Replenishment & Restocking

Leading retailers have demonstrated measurable success with AI-driven replenishment systems. Walmart rolled out agentic AI in several stores to improve inventory management. These systems use computer vision and shelf sensors to monitor product levels, and when stock gets low, the AI triggers restocking orders automatically. In one pilot store, Walmart cut out-of-stock events by 30% within six months. By deploying autonomous inventory robots in over 500 U.S. stores, the company has also reduced inventory inaccuracies by 10% and cut labor costs associated with manual checks.

The fashion retail sector provides another compelling case study. H&M has implemented AI to improve inventory management by capturing data from search engines and blogs to learn about the latest fashion trends. This data helps H&M make informed decisions about restocking popular items and distributing them throughout their franchises. Similarly, specialty retailers have achieved remarkable results. Lowe’s leverages AI to revolutionize inventory management, using small cameras on shelves to monitor stock levels in real time. When a gap is detected, it sends an alert to store devices, ensuring staff know when to restock.

Dutch retailer Shoeby, which had been managing stock manually across its 240 stores, switched to the AI Replenisher from Wair and increased inventory turnover by 4%, reduced stock on hand by 2% and increased revenue by 3%, according to Wair.

Jeans maker Levi Strauss implemented AI-driven store-replenishment software that automatically adjusts shipments based on current sales data and customer behavior, ensuring high-demand product are in stock and preventing the accumulation of inventory at low-performing stores. 151 2.3 Fulfill (Supply Chain & Logistics)