Applications of generative and predictive AI in nutrition and dietetics: a narrative review

Abstract

In the era of Industry 4.0, where automation and digitalization are central to processes and systems, artificial intelligence (AI) is becoming an essential tool that provides innovative solutions across various fields. Nutrition, as a vital component of public health, is among the areas increasingly shaped by the integration of AI technologies. This review aims to identify the strengths and limitations of these models, assess their potential as decision-support tools for healthcare professionals, and shed light on the existing gaps in the field. A comprehensive literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar databases to identify relevant studies published between January 2019 and May 2025. A total of 44 articles were included in the review. The main findings suggest that the application of AI in nutrition is still emerging, with the majority of studies centered on dietary assessment. There is comparatively less emphasis on food estimation, disease prediction, lifestyle interventions, and understanding diet-related diseases. Further clinical studies are necessary to evaluate the effectiveness of AI-based interventions.

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