Aliaga Ramos J. Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia. Artif Intell Gastrointest Endosc 2026; 7(2): 121689 [DOI: 10.37126/aige.121689]
Corresponding Author of This Article
Josué Aliaga Ramos, MD, Doctor, Service of Gastroenterology, Hospital José Agurto Tello-Chosica, 229 Walter Stubbs Street, Lima 150118, Peru. arjosue3000@gmail.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
review-article
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Artificial intelligence-assisted colonoscopy: Transforming detection, characterization, and management of colorectal neoplasia
Josué Aliaga Ramos
Josué Aliaga Ramos, Service of Gastroenterology, Hospital José Agurto Tello-Chosica, Lima 150118, Peru
Author contributions: Aliaga Ramos J conceived and designed the study, performed the literature review, conducted the data interpretation, wrote the original draft, revised the manuscript critically for important intellectual content, and approved the final version of the manuscript.
AI contribution statement: No artificial intelligence (AI) tools were used in the preparation of this manuscript. The study conception, literature review, critical analysis, writing, revision, and final approval were performed entirely by the author.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Corresponding author: Josué Aliaga Ramos, MD, Doctor, Service of Gastroenterology, Hospital José Agurto Tello-Chosica, 229 Walter Stubbs Street, Lima 150118, Peru. arjosue3000@gmail.com
Received: March 31, 2026 Revised: July 13, 2026 Accepted: August 3, 2026 Published online: September 8, 2026 Processing time: 158 Days and 1.6 Hours
Core Tip
Core Tip: Artificial intelligence (AI) is rapidly redefining the landscape of colorectal neoplasia, emerging as a pivotal driver of a new era in precision endoscopy. By augmenting human perception with advanced pattern recognition and real-time data processing, AI-enabled systems have demonstrated a consistent capacity to enhance adenoma detection, refine optical diagnosis, and support therapeutic decision-making with unprecedented accuracy and reproducibility. Beyond improving key quality indicators such as adenoma detection rate and diagnostic performance, AI mitigates operator-dependent variability and establishes a more standardized and objective approach to endoscopic practice. Its integration across the entire continuum of care from risk stratification and screening to lesion characterization and advanced endoscopic resection positions AI as a transformative tool capable of optimizing colorectal cancer prevention strategies. As evidence continues to accumulate, AI is no longer a complementary technology but a central component in the evolution toward more effective, individualized, and outcome-driven management of colorectal neoplasia.
