This research covers the cross-disciplinary applications of generative AI in advancing early detection and diagnosis of oral cancer. Due to its high mortality rate, usually occasioned by late diagnosis, oral cancer stands out as one of the most insidious health issues for which innovation is required in early intervention. Generative AI approaches, mainly GANs and VAEs, are promisingly advancing essential medical imaging, pathology, genomics, and public health areas. These AI models enhance the resolution of medical imaging, simulate various pathological scenarios, generate synthetic data in histopathology, and predict genetic mutations. Applications of AI in preventive dentistry and public health strategies will contribute to identifying and screening high-risk populations. Integration of AI methodologies across disciplines allows for improvement in early diagnosis, individualization of patient care, and the development of targeted therapies. These findings prove that generative AI, being cross-disciplinarily applied, might become a real game-changer in oral cancer research, offering new horizons for much more precise detection and considerably improving the outcomes of the patients.