Artificial intelligence (AI), particularly deep learning, is rapidly transforming dental diagnostics from automated interpretation of radiographs to remote screening using intraoral photos. Recent systematic reviews and meta-analyses report high accuracy for AI models in tasks such as caries detection and radiographic interpretation, and new clinical deployments are appearing. However, important challenges remain: dataset bias and poor socio-demographic reporting, explainability, data privacy and regulatory gaps, integration into clinical workflows, and real-world validation. This review synthesizes current applications, core enabling technologies, clinical benefits, major challenges, and realistic future directions to guide researchers, clinicians, developers, and regulators toward safe, effective, and equitable AI-enabled dental care.