Artificial intelligence plays an increasingly important role in modern dentistry, offering the possibility of precise and quick diagnostic image analysis and supporting the process of pathology detection. Aim: The study aims to discuss the use of artificial intelligence in caries detection, with an emphasis on radiographs and intraoral imaging analysis, and to assess the potential of this technology in the quality and efficiency of dental diagnostics improvement. Methods: A review of the scientific literature covering the years 2015–2024 was carried out, analyzing the results of studies on the effectiveness of artificial intelligence algorithms in caries detection. Publications evaluating parameters such as sensitivity, specificity, and precision compared to traditional diagnostic methods were included. Results: AI algorithms, particularly convolutional neural networks, present high accuracy, sensitivity, and specificity in caries detection, often outperforming traditional methods in detecting early lesions. The use of artificial intelligence standardizes the diagnosis, shortens the time of analysis, and reduces errors caused by a subjective clinical assessment. Major limitations include the need for high-quality training data, implementation costs, and challenges associated with technology acceptance. Conclusions: Artificial intelligence has the potential to significantly improve caries detection, offering precision, efficiency, and algorithms standardization. However, taking full advantage of its capabilities requires further research, standardization of algorithms, and appropriate adaptation of the clinical environment.