Artificial intelligence in dentistry: A comprehensive review of past, present, and future directions

Abstract

ABSTRACT Artificial intelligence (AI) has rapidly emerged as a transformative force in modern dentistry, offering innovative solutions that enhance diagnostic precision, treatment planning, education, patient management, and regenerative medicine. The integration of advanced computational methods – including machine learning, deep learning, convolutional neural networks, and hybrid neuro-fuzzy systems – has enabled automated analysis and clinical decision support with accuracy approaching or even surpassing that of experienced dental specialists. Recent research between 2020 and 2025 demonstrates AI’s growing role across dental specialties such as radiology, orthodontics, endodontics, periodontics, oral pathology, and prosthodontics. These technologies have improved early disease detection, personalized treatment strategies, and workflow efficiency, while also enhancing educational outcomes through simulation and predictive modeling. Despite these advances, challenges remain concerning data quality, algorithm transparency, ethical considerations, and clinical validation. This review synthesizes current evidence from recent literature, highlighting AI’s core technologies, specialty-specific applications, benefits, and limitations. Furthermore, it explores emerging trends such as explainable AI, multimodal learning, and human–AI collaboration, offering insights into the future trajectory of AI-driven innovations in dental research and clinical practice.

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