The application of artificial intelligence (AI) in colonoscopy is attracting a growing amount of attention because it has the potential to improve the quality of colonoscopy.1,2 The main focuses of research in this field comprise automated polyp detection3,4 and characterization5,6 (ie, pathologic prediction), which may respectively contribute to a higher rate of adenoma detection and a reduction of the costs related to unnecessary polypectomy. However, there has not yet been any report of technology capable of simultaneous polyp detection and characterization, which is the optimal situation for fully automated colonoscopic observation.