This whitepaper explains how AI can improve profitability in inventory management by reducing waste, stockouts, and manual effort while improving forecasting and decision-making across sourcing, storage, and fulfillment. It outlines where costs accumulate across the inventory lifecycle (planning, procurement, warehousing, tracking, replenishment, returns, risk, compliance, and obsolescence), noting that many businesses have 20–40% of assets tied up in inventory and that carrying costs can reach 40% or more when fully tallied (pages 4–6). It highlights AI use cases such as cash-flow forecasting (freeing up to 20% of cash), real-time monitoring and alerts, automated tracking, better warehouse layout and picking, improved customer and employee satisfaction, forecast error reduction (20–50%),

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