The Future of Artificial Intelligence-driven Personalized Nutrition in Gastroenterology and Hepatology: Emerging Trends and Perspectives

Nutrition plays a pivotal role in the prevention and management of gastrointestinal and hepatic diseases, yet dietary guidance remains generic, limiting its effectiveness. Conditions such as inflammatory bowel disease, irritable bowel syndrome, metabolic dysfunction-associated steatotic liver disease, celiac disease, and gastroesophageal reflux disease are significantly influenced by dietary factors. Personalized nutrition has emerged as a promising strategy to tailor interventions, but conventional approaches fail to account for individual metabolic, genetic, and microbiome variability, limiting their clinical impact. The rapid rise of artificial intelligence (AI) has transformed precision nutrition by integrating genomics, microbiome profiles, metabolic markers, and real-time dietary tracking to generate individualized recommendations. AI-driven systems are advancing dietary assessment, condition-specific nutrition optimization, and continuous monitoring through tools such as wearable devices and natural language processing-based diet analysis. These innovations hold transformative potential in gastroenterology and hepatology, offering dynamic, patient-specific strategies that may enhance clinical outcomes. However, challenges remain, including the lack of standardized AI-driven protocols, ethical concerns such as bias and data privacy, limited clinical validation, and the underrepresentation of nutrition in many current AI applications. Opportunities for progress include developing federated learning models, expanding real-world validation studies, and designing regulatory and ethical frameworks for safe implementation. This narrative review synthesizes literature published between 2015 and 2025 across five databases, highlighting key applications, limitations, and future directions of AI-driven personalized nutrition in gastroenterology and hepatology. It provides insights into how AI could reshape patient-centered care through more individualized, effective, and scalable dietary strategies.