Abstract: Radiotherapy-induced oropharyngeal mucositis is a common adverse effect of radiotherapy for patients with head and neck tumors, characterized predominantly by "swallowing-induced breakthrough pain". It occurs in almost all patients undergoing radiotherapy for head and neck tumors, severely impairing their quality of life and treatment compliance. The delineation of substructural organs at risk of radiotherapy-induced oropharyngeal mucositis, based on the common occurrence areas of "swallowing-induced breakthrough pain", helps to improve the predictive efficacy of severe radiotherapy-induced oropharyngeal mucositis, facilitate accurate identification of high-risk patients and optimization of radiotherapy plans, thereby reducing the incidence of severe radiotherapy-induced oropharyngeal mucositis and improving the prevention and treatment outcomes for high-risk patients. Artificial intelligence-assisted delineation of substructural organs at risk of radiotherapy-induced oropharyngeal mucositis helps to promote the homogenization of delineation results and improve the efficiency of target volume delineation. To guide the clinical applications of such artificial intelligence, it is necessary to establish a standardized and reasonable consensus on artificial intelligence-assisted delineation of substructural organs at risk of radiotherapy-induced oropharyngeal mucositis. This consensus elaborates the clinical manifestations, classification, definition of substructural organs at risk, clinical workflow and evaluation system for artificial intelligence-assisted delineation, advancing the prevention and treatment of radiotherapy-induced oropharyngeal mucositis.