The actual situation is different. Companies struggle to get competitive value using AI, and there are several reasons for this, varying from overpromised sales messages down to how companies apply AI.
Applying AI for cross-functional task execution and optimization that includes all functional areas requires a holistic approach using internal and external data. A cherry-picking approach focusing on selected functional areas of the supply chain will not bring any miracles for task execution and optimization. Then you are stuck in zoning, dedicated spaces for resources and silos of optimization.
Another mistake many companies make is installing AI to provide data for manual task execution and optimization decisions. This is, unfortunately, another showstopper. Because humans can’t recognize patterns supplied by internal and external data, this is too complex.
What is the right approach to maximal output when using AI for task execution and optimization?
Miracles can happen if you use AI for decisions across functional areas; this will help you to change from a manual-run operation to a highly efficient and system-run environment without manual decisions.
The post What is AI-managed task execution and optimization, and does it work? appeared first on Logistics Viewpoints.