual clinical utilization remains low. Specialists exhibited greater awareness and preparedness compared to general practitioners. Addressing structural barriers, strengthening digital infrastructure, and integrating formal AI training may facilitate responsible and effective implementation of AI in routine dental practice.