Artificial intelligence-driven food and nutrition systems: from smart food production to personalized nutrition

Abstract

Artificial Intelligence (AI) is rapidly emerging as a technology that integrates sectors such as food production, manufacturing, supply-chain management, diet-related information, and personalized nutrition. By integrating machine learning, computer vision, predictive analytics, robotics, and large language models, AI is reshaping how food is produced, processed, evaluated, and consumed. In primary production, it enhances precision agriculture and resource optimization. During processing and distribution, AI-driven automation, quality control, and predictive systems enhance efficiency, safety, and supply-chain resilience. At the consumer interface, adaptive dietary recommendation systems integrate user profiles, food composition databases, clinical biomarkers, omics profiles, and behavioral feedback to generate personalized recommendations. Emerging hybrid AI approaches that combine computational intelligence with established nutritional science are also improving dietary assessment. For example, image-based systems using convolutional neural networks and transformer architectures demonstrate promising capabilities in automated food recognition and intake estimation. Despite these advances, AI-driven food and nutrition systems remain in an early translational phase, with substantial challenges limiting widespread adoption. These include heterogeneous and incomplete datasets, limited real-world validation, insufficient model transparency, regulatory and ethical uncertainties, and unequal accessibility among small-scale producers and vulnerable populations. Addressing these barriers will require interdisciplinary collaboration among food scientists, nutritionists, data scientists, policymakers, and industry stakeholders. This perspective examines the emerging role of AI as a transformative force in nutritional intelligence, smart food manufacturing, sustainable food systems, and precision nutrition. The article also discusses key opportunities and challenges for its responsible integration into future food systems.