Summary
Microsoft doesn’t bill all its AI products the same way. Some are traditional per-user licences that appear on your Enterprise Agreement, while others are consumption meters billed through Azure. Several products offer both options, which is what makes budgeting complicated.
The split creates a practical problem: licensing and Azure consumption typically sit in different budgets, require different approval processes, and land on different desks. If you’re forecasting Microsoft AI costs for next year, you need to know which products appear where.
Key takeaways
Per-user AI products (M365 Copilot, GitHub Copilot, Teams Premium) are billed through your licensing agreement and are predictable. Per-action and per-compute products (Copilot Credits, Security Compute Units, Azure OpenAI tokens) are billed through Azure and scale with usage.
A single AI interaction can trigger costs across both billing systems, making forecasting harder than it looks.
There is no unified dashboard for Microsoft AI consumption. You need to monitor multiple portals and reconcile manually.
Capacity packs, the Pre-Purchase Plan (P3), and MACC commitments offer savings but require you to forecast consumption before you have real usage data.
The Two Billing Worlds
Microsoft has two distinct billing mechanisms for AI products:
Licensing (Enterprise Agreement/Cloud Solution Provider/Microsoft Customer Agreement) | Azure Consumption |
|---|---|
With traditional subscriptions, you commit to a quantity of licences, pay monthly or annually, and the cost is predictable. Procurement teams have managed subscriptions for decades, and the costs appear on your Microsoft agreement rather than your Azure bill. Microsoft 365 Copilot and Teams Premium fall squarely into this category. GitHub Copilot’s per-seat subscription does too, though from June 2026 it also has a variable token-based component. | Pay-for-what-you-use meters work differently. Costs scale with activity rather than headcount, and billing happens through Azure subscriptions that are often managed by IT or cloud operations rather than procurement. The costs are inherently variable, which makes forecasting harder. Examples include Azure OpenAI (billed per token), Copilot Credits (billed per credit), and Security Compute Units (billed per hour). |
The budgeting problem
When your CFO asks “what will Microsoft AI cost next year?”, the honest answer is that it depends on which products, and you’ll need two different numbers.
The licensing portion you can forecast with reasonable confidence. The Azure portion depends on how much your organisation actually uses the tools, and that’s harder to predict, especially in year one.
Which Products, Which Bill
Product | Billing Model | Where It Appears | Predictable? |
|---|---|---|---|
Microsoft 365 Copilot | Per-user licence ($30 Enterprise, $18 Business with current promo, list $21) | Licensing agreement | ✅ Yes |
Microsoft 365 Copilot Business | Per-user licence ($18 with current promo, list $21) | Licensing agreement | ✅ Yes |
GitHub Copilot (subscription) | Per-user licence ($0–39) | Licensing agreement | ✅ Yes |
GitHub Copilot (token overage) | AI Credits ($0.01 each, from June 2026) | GitHub billing | ❌ No |
Teams Premium | Per-user licence ($10) | Licensing agreement | ✅ Yes |
Security Copilot (standalone) | Security Compute Units (SCUs, $4–6/hour) | Azure | ❌ No |
Security Copilot (E5 inclusion) | Included SCUs (400 per 1,000 users, 10,000 cap) | Neither (included) | ✅ Yes (capped) |
Copilot Studio (pay-as-you-go/PAYG) | Copilot Credits ($0.01 each) | Azure | ❌ No |
Copilot Studio (capacity packs) | Subscription ($200/month) | Licensing agreement | ✅ Yes |
Autonomous agents | Copilot Credits (5 per action) | Azure | ❌ No |
Azure OpenAI | Per token | Azure | ❌ No |
Dataverse (add-ons) | Per GB/month | Licensing agreement | ✅ Yes |
Dataverse (PAYG) | Per GB/month | Azure | ❌ No |
The pattern:
The general rule is that per-user products are billed through licensing, while per-action or per-compute products are billed through Azure. Some products offer both options, and those hybrid products are the tricky ones. Security Copilot can be standalone (billed through Azure) or included with E5 (no separate charge). Copilot Studio can be capacity packs (licensing) or PAYG (Azure). From June 2026, GitHub Copilot joins this hybrid category. The per-seat subscription is predictable, but token consumption beyond the included AI Credit allowance creates variable costs on top. You might have both models in the same organisation, which means you’re tracking costs in two places.
When Costs Stack
A single AI interaction can trigger costs across multiple billing systems, which makes forecasting difficult.
Example 1: M365 Copilot user builds an autonomous agent
A knowledge worker has an M365 Copilot licence. They use Copilot Studio to build an agent that monitors a shared mailbox and processes incoming requests automatically.
Component | Cost | Bill |
|---|---|---|
M365 Copilot licence | $30/month | Licensing |
Autonomous trigger (per email) | 5 credits = $0.05 | Azure |
Generative answer | 2 credits = $0.02 | Azure |
Two actions (read, respond) | 10 credits = $0.10 | Azure |
The licence is fixed at $30/month. But if the mailbox receives 500 emails per month, the agent consumes 8,500 credits ($85/month) on top of that. The $30 appears on your EA; the $85 appears on your Azure bill.
Example 2: Copilot Studio capacity packs with overage
You’ve bought 3 capacity packs ($600/month) expecting 75,000 credits of usage. A busy month pushes consumption to 90,000 credits.
Component | Cost | Bill |
|---|---|---|
3 capacity packs | $600/month | Licensing |
15,000 overage credits | $150 | Azure |
Total | $750 | Split |
The capacity packs are on your licensing agreement. The overage is PAYG through Azure. Two different budget lines for the same product.
Example 3: M365 Copilot user’s agent serves unlicensed colleagues
An M365 Copilot user builds an HR policy agent and shares it with the whole company. The builder has a licence, but most employees don’t.
Component | Cost | Bill |
|---|---|---|
M365 Copilot licence (builder) | $30/month | Licensing |
Agent usage by builder | Included | – |
Agent usage by 200 unlicensed users (10 queries each) | 4,000 credits = $40/month | Azure |
The builder’s usage is covered by their licence. Everyone else generates PAYG consumption.
Example 4: Security analyst with both Copilots
A security analyst on M365 E5 uses both M365 Copilot and Security Copilot.
Component | Cost | Bill |
|---|---|---|
M365 Copilot licence | $30/month | Licensing |
Security Copilot SCUs (included with E5) | Up to 400 SCUs per 1,000 users | – |
Security Copilot SCUs (if exceeding allocation) | PAYG overage at $6/SCU (coming at a future date) | Azure |
If they stay within the E5 allocation, Security Copilot costs nothing extra. Microsoft has stated that usage beyond the allocation will be throttled at a future date, with an option to scale at $6/SCU on a PAYG basis at that time. The M365 Copilot licence is always on the EA.
Example 5: Power Automate flow triggers Copilot Studio agent
A Power Automate Premium user builds a flow that calls a Copilot Studio agent for document processing.
Component | Cost | Bill |
|---|---|---|
Power Automate Premium licence | $15/month | Licensing |
Copilot Studio agent (per invocation) | Variable | Azure |
Content processing (per page) | 8 credits = $0.08 | Azure |
The flow licence is fixed. The agent consumption scales with how many documents get processed.
In every case, the licence fee is only part of the story. The consumption-driven portion depends on what people do with the tools, and it flows through a different billing system entirely.
The Visibility Gap
But there’s a practical problem. No single dashboard shows all your Microsoft AI consumption.
M365 Copilot usage appears in the Microsoft 365 admin centre
Copilot Credits appear in the Power Platform admin centre
Security Copilot SCUs have their own usage dashboard
Azure OpenAI consumption appears in Azure Cost Management
Dataverse capacity appears in Power Platform admin centre
As Jukka Niiranen, a Power Platform licensing specialist, observed: partners working on customer analytics “need to combine multiple data sources just to see what their organisation has consumed today”.
What the visibility gap means for budgeting
The practical consequence is that you can’t pull a single report showing total AI spend. Different consumption types require different monitoring tools, and autonomous agents compound the problem because they generate consumption without any user activity to track. Month-end reconciliation requires manual effort across multiple portals, and until Microsoft provides better tooling, there’s no way around it.
What you can do
In the meantime, set up spending alerts in both Power Platform admin centre and Azure Cost Management. Designate someone in your organisation to own cross-product visibility, and have them review consumption weekly rather than waiting until month-end. You’ll need to build a manual consolidation process, at least until Microsoft provides something better.
How to Budget
Given the split billing model, here’s how to approach forecasting:
For licensing-based products
Licensing-based products are straightforward to forecast. You count users, multiply by the price, and apply any negotiated discounts.
Product | Forecast Method |
|---|---|
M365 Copilot | Users × $30 (or $18 for Business with current promo) × 12 months |
GitHub Copilot (subscription) | Developers × plan price × 12 months |
Teams Premium | Meeting-heavy users × $10 × 12 months |
Build in a buffer for mid-year expansion, but the base cost is predictable. Note that from June 2026, GitHub Copilot token overage beyond the included AI Credit allowance is variable and should be forecast separately (see consumption-based products below).
For consumption-based products
Consumption-based products require usage estimation, which is inherently uncertain until you have real data from your own environment.
The best approach is to start with pilots. Run a small deployment for two to three months, measure actual consumption, and then extrapolate with a safety margin built in.
As you plan, identify the cost drivers that will affect your consumption. Consider how many agents will run, how often autonomous triggers will fire, what interaction volume you expect, and which AI tools your agents will invoke.
You should also set spending limits from the start. Both Power Platform admin centre and Azure allow you to configure budgets and alerts, and you should use them before consumption surprises you.
Capacity packs vs PAYG
If your Copilot Studio usage is predictable, capacity packs ($200/month for 25,000 credits) save 20% versus PAYG ($0.01/credit), though unused credits expire at the end of each month.
Our recommendation is to start with PAYG to establish baseline usage, then shift to capacity packs once you understand consumption patterns.
Pre-Purchase Plan (P3)
For high-volume or variable usage, the Copilot Credit Pre-Purchase Plan offers a one-year upfront commitment with tiered discounts ranging from 5% to 20% depending on volume. Unlike capacity packs, P3 credits expire annually rather than monthly, which gives you more flexibility. P3 is also Microsoft Azure Consumption Commitment (MACC)-eligible, meaning the credits count toward your Azure spend commitment.
P3 makes sense if you’re spending $3,000+/year on Copilot Credits and can forecast with reasonable accuracy. Below that threshold, PAYG is simpler.
MACC interactions
If you have a Microsoft Azure Consumption Commitment, P3 credits count toward it, which can help you hit MACC targets while getting discounted AI capacity.
But be careful, because MACC commitments create pressure to spend. Don’t buy P3 credits you won’t use just to satisfy a commitment.
Questions for Your Next Renewal
When you’re negotiating a Microsoft agreement that includes AI products, these questions will surface the information you need:
Scope | Which AI products are we buying through licensing, and which will be billed through Azure? Do we have Azure subscriptions in place for the consumption-based products? Who owns the Azure budget for AI consumption? Is it the same team managing licensing? |
Forecasting | What’s our expected user count for per-user products (M365 Copilot, GitHub Copilot, Teams Premium)? For GitHub Copilot: what’s our expected AI Credit consumption beyond the included allowance, and have we reviewed the usage report? For Copilot Studio: are we building agents? Will any run autonomously? What’s the expected trigger volume? For Security Copilot: are we on E5 (included SCUs) or standalone (Azure consumption)? |
Cost control | Have we set up spending alerts in Power Platform admin centre and Azure Cost Management? Who will monitor AI consumption across portals? What’s our escalation path if consumption exceeds forecast? |
Commercial | What discounts are available on M365 Copilot? (Don’t accept list price without asking.) Should we buy Copilot Studio capacity packs or start with PAYG? If we’re spending $50,000+/year on Copilot Credits, should we evaluate P3? Does our MACC commitment affect how we should structure AI purchases? |
Governance | Who can create agents that consume Copilot Credits? Do we have approval workflows before agents are published? How will we prevent autonomous agents from generating unexpected charges? |
Need Help?
The split billing model for Microsoft AI creates complexity that traditional licensing expertise doesn’t fully address. If you’re trying to forecast costs, negotiate a Microsoft agreement, or make sense of how licensing and Azure consumption interact, get in touch.
We don’t sell Microsoft licences, so our advice is unbiased. We help you understand what you’re actually paying for.
