Research on AI-Driven Optimization of Supply Chain Collaborative Management for Agri-Related Enterprises in Henan Province under Digital Rural Development

Abstract

Against the backdrop of the deep integration of digital rural development and the rural revitalization strategy, Henan Province
one of China's major agricultural regionsfaces prominent challenges in the supply chains of agri-related enterprises, including insufficient collaborative efficiency, information asymmetry, and imbalanced resource allocation. The deep application of artificial intelligence
(AI) technologies provides an effective pathway to address these challenges. Based on the practical experience of digital rural development in Henan Province, this study analyzes the practical significance and existing problems of AI-driven supply chain collaborative
management for agri-related enterprises. An optimization framework is constructed from four dimensions: information sharing, production
scheduling, logistics distribution, and risk prevention and control. By integrating case studies of local agri-related enterprises in Henan,
the feasibility of the proposed optimization pathways is empirically examined. Furthermore, safeguard measures are proposed from the
perspectives of policy support, technological adaptation, and talent cultivation, with the aim of providing reference insights for agri-related
enterprises in Henan Province to achieve high-quality supply chain development by leveraging opportunities arising from digital rural development.