Regardless of where we were born and raised, we all have heard many fairy tales during our childhood, portraying the image of a future with cars flying and robots living among us, setting the stage for a potential symbiosis of humans and manmade robots. A robot’s brain is built upon particular algorithms that allow for executing a range of tasks assigned to its main core, artificial intelligence (AI). AI pinpoints the efficient completion of duties generally carried out by humans while sidestepping possible biases originating from fatigue, emotions, misperceptions, and human errors, resulting in consistent and reproducible outcomes. One of the major branches of AI is machine learning (ML), which pivots on a mathematical set of rules to generate predictable results. The most prominent subfield of ML is deep learning (DL). An indispensable component of DL is multilayered artificial neural networks (ANN) that act as data analysis and produce cognizable outputs. Plenty of benefits have been allocated to AI applications in Medicine and Dentistry, such as enhanced diagnosis, treatment planning, and analysis of treatment outcomes, along with radiographic and photographic pattern recognition. Moreover, AI is integrated into medical education to create real case simulations and analysis of academic outcomes. Oral and maxillofacial surgery is no exception and benefits from various applications of AI and ML in diagnosis, treatment planning, and analysis of head and neck benign and malignant lesions, bone reconstruction and orthognathic surgery, dental implantology, traumatology, and minor oral surgeries. The following chapter elucidates the applications of AI in oral and maxillofacial surgery and sheds light on its advantages, limitations, challenges, and future trends in this field.