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Artificial intelligence (AI) is rapidly transforming dentistry through innovations in clinical practice, education, and research. Machine learning, and deep learning in particular, support disease diagnosis, treatment planning, prognosis prediction, and patient care. They do so by leveraging large-scale datasets from disciplines such as periodontology, endodontics, oral and maxillofacial surgery, orthodontics, and prosthodontics. This review first examines the technical and ethical foundations of dental AI, emphasizing data quality, representativeness, privacy protection, and standardized evaluation metrics. It then synthesizes current clinical applications, including AI-assisted diagnosis, image interpretation, surgical planning, robotic interventions, and predictive modeling of treatment outcomes. Educational uses of AI are examined in the context of simulation-based training, virtual reality integration, automated assessment, and patient education. The role of AI in scientific discovery is discussed with respect to data mining, biomarker identification, drug design, literature synthesis, and peer review support. Despite its potential, dental AI adoption faces challenges including limited and biased datasets, interoperability barriers, model interpretability, ethical concerns, and insufficient user training. Future integration will require rigorous external validation, regulatory compliance, seamless workflow incorporation, and interdisciplinary collaboration to ensure safety, transparency, and clinical utility. By addressing these limitations, AI can serve as a robust, multidimensional decision-support tool to improve diagnostic accuracy, personalizing care, and advancing dental education and research.
Tay et al. (Thu,) studied this question.