# Know your AI gross margin per customer. Forecast next quarter within a stated band.

> Know your AI gross margin per customer, forecast next quarter's spend within a stated band, track commitment burn-down against Azure, AWS and Anthropic contracts, and produce chargeback that survives audit.

Source: https://tokenomy.ai/for-finance
Last updated: 2026-09-07
Publisher: Tokenomy — FinOps for AI
License: free to quote with attribution and a link to the source URL.

Four situations put AI spend on the CFO's desk: inference as cost of goods sold, forecast and accrual, commitment burn-down, and audit-grade chargeback. Tokenomy answers each from the metered ledger, with assumptions visible and the price record dated underneath.

## Inference is COGS

Contribution margin per account, per feature and per plan — ranked worst-first, so accounts priced below inference cost surface before renewal rather than after.

## Forecast and accrual

Usage-driven spend is hard to budget and harder to accrue. Forecasts carry an explicit confidence band, month-to-date accrual comes with its method attached, and variance history shows whether the band earns its credibility.

## Commit burn-down

Enter Azure, AWS or Anthropic commitment terms once. Track burn against required pace, see the projected exhaustion or shortfall date, and the dollars at risk if nothing changes.

## Audit-grade chargeback

Allocation to business units with method, assumptions and source records attached to every line — exportable, reproducible and dated, so last quarter's number can be regenerated this quarter.

## Metered, reconciled or modeled

Every figure carries its provenance. Nothing is presented as measured that was not measured, and no savings percentage appears on the finance surface at all.

## Related pages

- [For engineering teams](https://tokenomy.ai/for-engineering)
- [Economic assessment](https://tokenomy.ai/assessment)
- [Build a CFO briefing](https://tokenomy.ai/waste)
- [Pricing](https://tokenomy.ai/pricing)