Background: Artificial intelligence (AI) has evolved from theoretical concepts into an important component of contemporary dental science. Advances in machine learning, deep learning, artificial neural networks, and convolutional neural networks have enabled automated analysis of complex clinical and imaging data.

Aim: To review the current applications and clinical potential of AI in oral medicine, oral and maxillofacial radiology, pathology, and oral oncology.

Materials and Methods: A targeted literature review of 32 foundational references was undertaken, encompassing publications from the conceptual development of AI in 1955 through clinical applications up to 2021. Evidence was categorized into maxillofacial radiodiagnosis, diagnostic oral pathology, and oral oncology, with emphasis on algorithms, diagnostic targets, and comparison with human clinical performance.

Results: AI demonstrated promising diagnostic performance in automated tooth detection and numbering, dental caries identification, periodontal bone assessment, biopsy pre-screening, tissue spectral analysis, oral lesion classification, cervical lymph-node metastasis detection, and survival prognostication. In several applications, AI achieved diagnostic accuracy comparable to or exceeding experienced clinicians.

Conclusion: AI can augment clinical decision-making and improve diagnostic efficiency in dentistry. However, algorithmic transparency, data standardization, patient privacy, ethical governance, and multicentre validation remain essential for safe and evidence-based clinical integration.