Your team runs demand forecasts with machine learning. Inventory optimization models run overnight. Supplier analytics dashboards refresh automatically. Adoption is solid.
Margins barely moved. Inventory sits unchanged. Lead times haven’t shifted.
A recent study of 1,250 companies found that 95% see zero measurable ROI from their AI investments in supply chain. Not because your team isn’t using the tools. They are. They’re just using them on work that doesn’t touch your bottom line.
The gap isn’t adoption. It’s selection.
The 5% automate dollars, not processes
Here’s what separates winners from everyone else.
Top performers concentrate 70% of their supply chain AI budget on five areas: demand-to-supply planning, logistics optimization, supplier quality and risk, inventory allocation, and procurement. Not internal dashboards. Not meeting automation. Not status report summaries.
The results show up in numbers. These functions drive 20% cost reductions and 15% cash flow improvements compared to administrative work.
A beverage company deployed AI-powered demand forecasting across 47 distribution centers. They cut safety stock by $8M annually. A semiconductor manufacturer automated supplier quality monitoring across 200+ vendors. They reduced defect-related delays by 35%.
The 95%? They automated supply chain meeting notes and built internal reporting dashboards. Process time saved, sure. Money made? No.
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