In response to the severe challenge of high incidence but low early detection rate of gastrointestinal cancers in China and the limitations of traditional endoscopic screening, artificial intelligence (AI)-assisted endoscopy is emerging as a key solution for early screening, diagnosis, and treatment. Deep learning-based computer-aided detection and diagnosis systems have demonstrated significant potential to enhance clinical sensitivity, specificity, and operational efficiency in the early identification, pathological characterization, and guidance of precision endoscopic therapy for esophageal, gastric, and colorectal cancers. Although challenges remain in data standardization, algorithm interpretability, and regulatory compliance and ethical governance, the deep integration of AI and digestive endoscopy is transforming the diagnostic and therapeutic paradigm from “experience-dependent” to “data-driven”, and offers a core driving force for achieving comprehensive and precise prevention and control of gastrointestinal tumors.