AI agents in distribution: 5 use cases that actually deliver value
AI in ERPs is often a buzzword. Here are 5 operational use cases where AI agents bring measurable value, without cliché or hype.
1. Smart overdue account follow-ups
Instead of a generic automated email, the agent looks at account history: "this customer always pays at 35 days, no big deal" or "this customer has 4 invoices late out of 6, urgent". Right message at right time.
Observed impact: -25% average delay, +15% recovery on invoices > 90 days, in 4 months.
2. Margin anomaly detection
The agent monitors every sale and flags abnormally low margins: a product sold below minimum guaranteed price, an excessive discount given by a rep, a supplier cost that increased without pass-through.
Without agent: these errors get lost in the mass. With: they surface on screen the next day, and the decision is taken quickly.
3. Stock-out forecasting by seasonality
The agent looks at sales history per SKU over 2-3 years, identifies seasonality, and alerts 4-6 weeks before likely stockout. "You'll run out of 235/65R17 winter in early October — order 800 units now."
Particularly useful in automotive (seasonal swaps) and food distribution (holidays).
4. Sales recommendations
When a customer calls to order 4 tires, the agent checks: did they have a TPMS program linked to this size? How many tires did they buy in the last 24 months? Is there a compatible product on promotion?
No spam — just the 1-2 most relevant opportunities, presented to the sales rep in real time.
5. Delivery anomalies
The agent compares today's deliveries with historical patterns: a driver taking 40% longer than usual, a customer who has repeatedly accused of delay, a route drifting.
You intervene before the problem becomes a customer dispute.