AI Spend reports

Not everyone has this

Tokenomics is an optional module. If you can’t see it in the menu, it isn’t switched on for your workspace — ask an admin to turn it on under Settings ▸ Workspace Settings ▸ Features.

AI spend behaves unlike anything else on your bill. It’s consumption-based with no capacity to rightsize, the unit price changes when someone switches model, and a single badly-written prompt loop can cost more than a server. It gets its own reports for that reason.

Five views

View	Answers
AI Spend	What are we spending, by provider — tokens, seats and compute together
AI Spend by Model	Which models, with the input/output mix and blended unit cost
AI Spend by Application	Which application, team and cost group the spend belongs to
Token Spend & Forecast	Where the month lands, against budget
Cost per 1K / 1M Tokens	The unit rate over time, and the cache-hit rate driving it

The number to watch

Cost per 1K / 1M tokens is the AI equivalent of unit economics. Total AI spend going up while cost per million tokens goes down means you’re getting more work done more efficiently — a good month that looks like a bad one on the total alone.

Cache-hit rate is the biggest lever on that rate, which is why it sits on the same view.

What’s live and what isn’t

Provider coverage is uneven today

Spend on AI services billed through your cloud provider is real. GitHub Copilot usage is live, including per-model breakdown.

Token counts, cache-hit rates and blended cost per million for the other providers — Anthropic, OpenAI, Cursor — are examples until those usage APIs are connected. Where a view has no feed it says Token telemetry not connected rather than showing a plausible number.

So: treat the cost figures as real and the fine-grained token metrics as directional unless the screen tells you otherwise. Full detail on what isn’t available yet.

Filters

Period, provider, cost group and cost basis all apply — the AI vendors are billing providers like any other, so the provider chip genuinely slices these views.

Virtual tags don’t: token telemetry carries no resource tags, and the chip says so.

Where the other AI screens are

This report is about cost. The adoption question — who’s using which tool, and are the seats worth it — is on AI tool adoption, and the optimization suggestions are on TokenMaxing.