Artificial intelligence (AI) is a rapidly evolving field that focuses on the development of intelligent machines capable of performing tasks that would normally require human intelligence. AI systems use a variety of techniques, with machine learning, supervised learning, unsupervised learning, reinforcement learning, and deep learning being some of the major subtopics in the field. It has gained prominence worldwide as it mimics human intelligence and addresses various challenges. Dentistry has witnessed notable improvements due to their implementation. For instance, image-based automatic detection of diseases and other diagnosis-support systems, as well as image segmentation, resolution enhancement of dental radiographs, have all experienced significant advancements with the aid of AI. The realm of AI techniques in dentistry remains wide open, encompassing various areas, all falling within the emerging digital dentistry paradigm. This thesis is a narrative review that aims to critically analyze and report on the available data on the use and application of AI in dentistry. In doing so, it will collect relevant information from the available literature and highlight the current clinical trends, research advances, and future applications of AI in dentistry. Furthermore, it sheds light on its limitations and future possibilities. Therefore, it is necessary to also briefly discuss the technical aspects of artificial neural networks, machine learning, and deep learning and their use. Thus, the purpose of this thesis is to provide the uninformed reader in the field of computer science with a brief description of the relevant AI systems and their implications for different areas of dentistry.