Inbound Logistics | July 2026

Where AI Delivers Operational Value Demand forecasting Freight matching

AI’s potential in supply chains seems

Warehouse slotting Shipment visibility

boundless. But what do industry insiders see in terms of quantifiable eciency gains? Does artificial intelligence measure up? Short answer: in spots.

By NICOLAI VON BISMARCK , Partner, McKinsey & Company

We see AI deliver clear operational value in structured, rules- based environments where workows are repeatable and

Where AI does not yet deliver value is judgment-based, probabilistic work that requires in-the-moment human decisions, nuanced expertise, or complex case management. In logistics, this means exception handling on damaged or misdirected freight, complex customs brokerage, and supplier relationship negotiations where context, trust, and improvisation still matter. The challenge is both technology limitations—AI struggles with ambiguity and novel scenarios—and human adoption, where frontline workers resist tools that don’t match how they make decisions. The gap between AI deployment and AI impact remains wide. Many organizations are taking an organic, uncoordinated experimentation strategy that lacks clear linkage to value. Companies that can identify their unique economic leverage points—where AI can create disproportionate impact—and prioritize these high-impact areas are more likely to see meaningful, scalable returns.

outcomes are measurable. In logistics, the front-runner domains include demand forecasting, freight matching, warehouse

slotting, and shipment visibility— environments where AI’s ability to

process volume, maintain availability, and enforce consistency transforms the economics of operations in ways that were previously unachievable. McKinsey’s research on AI in distribution operations quanties the impact: reductions of 20 to 30% in inventory, 5 to 20% in logistics costs, and 5 to 15% in procurement spend. We see companies land rmly in those ranges— one last-mile operator with more than 10,000 vehicles achieved $30 million to $35 million in savings from AI-powered virtual dispatcher agents—a 15x return on a $2-million investment.

SUPPLIER RISK MONITORING

Share of CEOs surveyed who say AI is delivering measurable value in supplier risk monitoring—yet they also say there are barriers in further scaling AI use in the supply chain including data quality (38%), lack of skills (30%), and clarity around ROI (29%), according to The Global Supply Chain Resilience Outlook report by Proxima, a procurement and supply chain consultancy (part of Bain & Company).* 51 % *The report surveyed more than 500 CEOs at businesses generating more than $500 million in annual revenue across the United States, UK, Australia, Singapore, and Germany.

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