Simulating Reality and Transforming Endoscopic Education-Lessons from Esophageal Dilation

Although endoscopic training has traditionally relied on mentorship and procedural volume to assess proficiency, the major gastroenterology societies have increasingly adopted competency-based assessment tools, including the Assessment of Competency in Endoscopy (ACE) and Direct Observation of Procedural Skills (DOPS), to provide a more objective evaluation of technical and cognitive skills. Despite these advances, mentor-based assessment remains susceptible to subjectivity. Emerging technologies such as simulation, virtual reality, and artificial intelligence (AI) offer opportunities to further standardize endoscopic education and enhance training. Simulation-based learning improves early endoscopic competency, exhibiting utility in both basic and advanced procedures. Similarly, AI applications in endoscopy are expanding beyond lesion detection to include procedural guidance, anatomical recognition, and performance optimization. Esophageal dilation for benign esophageal strictures serves as a model to illustrate the integration of these technologies into endoscopic education. Though the procedure requires mastery of risk stratification, device selection, and technical execution, competency assessment remains primarily volume-based. AI-assisted systems may provide real-time guidance for stricture characterization, dilator selection, and procedural endpoints, whereas simulation platforms may facilitate skill acquisition in a risk-free environment. The integration of simulation and AI into competency-based curricula has the potential to accelerate learning, reduce subjectivity, and improve endoscopic training.