Artificial Intelligence in Extended Agri-Food Supply Chain: A Short Review Based on Bibliometric Analysis

Abstract

Climate change and population growth are triggering a digital transformation in agriculture. Consequently, agri-food supply chains are becoming more intelligent, producing vast amounts of data and pushing the boundaries of the traditional food lifecycle. However, artificial intelligence (AI) for the extended agri-food supply chain is only beginning to emerge. This paper presents a short literature review of eighteen papers on the intelligent agri-food supply chain. The bibliometric analysis reveals key research clusters and current trends in the AI-enabled stages of food production, distribution, and sustainable consumption. The important advances of AI in traditional stages of production need to be expanded with intelligent planning for demand uncertainty and personalized needs of end-customers, storage optimization, waste reduction in the post-production phase (e.g., distribution and recycling), and boundary-spanning analytics. For theory, this work highlights mature areas for AI adoption in agri-food and identifies opportunities for future research in the extended agri-food supply chain. For practice, the review findings can inspire startups interested in extended agri-food ecosystems and incumbents in their pilot projects for the intelligent and sustainable digital transformation of agri-food. AI techniques can contribute to close the loop of sustainable agri-food supply chains