Redefining oral healthcare through artificial intelligence: a review of current applications and a roadmap for the future of dentistry

Abstract

The integration of artificial intelligence (AI) into dental practice represents a significant technological advancement in oral healthcare. This narrative review examines current research across AI domains including machine learning, deep learning, computer vision, natural language processing, and generative modeling to assess how AI is influencing clinical workflows, diagnostic procedures, treatment planning, and surgical interventions in dentistry. The central research question addresses how artificial intelligence is currently being applied in dental practice and what opportunities and challenges exist for its future implementation. Evidence from peer-reviewed studies demonstrates variable efficacy of AI in supporting diagnostic decisions for caries, periodontal disease, and oral cancer; assisting orthodontic planning and prosthodontic CAD/CAM workflows; and enabling robotic surgery and predictive modeling. While some AI models show promising accuracy metrics, questions remain about their generalizability and real-world performance. The review explores integration of AI through electronic health records, decision-support systems, and emerging digital twin technologies. Interdisciplinary collaborations with biomedical engineering, computational biology, and materials science are examined. Critical challenges including algorithmic bias, data privacy, informed consent, liability frameworks, and adoption barriers such as technological infrastructure, clinician acceptance, and regulatory uncertainties are discussed. Future directions emphasize federated learning for collaborative model development; explainable AI to improve transparency; integration with multi-omics data; and adaptive systems capable of continuous learning. This review provides a balanced assessment of AI's potential in dentistry while acknowledging significant implementation challenges that must be addressed to ensure equitable and effective patient care.

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