Generative AI for pre-consultation mental health triage in disorders of gut-brain interaction

Disorders of gut-brain interaction (DGBI) are common, disabling, and frequently accompanied by anxiety, depressive symptoms, sleep disturbance, symptom-related fear, and repeated health care use. In routine gastroenterology practice, these problems are often recognized late, after fragmented histories, multiple visits, and avoidable investigations. Recent work on generative artificial intelligence (GenAI) and conversational systems suggests a narrower and more practical clinical use case than autonomous diagnosis: supervised pre-consultation triage. We propose that DGBI is a suitable setting for this approach because triage depends on integrating symptom narratives, prior investigations, alarm features, and psychosocial context rather than on a single test result. A GenAI-enabled intake tool could summarize patient-entered histories, incorporate brief distress screening and symptom diaries, flag possible medical or psychiatric escalation, and help route patients toward standard gastroenterology review, integrated psychogastroenterology, dietetic input, or urgent assessment. Its value would lie in making the first consultation more efficient and more clinically informed, not in replacing specialist judgment. For such systems to be acceptable, five conditions are essential: a narrowly defined triage task, multidomain but proportionate data collection, explicit rules for medical and psychiatric escalation, clinician review before action, and prospective evaluation across workflow, safety, equity, and patient acceptability. DGBI offers a realistic opportunity to develop GenAI tools that are useful precisely because they are constrained, auditable, and embedded in multidisciplinary care.