AI Solutions for Sustainable Agricultural Supply Chains

Abstract

The agricultural supply chain faces mounting sustainability challenges, including resource inefficiencies, climate-induced disruptions, and environmental degradation. Artificial Intelligence (AI) has emerged as a transformative solution, offering predictive analytics, machine learning, and big data tools to optimize agricultural production, streamline logistics, and enhance supply chain resilience. This paper presents a theoretical framework for integrating AI into sustainable food supply chains, emphasizing its role in improving ecological and economic efficiency. Through an extensive literature review, the study explores AI’s applications in crop planning, logistics optimization, and supply chain adaptability. It further examines key theoretical foundations, barriers to AI adoption, and strategic approaches to leveraging AI for sustainable development. By bridging AI research with sustainability discourse, this paper provides insights for policymakers, industry leaders, and researchers on strategic AI adoption to foster resilient and low-carbon food supply networks.