Knowledge, Practices, and Perspectives of Artificial Intelligence–Enabled Behaviour Management Techniques in Children during Dental Treatment: A Cross-Sectional Questionnaire Study

Abstract Background: Child dental anxiety remains a major barrier to care. Recent advances in Artificial Intelligence (AI) offer new management methods, yet their awareness and clinical integration are underexplored. Aim: To assess the knowledge, practices, and perspectives of pediatric dental practitioners in India regarding AI-enabled behavior management. Materials and Methods: An analytical cross-sectional survey was conducted among 200 dental professionals (students, trainees, and academicians). Data assessed familiarity, utility, safety, and scope of AI tools. Results: Inferential analysis showed a significant positive correlation between professional category and awareness, indicating familiarity increased with professional qualification. Nevertheless, nearly half (47.5%) were unfamiliar with AI use, and 73% viewed it as an “early adopter fringe” concept. Professionals reported high perceived utility (85.5% manage disruptive, 88.4% reinforce), with Virtual Reality (83%) and mobile applications (61.5%) being the most recognized tools. A strong consensus emerged: 87.5% supported AI as an adjunct, and 75.9% favored a hybrid model, while 85% opposed automation. Conclusion: Pediatric dental practitioners show openness to AI-assisted behavior management but maintain skepticism regarding full automation. Continuous education and ethical guidelines are essential for responsible, evidence-based integration.