Your Supply Chain Has an Enterprise Debt Problem
Systems got added region by region, asset by asset, usually to solve whatever problem was in front of someone at the time.
Home » Blogs » Think Tank » Your Supply Chain Has an Enterprise Debt Problem Think Tank RSS Your Supply Chain Has an Enterprise Debt Problem October 28, 2026 Mantej Singh Randhawa, SCB Contributor Ask any logistics or supply chain leader whether artificial intelligence can improve forecasting, routing or fulfillment, and you'll almost always get a yes. But if you ask whether their organization is actually ready to run AI at scale, confidence drops off.
That gap is about the foundation underneath the technology. And the challenge has only become more visible with agentic AI. For an agentic system to be able to optimize a shipment lane or catch an exception before it turns into a delay, it needs trusted data, consistent workflows and clearly defined business rules to act on. In many supply chain organizations today, that groundwork just isn't there yet. It's simply the legacy of how these networks were built in the first place.
Most supply chain leaders already feel this weight building. Systems got added region by region, asset by asset, usually to solve whatever problem was in front of someone at the time rather than to fit into some larger, coherent operating model. Shipment visibility lives in one platform, asset tracking in another, supplier data somewhere else entirely, and exceptions get worked out by hand because that's faster than fixing what's actually broken. None of this is new. What's changed is the cost of leaving it alone.
This story was originally published by SupplyChainBrain. Read the full story at SupplyChainBrain →
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