A Food Data-Nutrition Intelligence framework to support UK food system transformation

This review explores opportunities and challenges across data, health metrics, nutrition science, digital technology and policy in the context of healthier food system transformation. Rapid advancements in digital technology and artificial intelligence have reshaped how food is produced, formulated, marketed, purchased and consumed, with vast quantities of data generated across supply chains and retail environments. How individuals access, track and generate food and health information has shifted. Despite unprecedented data availability, fragmentation, diverging definitions, inconsistent health metrics and misaligned timelines across academia, policy, industry and technology limit effective and timely integration. This review develops two interrelated concepts, The Food Data Landscape (FDL) and Nutrition Intelligence (NI). It explores the structure and limitations of the FDL, considers the role of health metrics and describes technological developments and emerging NI applications. A conceptual Food Data-Nutrition Intelligence (FD-NI) Framework is presented providing a shared foundation for advancing more coherent research, policy and practice. This framework positions NI as an integrative layer capable of translating complex, fragmented data into actionable, evidence-based insights that can inform healthier decision making at scale. Transformative potential of AI will not be realised through technological advancement alone. Standardised data infrastructures, transparent assumptions, traceable decision making and collaborative governance frameworks that embed scientific integrity are key. Coordinated collaboration is critical to harness the full potential of NI to deliver meaningful, system-wide, timely transformation towards healthier, more sustainable diets. Future research should define stakeholder roles across the FDL and develop methodological, governance and evaluative frameworks to support responsible and impactful NI.