Early and accurate discovery of oral cancer (OC) is important for medical services to deliver high-quality OC care as it can drastically reduce patient mortality. Assam, one of the states of the North Eastern Region (NER) of India, reports a significantly high proportion of OC cases every year, leaving behind tears, fears, pain, and loss. Despite the ease to examine the oral cavity during routine examinations, many malignancies remain unobserved till it has progressed to an advanced stage. To ascertain the existence of OC at an early stage, it is essential to observe the emergence of lumps in the oral cavity and undertake radiographic imaging and biopsies as recommended by a medical examiner or an oncology specialist. This necessitates substantial financial resources from the sponsoring organization and the patient. While increasing occurrence of OC can be minimized by prohibiting the use of toxic chewable goods, OC cannot be entirely eliminated due to a number of reasons. Hence, a system is required that can detect OC at an early stage and help doctors take appropriate measures in remote settings. The goal of this work is to investigate the necessity of AI-assisted strategies and techniques for the early and accurate detection of OC in the remote settings of Assam to deliver good-quality OC care at an affordable cost that will help medical professionals to take appropriate decisions.