One of the most common questions we hear is "how can I charge back the cost of AI workloads to the business units responsible for their consumption?"

As your organization scales and your AI usage becomes more distributed, departmental chargeback becomes increasingly important for maintaining clear cost ownership and financial accountability. It gives each business unit visibility into the costs it incurs, supports more accurate budgeting, and helps the organization manage growing AI spend without relying on a single centralized budget.

In this post, we’ll cover: 

• What is chargeback?

• How is chargeback built-in to Agent 365 cost management in Microsoft 365 admin center?

• How will custom chargeback scenarios be supported?

What is chargeback?

Chargeback is not a new concept. Organizations have long used it to assign shared technology costs to the business units responsible for their consumption. But it is becoming more important as AI shifts from fixed per-user licenses to usage-based billing.

Chargeback brings that same discipline to AI by assigning costs to the business units responsible for their AI usage, rather than leaving them in one central budget. As your organization become more mature in its AI adoption, they increasingly want this level of accountability—so each business unit owns the cost of its AI usage and becomes responsible for the value it generates.

For example, IT builds an AI agent that helps the Sales Development team research prospects, personalize outreach, and write follow-up messages. IT tracks how much the team uses the agent and charges those costs to the sales department each month, instead of covering them through a central IT budget. This helps sales understand what it is spending and compare that cost with results such as qualified opportunities and pipeline generated.

How is chargeback built-in to cost management?

Agent 365 cost management in the Microsoft 365 admin center gives IT admins a one-stop shop to manage usage-based billed AI services. It’s already included in your existing Microsoft cloud subscriptions (i.e., it does not require separate Agent 365 or ME7 licensing to manage your Microsoft services). As we shared in our previous FinOps for AI post, cost management brings together the visibility and controls you need to understand usage, manage spend, and make more informed decisions as AI adoption grows.

Spending policies are at the center of the experience. They let admins decide who can use supported AI services, set enforced spending limits, and receive alerts as usage approaches those limits. This helps you give teams room to use AI while keeping variable costs within clear guardrails.

Departmental chargeback in cost management is built into the experience, and it is structured on Azure subscriptions and resource groups. We designed it this way because many organizations already align on an Azure subscription to each department, giving that department a clear boundary for managing and tracking its own costs. If a separate subscription for every department does not fit your setup, each department can instead use its own resource group within a shared subscription. Either approach lets AI usage follow the same financial structure as the rest of your cloud spend, so costs are assigned to the right team and fit into existing reporting and finance processes. Because usage is tied to the right subscription or resource group from the start, you can avoid the manual work of calculating each department’s bill and charging them at the end of the month.

This gives you a practical way to introduce chargeback without adding another layer of manual tracking or reconciliation. For more details on organizing along Azure subscriptions and resource groups, check out this link for more details: Resource organization design area overview - Cloud Adoption Framework | Microsoft Learn.

Configuring this in cost management is simple. When selecting the billing method for the spending policy, you can select the Azure subscription and resource group that should receive the charges, along with the region where billing-related tenant and usage data will be stored. This connects the department’s AI usage to the right Azure billing structure from the start. Built-in departmental chargeback is available for spending policies billed via pay-as-you-go and pre-purchase plans.

You can also view this spend directly in the Azure Portal. Open the subscription connected to the spending policy, go to cost analysis, and filter the meter category to Microsoft Copilot Studio. From there, add a tag filter for policyname or servicename—for example, Cowork—to narrow the view and understand spend trends over time. (Note: Although the meter category currently appears as Microsoft Copilot Studio, it reflects all Copilot Credits usage; we are working to update the name so it better represents the services covered.)

How will custom chargeback scenarios be supported?

Built-in departmental chargeback works well when your organization already uses Azure subscriptions or resource groups to separate costs. But not every chargeback model follows that structure. And some organizations have established FinOps, reporting, or finance processes that require data to flow into their own systems.

The Microsoft 365 Copilot Cost Management APIs in Microsoft Graph are available through the Microsoft Graph beta endpoint, giving you a programmatic way to manage cost controls at scale. With these APIs, you can view credit balances at the user, service, and tenant levels; create, read, update, and delete spending policies; manage the groups each policy applies to; configure service settings; and set limits and alerts.

For example, you could use a single POST request to create a spending policy for a pilot group with a clear monthly cap and a per-user limit. In the same request, you can choose the billing method and enable the services the policy should cover—such as Cowork and Work IQ—so the right users, budget guardrails, and service access are configured together. You can get started today by reviewing the documentation available on Microsoft Learn.

POST https://graph.microsoft.com/beta/copilot/costManagement/spendingPolicies
Content-Type: application/json

{
  "@odata.type": "#microsoft.graph.selectedGroupsSpendingPolicy",
  "displayName": "Pilot teams monthly cap",
  "periodLimit": { "@odata.type": "#microsoft.graph.limitedCostManagementQuantity", "value": 10000, "unit": "copilotCredit" },
  "perUserLimit": { "@odata.type": "#microsoft.graph.limitedCostManagementQuantity", "value": 500, "unit": "copilotCredit" },
  "billingMethods": "prepaidCredits",
  "serviceSettings": [
    { "serviceId": "cowork", "state": "enabled" },
    { "serviceId": "workIQ", "state": "enabled" }
  ]
}@

We are building on this foundation to give you more flexibility in your custom chargeback processes. To support that flexibility, we are developing a data pipeline for detailed AI cost and usage data that you can bring into your business intelligence tools, data lakes, or chargeback systems of choice. From there, you can apply your own allocation rules, combine AI spend with other technology costs, and support the reporting and financial processes that already work for your business. We plan to share more updates next month.

As AI becomes a bigger part of how work gets done, you need a practical way to understand who is using it, manage what they spend, and connect that investment to business value. Whether you use built-in departmental chargeback or extend it with Microsoft Graph and custom reporting, you have a flexible foundation that can grow with your organization.