Artificial Intelligence in Dentistry: Current Evidence, Clinical Utility, and Challenges

Abstract

Introduction The rapid expansion of digital technologies in dentistry has resulted in increased reliance on complex clinical and imaging data, creating opportunities for artificial intelligence (AI) to support diagnostic and treatment-related decision-making. While AI-based systems have demonstrated promising results, their clinical relevance and ethical implications require critical evaluation. This narrative review aims to evaluate the current evidence on AI applications in dentistry with particular emphasis on clinical utility, validation, and ethical considerations. Methods A narrative review of the literature was conducted using peer-reviewed studies focusing on AI applications across dental specialties, including dental imaging, orthodontics, endodontics, prosthodontics, implant dentistry, oral medicine, and oral pathology. Emphasis was placed on clinically relevant outcomes, validation approaches, and real-world applicability. Results AI has shown substantial potential as a decision support tool in dentistry, particularly in diagnostic imaging, automated analysis, and treatment planning. Applications such as caries detection, cephalometric landmark identification, periapical pathology detection, and digital smile design demonstrate improved efficiency and consistency. However, most AI systems remain limited by retrospective study designs, lack of external validation, population bias, and restricted interpretability. Conclusion AI represents a valuable adjunct in modern dental practice when used to support, rather than replace, clinical judgment. Responsible integration of AI requires robust validation, ethical governance, clinician education, and regulatory clarity to ensure patient safety and equitable care.

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