Harnessing artificial intelligence in gastrointestinal endoscopy for early detection of dysplastic lesions in inflammatory bowel disease

Artificial intelligence (AI) has become an increasingly valuable tool in gastrointestinal endoscopy, especially in the context of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. One of its most impactful applications is the early detection and accurate characterization of dysplastic lesions, which are often difficult to identify owing to chronic inflammation and mucosal alterations. AI-based systems, such as computer-aided detection and computer-aided diagnosis, have shown excellent performance in identifying subtle or flat lesions, improving the quality and consistency of dysplasia surveillance, and aiding in colorectal cancer prevention. In addition to neoplasia detection, AI plays a significant role in assessing mucosal inflammation and disease activity by offering objective scoring, reducing interobserver variability, and even predicting histological remission without the need for biopsy. These capabilities enhance decision-making and support a more personalized approach to patient management. While technical, regulatory, and integration challenges remain, current evidence supports the growing role of AI in improving both diagnostic precision and long-term outcomes in inflammatory bowel disease endoscopy.