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Explore five essential questions supply chain leaders should ask before investing in AI planning agents. Learn how to evaluate data reliability, scenario feasibility, decision authority, governance, and measurable business outcomes beyond traditional APS systems.
Advanced planning and scheduling (APS) systems help supply chain teams model constraints, balance supply and demand, and evaluate feasible plans. Yet an exception alert is not the same as an accountable decision. A delayed component may demand supplier escalation, inventory transfer, production resequencing, or a revised customer promise. Each response affects different stakeholders.
The emerging case for planning agents is that they may help connect these fragmented steps: investigate a signal, retrieve permitted evidence, compare scenarios, and prepare a recommendation for review. That does not mean every agent can act autonomously or that an APS investment has become obsolete. Gartner has warned buyers about “agent washing,” in which established capabilities are presented as agentic without the underlying ability to perform meaningful multistep work.¹
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