This chapter explores the practical applications of Artificial Intelligence (AI) in the early detection and diagnosis of oral cancer, focusing on risk stratification, RGB image classification, histopathology image classification, and integrated analysis aids. It presents implementation strategies, empirical results, and the demonstrable impact of AI-driven models in transforming clinical workflows and improving patient outcomes. Key methodologies include logistic regression for risk stratification, Simple Convolutional Neural Networks (CNNs) for image classification, and SHAP interpretability for feature importance analysis. The chapter also introduces specialized AI tools, such as the oral cancer risk assessment aid, oral lesion AI screening aid, and oral histopathology AI screening aid, designed to assist healthcare professionals in preliminary assessments. While these tools offer significant potential in augmenting human expertise, their limitations are emphasized, ensuring they are used as supplemental aids rather than replacements for professional medical judgment.