Artificial intelligence (AI) is increasingly being explored in gastrointestinal endoscopy, with growing interest in its potential applications in urgent and emergent settings. In the context of gastrointestinal bleeding and other advanced endoscopic procedures, AI-based technologies aim to support endoscopists in bleeding detection, risk stratification, procedural guidance, and outcome prediction. While AI is not yet routinely implemented in emergency endoscopy, several approaches—including computer vision systems, deep learning models, and advanced imaging techniques—have demonstrated promising results in both diagnostic and therapeutic scenarios. This chapter reviews currently available technologies and emerging AI applications relevant to the endoscopic management of gastrointestinal bleeding. In addition to bleeding detection and hemostasis, the chapter discusses AI-based clinical prediction models for adverse events during endoscopic retrograde cholangiopancreatography, such as post-ERCP pancreatitis, as well as deep learning applications in the diagnosis of biliary strictures using cholangioscopy. Current evidence, limitations, and future directions are examined, with particular attention to clinical validation, workflow integration, and the role of AI as a decision-support tool in endoscopic practice.