Applications of Artificial Intelligence in the Diagnosis and Treatment of Oral and Dental Diseases: Toward Smart Dental Systems in Healthcare Institutions

Abstract

The integration of artificial intelligence (AI) into dental care holds significant promise, yet its specific adoption and impact within Saudi Arabian healthcare institutions remain underexplored, creating a critical knowledge gap for national health transformation strategies. This study, therefore, aimed to evaluate the current landscape and identify key determinants of AI implementation for oral disease management in the Kingdom. Employing a sequential explanatory mixed-methods design, data were collected from 350 dental professionals and administrators across tertiary care institutions via surveys, interviews, and focus groups. Results revealed a significant adoption gradient, with specialized dental centers (M=0.28) and private hospitals (M=0.18) demonstrating higher AI adoption than government hospitals (M=-0.32, p<0.001). A lack of specialized training emerged as the most severe barrier and the strongest negative predictor of adoption (β = -0.33, p<0.001), while formal training had the largest positive effect (Cohen’s d = 0.85, p<0.001). The findings indicate that the primary obstacle to smart dental systems in Saudi Arabia is not technological availability but a human capital and organizational readiness deficit. This research provides an evidence-based framework for policymakers, emphasizing that strategic investments in competency development and supportive governance are essential precursors to successful AI integration in dental healthcare.