AI-Based Predictive Analytics for Sustainable Demand Forecasting in Agri-Food Logistics

Predictive analytics, which is an AI technology, is changing the logistics of agri-foods by enhancing sustainability and demand forecasting. The conventional predictive approaches do not normally reflect their dynamic aspects, including weather fluctuations, market behavior and consumer behaviors, resulting into inefficiencies and food wastage. This chapter describes an AI-based framework that combines multi-source data, machine learning models, and decision support systems to come up with correct and real-time demand forecasts. The strategy facilitates optimal inventory control, effective distribution strategy, and minimized environmental concerns. There are enormous evidences of case studies showing enhancement of accuracy in forecasts, reduction of wastes, and efficiency in the operations. The results address the possible opportunities of AI assisting the resilient, adaptive, and sustainable food supply chains in the fast-changing global food system.

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