Artificial intelligence (AI) research in endoscopy is being translated at rapid pace with a number of approved devices now available for use in luminal endoscopy. However, the published literature for AI in biliopancreatic endoscopy is predominantly limited to early pre-clinical studies including applications for diagnostic EUS and patient risk stratification. Potential future use cases are highlighted in this manuscript including optical characterisation of strictures during cholangioscopy, prediction of post-ERCP acute pancreatitis and selective biliary duct cannulation difficulty, automated report generation and novel AI-based quality key performance metrics. To realise the full potential of AI and accelerate innovation, it is crucial that robust inter-disciplinary collaborations are formed between biliopancreatic endoscopists and AI researchers.

内窥镜领域的人工智能 (AI) 研究正在快速转化，许多已获批准的设备现已可用于管腔内窥镜检查。然而，已发表的胆胰内窥镜 AI 文献主要限于早期临床前研究，包括诊断 EUS 和患者风险分层的应用。本手稿强调了潜在的未来用例，包括胆管镜检查期间狭窄的光学特征、ERCP 后急性胰腺炎和选择性胆管插管困难的预测、自动报告生成和基于 AI 的新型质量关键性能指标。为了充分发挥人工智能的潜力并加速创新，