A leading grocery retailer operating across Asia and the Middle East reduced lost sales by 30 percent by adopting AI‑native demand forecasting. Previously reliant on manual processes and data triangulation from multiple sources, the retailer faced high anomalies, low predictability, and added workload for buyers managing downstream planning. Forecasting demand accurately across brick‑and‑mortar, quick‑commerce marketplaces, and food apps proved difficult, especially across diverse categories such as ambient, frozen, chilled, and café offerings. These inefficiencies led to estimated sales losses of 2–4 percent due to stockouts and overstocking. AI‑driven forecasting improved accuracy, efficiency, and sales outcomes.

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