AI FinOps

Gain better control over your AI costs with our FinOps approach | Arxus

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From Copilot to Cowork: rethinking your Microsoft 365 cost strategy using FinOps

AI is evolving rapidly in the modern workplace. What started as simple productivity gains with Microsoft 365 Copilot is now shifting toward AI agents like Cowork that can execute work across your entire environment. With that shift, cost becomes part of the conversation. You still pay per user, but with usage-based credits on top, your spend now depends on how AI is actually used. Many organizations are already seeing changes in their Microsoft bill without fully understanding why. To stay in control, you need a new approach: one that connects adoption with cost and usage. That’s where FinOps for AI comes in.

Mon, 27 July 2026

Kevin Meuldermans

Data & AI Engineer

What is Copilot Cowork? And why does it matter?

Copilot Cowork takes AI in the modern workplace a step further. While traditional Copilot helps you draft, summarize, or analyze, Cowork is built to execute work on your behalf. Instead of working prompt by prompt, you define an outcome. Cowork then plans the steps, gathers context across your Microsoft 365 environment, and executes tasks across multiple apps.

This is the key shift: you move from AI as an assistant to AI as a teammate. Cowork doesn’t just suggest what to do, it actually gets the work done.

And it doesn’t stop there. With Scout, Microsoft is taking this evolution one step further. Where Cowork executes tasks you define, Scout acts more proactively, surfacing insights, identifying opportunities, and bringing relevant information forward before you even ask. Together, Cowork and Scout shape a new model where AI doesn’t just respond, it anticipates, acts, and collaborates.

That’s what makes it valuable. It enables more automation, reduces manual effort, and helps teams focus on higher-value work. But it also introduces a new reality: the more work you delegate, the more consumption and cost you generate.

AI is no longer a separate silo

AI used to sit neatly inside Microsoft 365. It felt like an extension of familiar tools, easy to adopt and easy to budget. That’s no longer the case. With Cowork, Copilot agents, and Azure integration, AI now spans your entire environment: it connects data, tools, and systems, turning simple prompts into multi-step workflows.

This means AI is no longer just about improving productivity. It’s a cross-platform capability that directly impacts both your architecture and your costs.

INSIGHT

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AI agents in Microsoft Copilot: what does this mean for your productivity?

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Your Microsoft 365 invoice is evolving

For years, Microsoft 365 followed a simple rule: you paid per user, and your cost was predictable. That made budgeting straightforward and relatively risk-free. With the introduction of Copilot Cowork, that changes. You still pay for the Copilot seat, but on top of that, the actual work performed by AI is now metered using credits. Every task is priced based on how it is executed − depending on factors like the model used, how much data is involved, how many tools are triggered, and how long the process runs.

This means that the same feature can have very different costs depending on how it is used. What used to be a fixed monthly line item is now a combination of license cost and consumption-based cost.

What are you paying for exactly?

At first glance, the per credit cost may seem small. In practice, this is where many organizations underestimate the real impact. Credits are consumed continuously as users interact with Cowork agents. And unlike a flat license, the cost of every interaction depends on how the agent works, not just how often it is used.

Microsoft defines four key components that drive credit consumption: the AI model, contextual data, tool calls and the runtime. These four elements combine to determine the cost of every Cowork interaction. The more powerful the request, the more credits it consumes. The takeaway here: With Cowork, cost is no longer driven by user count, but by complexity and behavior. That’s exactly why organizations need a structured FinOps approach from day one.

The AI model powering the task

What drives up the costs?

Heavier models (Opus > Sonnet > lighter)
More tokens
Deeper reasoning
Multiple outputs

Contextual data from your environment

What drives up the costs?

When the model searches multiple sources in your Microsoft 365 environment, such as:

Emails and chats
Calendars
Meetings
Files
Business systems

The type of tasks the agent performs

What drives up the costs?

Creating documents
Sending emails
Posting in Teams
Managing calendars

The duration of the task

What drives up the costs?

Long-running, multi-step tasks that keep working even when your device is off.

Why will this increase your costs?

AI adoption will make your bill skyrocket. Why? It’s pretty simple. Users are no longer just asking simple questions. They are triggering workflows, aggregating data, and using AI to perform more complex tasks. Those actions require more compute and therefore consume more credits.

There’s no way around it, but that’s not necessarily a problem. The important shift is that cost is now linked to value. The more powerful the use case, the higher the consumption. The challenge is making sure that this consumption delivers real business impact.

The right partner makes the difference

Managing this new AI cost model requires more than just licensing knowledge. It brings together Microsoft 365, Azure, cost management, and user adoption into one interconnected challenge. Most organizations don’t have that full picture internally, which makes it difficult to stay in control as AI usage grows. This is where the right partner becomes essential. Not just to provide technology, but to help you navigate the complexity, make informed decisions, and scale AI in a controlled and sustainable way.

At Arxus, we take a FinOps-driven approach that combines both Microsoft 365 and Azure. We help you understand how AI is used across your organization, where credits are consumed, and how to optimize both your spend and your commitments. At the same time, we focus on adoption. Because the goal is not to reduce usage, but to make sure every interaction delivers real business value. That’s how you turn AI from a growing cost into a true business accelerator.

Our experts help you gain more control over your AI spending | Arxus

Take control over your AI consumption today

If you want to understand what this means for your organization, the next step is simple: get insight into your usage and build a realistic cost model. We’re here to help.

Contact our experts to gain a better insight in your AI costs | Arxus

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