Abstract
Colorectal cancer (CRC) remains a major global burden, demanding earlier detection and more precise care. Artificial intelligence (AI) is reshaping the CRC pathway by boosting lesion detection, expediting molecular triage, and enabling quantitative, multimodal decision support. Evidence shows computer-aided detection increases adenoma detection and lowers miss rates; digital pathology can infer microsatellite instability from routine slides to prioritize confirmatory testing. AI also strengthens CT/MRI via segmentation, radiomics-based risk stratification, nodal staging, and response prediction, while blood- and genomics-driven models extend noninvasive screening and prognosis. Translating these gains requires high-quality data, external validation, interpretability, workflow integration, and robust governance. Priorities include multicenter prospective studies, lifecycle performance monitoring, and implementation frameworks that ensure usability, equity, and cost-effectiveness, enabling AI to evolve into a dependable infrastructure that improves CRC outcomes.