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Artificial Intelligence (AI) is transforming global food systems by reshaping how food is grown, processed, distributed, and consumed. Using machine learning, computer vision, sensor networks, and digital twins, AI enables automation, precision, and real-time decision-making across precision agriculture, smart manufacturing, supply-chain management, and personalized nutrition. These applications enhance productivity, traceability, and resource efficiency, supporting Sustainable Development Goals (SDGs) 2, 12, and 13. However, adoption remains uneven. Smallholder farmers and low- and middle-income countries face barriers such as limited digital infrastructure, lack of region-specific datasets, and minimal integration of local knowledge. These disparities intensify inequalities (SDGs 1 and 10) and raise governance concerns about data privacy, algorithmic bias, and energy consumption (SDG 16). Real-world validation in diverse agroecological contexts also remains limited. Unlike previous reviews focused mainly on technology, this paper uniquely integrates governance frameworks, ethical considerations, and regional disparities to provide a holistic understanding of AI’s role in sustainable food systems. Achieving equitable AI transformation will require participatory governance, open-access data, targeted investments, and globally harmonized policies aligned with the SDGs. Moving from the Fourth Industrial Revolution (IR4.0) to the human-centered IR5.0 will further emphasize collaboration, transparency, and social responsibility in future food innovation.
Azfaralariff et al. (Mon,) studied this question.