The slope of enlightenment: Towards a more realistic understanding of the strengths and weaknesses of artificial intelligence for colorectal polyp assessment.

Artificial intelligence (AI) has rapidly evolved into a transformative adjunct to gastrointestinal (GI) endoscopy, particularly through deep-learning-based computer-aided detection (CADe) and diagnosis (CADx) systems. Early randomized controlled trials demonstrated substantial improvements in adenoma and polyp detection, fueling high expectations for AI-enhanced screening performance. However, real-world evidence has since revealed more modest and heterogeneous benefits, underscoring the challenges of generalizability, algorithmic transparency, workflow integration, and user engagement. This review synthesizes the current state of AI in colorectal cancer screening and polyp assessment, outlining both its strengths-including improved lesion recognition, enhanced quality assurance, and potential for real-time optical diagnosis and its limitations, such as false positives, variable clinical impact, medicolegal uncertainties, and the risk of cognitive offloading. Positioned along the "slope of enlightenment" of the Gartner Hype Cycle, AI in endoscopy is entering a phase of maturation characterized by pragmatic adoption, refined human-AI interaction and development of multimodal, explainable systems. Continued multicenter validation, standardized reporting, and responsible integration are essential to assess the technology's long-term value and achieving sustainable improvements in endoscopic quality and future colorectal cancer prevention.