Oral cancer, primarily oral squamous cell carcinoma (OSCC), poses a significant global health challenge due to its high morbidity and mortality rates, especially when diagnosed at advanced stages. Artificial Intelligence (AI) emerges as a transformative tool in early detection, diagnosis, and management of oral cancer. This chapter explores the evolving role of AI in oral oncology, focusing on its applications in automated image analysis, computer-aided diagnosis (CAD), risk stratification, integration with electronic health records (EHR), predictive modeling, and mobile health (mHealth) solutions. AI-driven methodologies, such as deep learning and machine learning, demonstrate high accuracy in analyzing clinical photographs, histopathological slides, and multimodal data, often surpassing traditional diagnostic approaches. Despite its promise, challenges such as data quality, algorithmic bias, model generalizability, and ethical concerns persist. The chapter also discusses future directions, including explainable AI (XAI), federated learning, and multimodal data integration, emphasizing the need for interdisciplinary collaboration to ensure responsible and effective clinical adoption. AI’s potential to revolutionize oral cancer care lies in its ability to enhance diagnostic precision, improve accessibility, and enable personalized treatment strategies, ultimately contributing to better patient outcomes and reduced global disease burden.