Enterprise Resource Planning (ERP) systems, specifically SAP, have long served as the backbone of organizational logistics, providing structured data management and transactional capabilities. However, the static nature of traditional ERP configurations is increasingly insufficient for the volatility of modern global supply chains. This paper examines the application of Artificial Intelligence (AI) within SAP logistics environments, highlighting how machine learning and predictive analytics transform the system from a passive repository into an intelligent decision engine. The analysis focuses on key SAP modules, including Integrated Business Planning (IBP), Transportation Management (TM), and Extended Warehouse Management (EWM). The study concludes that the integration of AI into SAP ecosystems enhances forecast accuracy, automates exception handling, and facilitates the transition toward the "Intelligent Enterprise," while simultaneously acknowledging challenges related to data governance and organizational change.
Kipper (2025) studied this question.