AI-Driven Order-to-Cash.
Working capital recovery via AI agents for invoicing, dispute routing, collections, and cash application matching.
Typical mid-market ranges, not guarantees, your single target metric is agreed in week 1.
DSO sits at 55-75 days. The collections team is firefighting.
Disputes are resolved ad-hoc by whoever picks up the phone. Cash application is manually matched. Invoice errors caught downstream cost more to fix than to prevent. Working capital tied up in AR is one of the cleanest EBITDA-adjacent levers an operating partner can pull, and one of the hardest to fix without redesigning how the function operates.
Seven things, in order.
- Process redesign of the O2C cycle: order entry, invoicing, collections, dispute management, cash application.
- AI agents for invoice generation and pre-send validation: catching errors before they delay payment.
- AI agents for dispute identification, classification, and routing: prioritized by value and likelihood-to-resolve.
- AI agents for collections prioritization and outreach drafting, calibrated to customer payment patterns.
- AI agents for cash application matching, raising the auto-match rate and routing exceptions intelligently.
- Deduction analytics with root-cause categorization, surfacing systemic issues for upstream fix.
- Change management: collections team training, AR dashboards for the CFO and operating partner.
Calibrated, not promised.
| Metric | Typical range |
|---|---|
| DSO | 5-15% reduction |
| Collections FTE | 20-40% reduction |
| Disputes within SLA | +30-50% |
| Cash application auto-match | 60-70% → 85-95% |
| Working capital release | DSO Δ × daily revenue |
| Dispute resolution time | days → hours |
- ERP and AR system with accessible historical AR data.
- Defined collection policies (or willingness to define them in-engagement).
- Engaged CFO or VP Finance as executive sponsor.
Want to know if this is the right starting point?
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