Inventory Management / Product Lifecycle Tracking

Diaper brand Kudos implemented an AI tool called EverX for inventory management and forecasting. The system enabled the company to determine demand needs across each SKU and geographic zone for real-time warehouse inventory requirements. It helped identify where to decrease fulfillment spending or add products during replenishment—for example, directing 70% of a sold-out SKU to the nearest warehouse and 30% to another—while ensuring reporting accuracy to avoid costly miscounts.

A leading multichannel retailer achieved meaningful results using an AI-powered Decision Intelligence for markdown optimization. By applying pricing recommendations to just 15% of its stock file, the retailer identified opportunities that drove savings of £2.4 million ($3 million), equating to additional margin worth approximately 1% of its overall turnover. The system also led to increased team productivity. Levi Strauss partnered with SAS to implement analytics that view and analyze millions of consumer demand signals, enabling the retailer to create demand plans targeting specific geographies down to the neighborhood level. This granular approach demonstrates how AI can transform inventory planning from reactive to predictive.

Walmart’s implementation of AI significantly increased its inventory turnover rate, indicating faster movement of goods and reduced holding costs, according to 2024 research from CDO TIMES and Harvard Business Review. Amazon’s inventory turnover rate has improved through AI-driven systems that create predictive models to anticipate demand shifts. For example, the system adjusts inventory levels in nearby warehouses when storms are predicted to affect specific regions, reducing both stockouts and excess inventory costs.