Artificial intelligence has become a significant instrument in oral and maxillofacial radiology. It offers novel automated diagnosis and treatment planning. The purpose of the review is to synthesize the already existing studies about the application of artificial intelligence in oral radiology. We conducted thorough research of the articles published in the period of 2021 to 2025. This will lay emphasis on research that validates the clinical use and outputs of AI performance in maxillofacial and dental imaging. Convolutional neural network models have shown remarkable results in a number of diagnostics cases, such as the detection of endodontic issues, the determination of periodontal health, caries detection, or jaw pathology. The quality of data used in training, the ability of the model to be easily interpreted, the equity of algorithms, integration into clinical practice, and regulatory approval are still significant issues. Artificial intelligence is significant in terms of the processing and interpretation of radiographic information in the oral health care field. Its goal is to enhance the precision of diagnosis and increase the efficiency of its work. Its successful implementation should pay close attention to data management, ethical practice, regulatory practice, and healthcare provider training.