Quick Answer
Explore why agentic AI supply chain pilots stall before production and how enterprise context, decision rights, human oversight, governance, exception handling, and outcome verification can help move workflows toward operational deployment.
Agentic AI pilots can look convincing long before they are ready for production. A controlled demonstration may show an agent identifying a supplier issue, analyzing a tariff change, investigating a plant exception, or preparing an aftermarket response. Production is different. The agent must work with live enterprise context, respect permissions, survive incomplete or conflicting data, escalate material decisions, and leave enough evidence for people to understand what happened.
The DataRobot and Supply Chain Now on-demand webinar, $2.5B in 72 Hours: What Agentic AI Looks Like When It Actually Works, frames this gap through real supply-chain scenarios. The session describes a tariff situation involving $2.5 billion in revenue risk addressed in 72 hours rather than weeks, while retaining human sign-off in the workflow.¹
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