
AI in the Supply Chain: 5 Practical Use Cases That Deliver Value
Explore five practical AI supply chain use cases and the data, integration, governance, and KPIs required to turn each one into measurable value.
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Have you ever gone into a store and discovered the product you wanted is out of stock? Or, have you ever been glad that a hot-selling consumer product was in stock? Since the COVID-19 pandemic, it’s become routine that many consumer products are out of stock due to supply chain disruptions. When popular products are routinely in stock, even during heavy demand periods and during sales promotions, chances are that vendor managed inventory (VMI) programs are involved. VMI and co-managed procurement are driven by POS data and updates. These systems enable supply chain partners such as retailers, suppliers, distributors and manufacturers to automatically share inventory and point-of-sale (POS) data to create a lean, demand-driven supply chan. The trading partners in a transaction, often a retailer and a manufacturer, for example, gain better insights into actual demand and consumption patterns and are able to execute their supply chains accordingly. This is just one example of how collaboration is enabled by data sharing networks such as VMI platforms and B2B integration platforms where information is shared in near real time or in real time.

Explore five practical AI supply chain use cases and the data, integration, governance, and KPIs required to turn each one into measurable value.

Generix is proud to once again be recognized in Gartner 2026 Magic Quadrant™ for Warehouse Management Systems (WMS)

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