This investigation examines AI's impact on transport management, suggesting improvements in efficiency and cost reduction.
As global supply chains become increasingly volatile, the limitations of static, legacy transportation management systems have become glaringly apparent. The transition to SAP S/4HANA represents more than a mere software upgrade; it is a foundational shift that enables the integration of Artificial Intelligence (AI) into transportation logistics. This paper investigates the revolutionary impact of AI on Transport Management (TM) within the SAP S/4HANA environment. It explores how in-memory computing facilitates real-time data processing, allowing AI algorithms to transform transportation from a reactive function into a predictive and autonomous operation. Specifically, the study examines AI-driven advancements in dynamic route optimization, predictive freight auditing, and real-time shipment visibility. The findings suggest that the symbiosis of S/4HANA and AI creates a self-optimizing logistics network capable of significantly reducing costs and improving service levels.
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Jose A Kipper (2023) studied this question.
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