What is AI inventory optimisation?
Inventory management in retail is a balancing act: too much stock means tied-up capital and markdowns, too little means lost revenue and dissatisfied customers. According to IHL Group, excess inventory costs retailers worldwide $362 billion per year, while stockouts cause $634 billion in missed revenue.
AI inventory optimisation analyses sales patterns, seasonal influences and external factors to determine optimal stock levels per product and per location.
How does it work?
Machine learning models analyse your sales history per SKU, category and location. They identify patterns that are invisible manually: correlations with weather, events, pay dates and marketing campaigns.
The system automatically generates order suggestions, predicts slow-movers that are candidates for markdown and flags impending stockouts early.
What does it deliver?
Retailers report 25% less overstock, 40% fewer stockouts and 10–15% lower inventory costs. The freed-up working capital can be invested in growth. According to McKinsey, AI-driven supply chains improve inventory efficiency by 20–50%.