In response to the fluctuating demand and supply dynamics observed over the past several years, numerous retailers are turning to artificial intelligence (AI) to refine their inventory management strategies. AI encompasses a wide array of technologies, software, and systems capable of analyzing extensive and complex data sets to make informed predictions. A survey conducted by KPMG involving retail and consumer executives revealed a 64% inclination towards employing AI for trend analysis and predictive inventory management. Another study in 2023 by BlueYonder, a supply chain software provider, indicated that demand forecasting and inventory optimization are key areas where AI and machine learning technologies are being applied by supply chain leaders.
Shelf Engine, a forecasting solutions provider, describes its approach as creating daily, probabilistic models for each unique stock-keeping unit (SKU) in every store. These models are constructed using a combination of historical sales data, daily sales figures, and external information such as local events, news trends, weather conditions, holidays, and even school schedules. To facilitate automated ordering, Shelf Engine employs profit models aimed at optimizing stock levels to ensure the availability of the freshest food for Dollar General customers. The company’s platform is crafted to autonomously generate orders to achieve this goal.
Walmart is among the other retailers that have integrated AI into their supply chain management, specifically for demand forecasting. Similarly, American Eagle Outfitters introduced an AI tool last year designed to maintain optimal inventory levels while meeting consumer demands, a move that has reportedly enhanced in-stock levels. Amazon has also developed AI applications to fine-tune inventory predictions in its fulfillment centers, enhancing operational efficiency.
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