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AI Forecasting Is Actually Useful for E-commerce Inventory — For About Three Things
Most e-commerce sellers I talk to are sitting on one of two problems: too much of the wrong stuff, or stockouts on the things that are actually moving. Often both, at the same time, in the same warehouse.
That’s a forecasting problem. It’s older than the internet. What’s changed is that AI is genuinely useful for it now — if you point it at the right things and stop expecting it to read your mind.
WHERE IT EARNS ITS KEEP
Velocity pattern recognition across a large SKU catalog.
Say you run 800 active SKUs. You can’t manually track the sales curve on all of them, spot that SKU 317 has been trending up 12% week-over-week for a month, and tie that to a seasonal search spike before your next reorder point hits.
A model can. It can do it across all 800 at once while you’re at the dock dealing with a receiving problem.
That isn’t hype. That’s just math running faster than a person can.
WHERE IT BEATS STATIC RULES
A fixed “reorder at 50 units” rule doesn’t know that a promotion goes live Thursday. It doesn’t know your supplier lead time crept from 7 days to 11 days last quarter. It doesn’t know that last April looked nothing like this…
