Implementing AI in agri-food supply chain security from the multi-stakeholder perspective: an exploratory review and future directions

Purpose In agri-food supply chains (AFSCs), food waste can be minimized, and food security can be improved with the assistance of artificial intelligence (AI). But the implementation of AI in AFSC is difficult due to various barriers. Therefore, this paper aims to examine the barriers in the AFSC and explores how these challenges can be addressed using AI. Design/methodology/approach This article draws on academic research, business best practices and legislative frameworks to provide suggestions from a conceptual and qualitative perspective. This critical assessment takes into account the viewpoints of many stakeholders and examines the difficulties of using AI technology in AFSC. Findings Our findings reveal the various barriers, such as for producers (lack of expertise, initial cost, data privacy concerns), for food processors (regulatory compliance, legacy systems, quality control, regulations and standards), for distributors (logistical challenges, seasonal variability, sustainability concerns, regulatory compliance) and for consumers (limited access to information, quality and freshness, complexity of the supply chain and cost fluctuations). Originality/value This study does an in-depth analysis focusing on the application of AI or the challenges faced by it from the perspective of all major stakeholders involved in AFSC. Our study not only identifies these challenges, but it also recommends what efforts are necessary to mitigate these challenges.