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Explore how manufacturing supply chains can move agentic AI from experimentation to production through governed decision workflows, enterprise context, human oversight, observability, and controlled execution.
The operating lesson is not that every supply-chain decision should be delegated to an autonomous system. It is that the distance between a material signal and a governed response can be redesigned. Production-grade agentic AI depends on connected enterprise context, reliable access to operational systems, explicit decision rights, observability, and human oversight where consequences are material.
For supply-chain leaders, this changes the evaluation question. A dashboard can tell a team that a tariff, supplier, equipment, or warranty condition has changed. An agentic workflow is expected to help determine what that change means, which actions are permitted, what evidence supports the recommendation, and who must approve the next step. The difference is decision velocity with control, not automation for its own sake.
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