The model is part of the product

Microsoft has started using its own AI models for some requests in Excel and Outlook. According to Bloomberg, its MAI models are now handling tens of thousands of prompts each week that previously would have relied more heavily on models from OpenAI or Anthropic.

The new models still handle a small fraction of total requests, and Microsoft has not announced that it is removing Claude or OpenAI models from Microsoft 365 Copilot. This is an incremental shift in how Microsoft runs the service, not evidence that the model picker is about to disappear.

Still, I think enterprise customers should pay attention.

Microsoft has been explicit about wanting to reduce what it spends on third-party models. That is a rational business goal. Anthropic and OpenAI charge for inference, Microsoft operates Copilot at a scale few companies can match, and every prompt carries a cost. If Microsoft’s own models can handle a task well enough for less money, routing some work to them makes sense.

The customer problem begins when “well enough” is decided entirely by the vendor, the substitution is difficult to see, and the subscription price stays the same.

Why model choice matters

It is tempting to treat models as interchangeable infrastructure. Most people do not care which database answers a query or which server processes an email. Why should they care which language model writes a paragraph or analyzes a spreadsheet?

Because the differences are still visible in the work.

Models vary in reasoning, writing, instruction-following, coding, tool use, and how they handle long or ambiguous tasks. A cheaper model may be perfectly adequate for summarizing a routine email. The same substitution can become obvious when the task is reconciling a complicated spreadsheet, editing a sensitive document, or following a long set of constraints without wandering off halfway through.

I see this in my own evaluations. Access to Claude inside Microsoft 365, especially in Excel, is one of the strongest reasons I can give someone to pay for the upgraded Copilot license. It puts a capable model inside the tool where the work already lives, with Microsoft’s identity, administration, and enterprise protections around it. That combination is useful.

Microsoft has promoted that choice too. When it announced Anthropic support in Microsoft 365 Copilot, it described the move as giving customers the flexibility to use different models and choose the right tool without jumping between platforms. That was not a minor implementation detail. It was part of the value proposition.

If customers subscribe partly because that choice exists, replacing it with an opaque routing decision changes the product even if the name and monthly price remain untouched.

The uncomfortable economics of flat-rate AI

I don’t expect Microsoft, or any other company, to provide unlimited access to the most expensive models forever at a fixed monthly price.

The economics are ugly. Traditional software subscriptions work because the marginal cost of one more active user is usually small. AI subscriptions are different. Every request consumes compute, and a complicated agent can make many model calls before it produces one visible answer. The heaviest users can consume far more than their subscription fee.

Vendors have a limited set of responses. They can raise prices, impose usage caps, move customers to metered billing, route more work to cheaper models, or subsidize the difference and hope inference costs fall quickly enough to rescue the spreadsheet.

Most are experimenting with several of those options at once.

OpenAI tried to simplify ChatGPT by making GPT-5 a unified system with a router that decided when a request needed deeper reasoning. At launch, it also removed access to several older models. Paid users objected, in part because they had learned which models worked best for different tasks. OpenAI restored the model picker and legacy model access within days.

Cursor changed its $20 Pro plan from a request allowance to $20 of frontier-model usage at API prices. Unlimited use remained available through Auto, where Cursor chooses the model. The company later apologized for communicating the change poorly, acknowledged that it had surprised customers, and offered refunds for unexpected charges.

GitHub Copilot is taking the metering route. Starting in June 2026, premium requests are being replaced with GitHub AI Credits, calculated from token use and each model’s published API price. This is more transparent than invisible substitution, but it also makes clear that access to expensive models is becoming a metered resource rather than a simple benefit of having a seat.

Anthropic is wrestling with the same problem from the other side. In April, it tested removing Claude Code from the $20 Pro plan for about two percent of new subscribers. Anthropic reversed the public-facing change after users noticed, but its head of growth acknowledged that the plans were created before long-running agents became an everyday use case. Those subscriptions were not designed for current usage patterns.

None of these companies is uniquely villainous. They are discovering that flat-rate subscriptions and variable inference costs make uncomfortable roommates.

But the pattern matters. The market is moving from “pay for access to these models” toward “pay for an AI service that decides how much intelligence each task receives.” That may be a workable product. It is not the same product.

Where Microsoft deserves some room

Microsoft has legitimate reasons to build and use its own models beyond saving money.

Owning more of the model stack can reduce dependency on suppliers that are also competitors. It can improve capacity planning. Smaller models can respond faster and use less energy. A model trained for a narrow Office task may outperform a larger general-purpose model on that specific task. Data residency and contractual requirements can also affect which provider is appropriate for a customer or region.

And bigger is not automatically better. I routinely use less expensive models for straightforward work and save the strongest ones for architecture, difficult analysis, and tasks where mistakes are costly. Deepseek V4.1 Flash, in particular, is roughly Sonnet-level for most of my agentic workflow. At an order of magnitude less price. Sensible routing can give users faster answers while preserving expensive capacity for the work that needs it.

I would welcome that kind of routing inside Copilot if customers could inspect it and override it.

The concern is not that Microsoft uses Microsoft models. What worries me is that model substitution could become an invisible way to reduce the cost of serving a paid customer without giving that customer a way to tell whether quality changed.

That concern is sharper because Copilot is sold as more than a chat box. Organizations make adoption plans around it. They train people. They review data protections, remediate oversharing, assign licenses, and decide which other tools they no longer need. The cost of a quiet model change is not limited to one disappointing answer. It can affect the case an organization made for the product in the first place.

What enterprise buyers should ask for

The answer is not a contractual promise that one named model will remain available forever. Models improve, providers retire old versions, and a frozen model catalog would become its own problem.

Enterprise customers need a clearer operating agreement around change.

Vendors should identify which model handled a request, especially when automatic routing is enabled. Customers should be able to choose a specific model for work where provenance or capability matters. Material changes to model access, routing behavior, or included usage should come with advance notice. If a premium model becomes a metered add-on, the pricing should be visible before someone builds a workflow around it.

Organizations also need to stop evaluating AI products as if the interface were the product. Procurement and governance reviews should ask:

• Which models are available today, and which are guaranteed by the agreement?
• When can the vendor substitute another model without notice?
• Can users or administrators require a specific model for a workflow?
• Is the model that processed a request visible in logs or usage reports?
• What happens to price and functionality when a third-party model becomes more expensive or unavailable?
• How will the vendor communicate a material change?

Those questions are not anti-Microsoft. They are what responsible customers should ask any AI vendor, including Anthropic, OpenAI, Google, Cursor, and the dozens of products packaging those models behind their own interface.

Partnership should allow an honest question

Microsoft is an important partner to my institution. I want its AI products to improve, and I want the partnership to work. I also think good partnerships have room for customers to say when a product decision could undermine trust.

Microsoft may build a model that matches or exceeds Claude for the work people do in Office. If it does, the case for using it will be easy to make. Show customers the results, expose the model choice, explain the economics, and let organizations decide how much control they need.

What would bother me is paying the same premium price for a product sold partly on access to advanced third-party models, then discovering that the expensive model had become an occasional upgrade behind a cheaper default. The invoice would say nothing changed. The product would say otherwise.

AI companies need sustainable economics. Customers need predictable value. The companies that handle this well will not be the ones that avoid changing their products. They will be the ones that make those changes visible, explain the tradeoffs, and give paying customers a meaningful choice.