FinOps for AI · Microsoft estate
AI ROI for the Microsoft estate.
Most AI cost tools read Azure OpenAI as one more provider. CloudMonitor is Azure-native, so it sees the whole Microsoft AI bill in one pane: Azure OpenAI and Foundry tokens and PTUs, GitHub Copilot, and Microsoft 365 Copilot, reconciled to the FOCUS-conformed Azure bill you already pay.
One tenant, three AI bills
The Microsoft AI spend lives in three places.
In a Microsoft shop, AI spend arrives on three meters under one tenant, one agreement, and one identity plane. CloudMonitor brings all three into the same cost groups as the rest of your Azure estate.
Azure OpenAI & Foundry.
Token spend by deployment and model, plus Provisioned Throughput (PTU) capacity, attributed to the team and workload that drove it.
GitHub Copilot.
Seat consumption with per-user acceptance and activity, so the seats earning their keep separate from the ones to reclaim.
Microsoft 365 Copilot.
Per-seat licensing set beside usage signal, so a five-figure monthly commitment maps to the people actually using it.
The Azure depth
PTU economics multi-cloud tools skip.
Provisioned Throughput is a capacity purchase, not a per-token one. Getting it right is where most of the recoverable Azure AI spend hides, and it needs Azure-specific modeling no provider-agnostic tool carries.
PTU break-even.
PTUs bill by the hour whether traffic flows or not. CloudMonitor shows the utilization above which reserved PTUs beat pay-as-you-go, and below which they don't.
Reservation & unallocated waste.
Below-100% PTU reservation utilization and deployed-but-unused PTUs are invisible on the invoice. Both surface here as recoverable spend.
Spillover modeling.
Size provisioned capacity for average load and let peaks spill to pay-as-you-go. CloudMonitor models the split so you don't reserve for the spike.
Hybrid Benefit & MACC.
Azure Hybrid Benefit and Microsoft commitment (MACC) drawdown counted against AI workloads, so spend you've already committed gets credited where it lands.
Finance-grade by design
Reconciled to the bill, not estimated from tokens.
Observability tools estimate AI cost from token counts they log. CloudMonitor reads your actual Azure billing, normalized to FOCUS, so the AI ROI you report ties to the invoice finance will close the month on.
FOCUS as the source of truth.
Azure AI spend lands in the same FOCUS-conformed model as the rest of your estate, so AI is one row in the allocation, not a separate spreadsheet.
Cost groups and chargeback.
Role-based cost groups carry AI spend into the same showback and chargeback workflows finance already runs for cloud.
Read-only, Fabric-native.
CloudMonitor reports and recommends; your team acts. Token, capacity, and billing data blend in a Fabric workspace isolated to your tenant.
Microsoft AI in CloudMonitor
Tokens, PTUs, and seats in one allocation.
One pane
Every Microsoft AI meter, one model.
Azure OpenAI tokens and PTUs, Copilot seats, and the rest of Azure roll into the same cost analysis, so the total Microsoft AI bill is one number a team owns, not three exports to reconcile.
Recoverable spend
PTU waste and dormant seats, surfaced.
Under-used PTU reservations, unallocated capacity, and dormant Copilot seats land in the recommendation queue with the dollars attached, so the Azure AI bill gets leaner without a quality trade.
What you can prove
Microsoft AI outcomes.
3 in 1
Azure OpenAI, Copilot, M365 Copilot in one pane
PTU
Break-even and reservation waste, modeled
FOCUS
Reconciled to the actual Azure bill
Source: this page interprets the FinOps for AI technology category published by the FinOps Foundation, licensed under CC BY 4.0. The wording, examples, and product mapping on this page are CloudMonitor’s own.
See your whole Microsoft AI bill in one pane.
The beta connects Azure OpenAI, GitHub Copilot, and your AI providers on your own tenant. PTU economics and value per token in minutes.
