Citations

ABSTRACT Background and Aims Artificial intelligence (AI) is increasingly integrated into gastrointestinal (GI) endoscopy, yet limited data exist on how patients and endoscopists perceive its use. This study aimed to evaluate users' values and preferences regarding AI in endoscopy to support effective implementation and inform guideline development. Methods As part of the World Endoscopy Organization (WEO) AI committee initiatives, two structured international surveys were conducted—one for patients and one for practicing endoscopists. Thirteen AI‐related statements were presented to patients via an established online platform, while 23 statements were shared with endoscopists through professional networks. Responses were captured using 5‐point Likert scales and analyzed with non‐parametric tests, including subgroup comparisons by age, gender, and endoscopic experience. Results A total of 1237 patients and 476 endoscopists participated. Most patients supported AI in image analysis (75.5%) but emphasized the need for endoscopist oversight (92.3%). Among endoscopists, 90.3% believed AI improves endoscopy quality, and 85.3% believed it benefits outcomes. Concerns were raised about liability (47%), operator dependency (34.8%), and procedure time (49%). Most respondents felt primary responsibility for AI‐related errors should rest with the endoscopist. Younger and male patients reported greater trust in AI. Conclusions Patients and endoscopists are generally supportive of AI in GI endoscopy, especially as an adjunct to human expertise. However, key concerns—including accountability, trust, and clinical integration—must be addressed to ensure responsible and effective adoption.

ABSTRACT In response to the World Health Organization's (WHO) Global Initiative on Artificial Intelligence (AI) for Health, the World Endoscopy Organization (WEO) highlights the unique challenges and opportunities AI presents for gastrointestinal endoscopy, particularly in resource‐limited settings. While AI technologies have shown promise in improving diagnostic accuracy and efficiency in high‐resource environments, their implementation in low‐ and middle‐income countries is hindered by infrastructural, economic, regulatory, and training barriers. This commentary explores how these challenges may exacerbate existing healthcare disparities, emphasizing the need for localized datasets, affordable AI models, simplified regulatory frameworks, and workforce capacity building. The WEO supports WHO's call for equitable AI deployment and advocates for region‐specific solutions, including mobile and offline AI tools, public‐private partnerships, locally developed algorithms aligned with prevalent disease patterns, and a flexibly adapted regulatory framework. By leveraging WEO's training networks and fostering collaboration among governments, clinicians, and industry, the integration of AI into endoscopy can become more accessible and relevant to underserved populations. The commentary underscores that AI should not be seen as a luxury but as a tool to bridge global disparities in care quality. Ensuring responsible and inclusive AI integration requires both global coordination and context‐specific adaptations to truly benefit all healthcare systems.