Perspectives, challenges and future of artificial intelligence in personalised nutrition research

Personalised nutrition (PN) has emerged as an approach to optimise individual health outcomes through more targeted and tailored dietary recommendations based on unique genetic, phenotypic, medical, lifestyle and contextual factors. The application of artificial intelligence (AI) presents an opportunity to achieve personalised nutrition advice at a scale that has population impact. This review introduces a nutrition audience to different AI applications and offers insights into the concepts of AI that might be relevant to the field of nutrition research. The current and future uses of AI in PN are discussed, as well as the potential benefits and challenges to their application. AI-driven solutions have the potential to improve health and reduce the risk of disease because they can consider more information about an individual in making recommendations. However, challenges such as data interoperability, ethical considerations, and model interpretability remain an issue limiting widespread use at this point. This review will provide a foundational understanding of the application of AI within PN and help to identify opportunities to leverage the potential of AI in transforming dietary guidance and enhancing health outcomes through innovative solutions.