Artificial intelligence in functional gastrointestinal disorders: From symptom recognition to personalised management

Abstract

Functional gastrointestinal disorders, now termed disorders of gut-brain interaction, are heterogeneous conditions shaped by psychological, physiological, microbial, and environmental factors.Diagnosis and treatment remain difficult because symptoms overlap, trajectories fluctuate, and no single objective biomarker exists.This minireview synthesises human evidence for artificial intelligence (AI) in symptom classification, digital phenotyping, microbiome and multi-omics prediction, treatment-response estimation, wearable monitoring, and language-based care.Targeted PubMed searches were updated through September 20, 2026.Current studies show feasibility, but most use small, single-centre cohorts, retrospective designs, or internal validation; calibration and prospective impact evaluation are uncommon.The most plausible near-term role of AI is therefore clinical augmentation: Identifying longitudinal patterns, supporting shared decisions, and detecting changes that require reassessment while preserving human oversight and patient autonomy.Large language models may improve education and communication, but disorder-specific evaluations reveal imperfect diagnosis and treatment recommendations with marked overconfidence.Translation requires representative cohorts that include overlapping organic disease, explicit endpoints despite the absence of a diagnostic gold standard, external validation, calibration, equity assessment, and prospective evaluation of patient benefit.AI should be judged by outcomes and care experience, not discrimination alone.