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A practical executive guide to governed agentic AI in manufacturing and supply chains, covering decision orchestration, supplier risk, plant operations, human oversight, governance, and the path from AI pilots to production workflows.
Agentic AI is moving enterprise AI from systems that describe, predict, or explain toward systems that can participate in multi-step operational workflows. In manufacturing and supply chain, that shift matters because important decisions rarely sit inside one application or one team. Supplier terms may live with procurement, demand assumptions with planning, production constraints with operations, economic baselines with finance, and system access with IT.
The on-demand DataRobot and Supply Chain Now session, “$2.5B in 72 Hours: What Agentic AI Looks Like When It Actually Works,” focuses on that operating challenge. The session describes a tariff signal that put $2.5 billion in revenue at risk and was resolved in 72 hours instead of weeks, with human sign-off at every step. It also examines agent workforces across multi-tier supplier risk, plant operations, and aftermarket service.¹
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