Artificial Intelligence in the Agri-Food Supply Chain: How it Might Facilitate Circular Economy Practices?

The agri-food supply chain faces a complex array of global challenges that significantly affect both environmental sustainability and societal well-being. Among the most pressing issues is the sector’s substantial contribution to environmental degradation, driven by resource-intensive practices in food production. These practices result in severe consequences for land use, water resources, and greenhouse gas emissions, exacerbating climate change and environmental damage (Willett et al., 2019). Simultaneously, ensuring global food security has become an increasingly urgent issue, with food demand projected to rise sharply as the global population expands. The growing scarcity of food resources, compounded by climate change and economic inequality, underscores the need for the adoption of Agri 5.0 and Circular Economy (CE) principles (Akundi et al. 2022; Belhadi et al. 2021; Liu et al. 2021). However, the agri-food sector remains not only linear in its supply chain but also fragmented, with a wide range of actors pursuing often conflicting objectives and misaligned goals. These challenges are particularly evident in the tension between global sustainability goals - such as environmental preservation and biodiversity - and the local objectives of individual stakeholders, such as maximizing productivity. This misalignment complicates the adoption of sustainable practices.