Context: Inventory turnover doesn't stall because teams lack forecasts, it stalls because decisions arrive after demand has already moved.

Challenges: Demand signals change but replenishment continues on autopilot, allocation follows prior assumptions, and ownership is spread across functions, so no one steps in when momentum slows until ageing inventory is already visible in reports.

Solution: The Inventory Turnover Guidance Agent, an AI agent built using Microsoft Copilot Studio, monitors demand velocity and ageing trajectories as they shift and intervenes during replenishment and allocation decisions, flagging slowing inventory before excess locks in.

Impact: Retailers adopting this approach see forced markdowns decline and working capital free up naturally, with turnover improving as a consequence of timely decisions rather than corrective pressure later.