MSFT--Top 10 position --notes on Q4 FY25 Result

 MSFT Q4 2025 RESULT SUMMARY

The FY result exceeded both my revenue and NPAT numbers by 1%. MSFT is an unusually stable and predictable company.

The commentary was both bold and focused on the Intelligent Cloud segment with detail on the progress MSFT is making to dominate the growth and proliferation of multi-agent market across the enterprise customer base. MSFT is uniquely positioned due to existing client integrations to capture a large share of this market and appears to be very proactive in doing so. The investment requirements are large, and the integration skills and marketing are complex.

The growth in cloud/AI profitable business is encouraging the company to aggressively expand its cloud business. MSFT regards the opportunity as generational.

The other segments were covered in a cursory way.

A deeper coverage will be provided under the template as MSFT is a large top 10 position in the fund.

 

Satya Nadella CEO

All up, Microsoft Cloud surpassed $168 billion in annual revenue, up 23%.

The rate of innovation and the speed of diffusion are unlike anything we have seen. To that end, we are building the most comprehensive suite of AI products and tech stack at a massive scale. And to provide more context, I want to walk up the stack, starting with Azure.

Azure surpassed $75 billion in annual revenue, up 34%, driven by growth across all workloads. We continue to lead the AI infrastructure wave and we took share every quarter this year. We opened new DCs across 6 continents and now have over 400 data centres across 70 regions, more than any other cloud provider.

Every Azure region is now AI-first. All of our regions can now support liquid cooling, increasing the fungibility and the flexibility of our fleet. And we are driving and riding a set of compounding S curves across silicon, systems and models to continuously improve efficiency and performance for our customers.

Take, for example, GPT4o family of models, which have the highest volume of inference tokens. Through software optimizations alone, we are delivering 90% more tokens for the same GPU compared to a year ago.

This quarter, we introduced the Microsoft Sovereign Cloud, the industry's most comprehensive solution spanning both public and private cloud deployments.

The next big accelerator in the cloud will be Quantum, This is how we will continue to think and make investments, with decade-long arcs, while making progress every quarter.

The next layer is data, which is foundational to every AI application. Microsoft Fabric is becoming the complete data and analytics platform for the AI era, spanning everything from SQL to no-SQL, to analytics workloads. It continues to gain momentum with revenue up 55% year-over-year and over 25,000 customers. It's the fastest-growing database product in our history.

Fabric OneLake spans all databases and clouds, including semantic models from Power BI, and therefore, it is the best source of knowledge and grounding for AI applications and context engineering.

This year, we launched Azure AI Foundry to help customers design, customise and manage AI applications and agents at scale. Foundry features best-in-class tooling, management, observability and built-in controls for trustworthy AI. Customers increasingly want to use multiple AI models to meet their specific performance, cost and use case requirements. And with Foundry, they can provision inferencing throughput once and apply it across more models than any other hyperscaler. And when we look narrowly at just the number of tokens served by Foundry APIs, we processed over 500 trillion this year, up over 7x. This is a good indicator of true platform diffusion beyond a few head apps and services.

Talking about the app layer, these applications are becoming embedded in our daily work and life. Our family of Copilot apps has surpassed 100 million monthly active users across commercial and consumer. And when you take a broader look at the engagement of AI features across our products, we have over 800 million monthly active users.

Customers continue to adopt Copilot at a faster rate than any other new Microsoft 365 suite, with strong usage intensity as shown by our week-over-week retention. And we saw the largest quarter of seat adds since launch with a record number of customers returning to buy more seats.

We are also seeing more customers use Copilot Studio to extend Microsoft 365 Copilot and build their own agents. This year, customers created 3 million agents using SharePoint and Copilot Studio.

We have 20 million GitHub Copilot users. GitHub Copilot enterprise customers increased 75% quarter-over-quarter as companies tailor Copilot to their own codebases, and 90% of the Fortune 100 now use GitHub Copilot. More broadly, GitHub usage and repos are seeing explosive growth because of AI. AI projects on GitHub more than doubled over the last year.

Dynamics 365 took share this year. in Sales,  ERP, and Contact Center.

LinkedIn is home to 1.2 billion members with 4 consecutive years of double-digit member growth. All up, comments on LinkedIn rose over 30% and video uploads increased over 20% this year. We continue to bring AI to every part of the LinkedIn experience, introducing agents across hiring as well as sales.

When it comes to Gaming, we have 500 million monthly active users across platforms and devices. We are now the top publisher on both Xbox and PlayStation this quarter. And we have nearly 40 games in development, so much, much more to come. We surpassed over 500 million hours of gameplay stream via the cloud this year. And Game Pass annual revenue was nearly $5 billion for the first time.

Amy E. Hood CFO

This year, we delivered over $281 billion in revenue, up 15% year-over-year, which reflects the broad strength of our products and services. Operating income was over $128 billion, up 17% year-over-year as we invested against the expansive opportunity ahead.

This quarter, revenue was $76.4 billion, up 18%, and 17% in constant currency. Gross margin dollars increased 16%, and 15% in constant currency, while operating income increased 23%. And earnings per share was $3.65, an increase of 24%, and 22% in constant currency.

For the first time, commercial bookings were over $100 billion, increasing 37%, and 30% in constant currency, on a strong prior year comparable

Commercial remaining performance obligation increased to $368 billion, up 37% and 35% in constant currency. Roughly 35% will be recognized in revenue in the next 12 months, up 21% year-over-year. The remaining portion, recognized beyond the next 12 months, increased 49%. And this quarter, our annuity mix was again 98%.

Microsoft Cloud revenue was $46.7 billion, ahead of expectations, and grew 27%, and 25% in constant currency. Microsoft Cloud gross margin percentage was slightly better than expected at 68%, down 2 points year-over-year from the impact of scaling our AI infrastructure, partially offset by continued efficiency gains in Azure and M365 Commercial Cloud.

Company's gross margin percentage was 69%, down 1 point year-over-year, driven by sales mix shift to Azure and the lower Microsoft Cloud gross margin noted earlier. Operating expenses increased 6% and 5% in constant currency, and operating margins increased 2 points year-over-year to 45%. Better-than-expected revenue growth coupled with a focus on operating efficiently drove the margin expansion.

At a total company level, head count at the end of June was relatively unchanged year-over-year.

Now to our segment results. Revenue from Productivity and Business Processes was $33.1 billion and grew 16%, and 14% in constant currency, better than expected, driven by M365 Commercial products in cloud services and M365 Consumer products in cloud services. M365 Commercial Cloud revenue was ahead of expectations and increased 18%, and 16% in constant currency, with 2 points of benefit from in-period revenue recognition.

M365 Commercial Products revenue increased 9% and 7% in constant currency, ahead of expectations due higher-than-expected Office 2024 transactional purchasing. M365 Consumer cloud revenue was better than expected, increasing 20% driven by ARPU growth following the January price increase and subscriber growth of 8%.

LinkedIn revenue increased 9%, and 8% in constant currency, with growth across all businesses, though Talent Solutions continues to be impacted by weakness in the hiring market. Dynamics 365 revenue increased 23%, and 21% in constant currency, with strong execution in our core annuity sales motions leading to growth across all workloads.

Segment gross margin dollars increased 16% and 15% in constant currency, and gross margin percentage increased slightly, driven by the efficiency gains noted earlier, even as we deliver more AI features across our products and scale our AI infrastructure.

Operating expenses increased 7%, and 6% in constant currency. Operating income increased 21%, and 19% in constant currency.

Next, the Intelligent Cloud segment. Revenue was $29.9 billion and grew 26%, and 25% in constant currency, ahead of expectations, driven by Azure and our on-premises server business. In Azure and other cloud services, revenue grew 39%, significantly ahead of expectations, driven by accelerated growth in our core infrastructure business, primarily from our largest customers. As a reminder, new cloud and AI workloads are built and scaled using the breadth of our services.

Revenue from Azure AI services was generally in line with expectations. And while we brought additional data center capacity online this quarter, demand remains higher than supply.

In our on-premises server business, revenue decreased 2%, and 3% in constant currency, ahead of expectations, primarily driven by transactional purchasing which also has higher in-period revenue recognition. Enterprise and Partner Services revenue increased 7%, and 6% in constant currency, with growth in Enterprise Support Services partially offset by a decline in Industry Solutions.

Segment gross margin dollars increased 17%, and 16% in constant currency, and gross margin percentage decreased 4 points year- over-year driven by scaling our AI infrastructure, partially offset by Azure efficiency gains noted earlier. Operating expenses increased 6%, and 4% in constant currency. And operating income grew 23%.

Now to More Personal Computing. Revenue was $13.5 billion and grew 9%, exceeding expectations, primarily due to Windows OEM as well as Xbox content and services. Windows OEM and Devices revenue increased 3% year-over-year, ahead of expectations, as inventory levels remained elevated.

Search and news advertising revenue ex TAC increased 21% and 20% in constant currency, driven by continued growth in both volume and revenue per search, as well as roughly 8 points of favorable impact from third-party partnerships, including the benefit of a low prior-year comparable.

And in Gaming, revenue increased 10%. Xbox content and services revenue increased 13%, and 12% in constant currency, driven by better-than-expected performance from first-party content and Xbox Game Pass.

Segment gross margin dollars increased 15%. Gross margin percentage increased 3 points year-over-year with improvement across all businesses. Operating expenses increased 4%, and 3% in constant currency. Operating income increased 34%, and 33% in constant currency, driven by continued prioritization of higher margin opportunities.

Other income and expense was negative $1.7 billion, primarily due to losses on investments accounted for under the equity method. Our effective tax rate was approximately 17%.

 

 

OUTLOOK

Next, building on the strong momentum we saw this past year, we expect to deliver another year of double-digit revenue and operating income growth in FY '26. We will continue to invest against the expansive opportunity ahead across both capital expenditures and operating expenses given our leadership position in commercial cloud, strong demand signals for our cloud and AI offerings, and significant contracted backlog.

Capital expenditure growth, as we shared last quarter, will moderate compared to FY '25 with a greater mix of short-lived assets. Due to the timing of delivery of additional capacity in H1, including large finance lease sites, we expect growth rates in H1 will be higher than in H2.

And as a result, we expect operating margins to be relatively unchanged year-over-year. And finally, we expect our FY '26 effective tax rate to be between 19% and 20%.

Q126

For Intelligent Cloud, we expect revenue of USD 30.1 billion to USD 30.4 billion, or growth of 25% to 26%, with roughly 1 point of benefit from FX as noted earlier. Revenue will continue to be driven by Azure, which can have quarterly variability in year-on-year growth rates depending on the timing of capacity delivery and when it comes online, as well as from in-period revenue recognition depending on the mix of contracts.

In Azure, we expect Q1 revenue growth of approximately 37% in constant currency, driven by strong demand for our portfolio of services on a significant base. Even as we continue bringing more data center capacity online, we currently expect to remain capacity- constrained through the first half of our fiscal year.

Question-and-Answer Session

Customers becoming competitors?

And in some sense, that's kind of what we now have, which is the largest AI workloads run on Azure. And when that happens, you learn the workload faster, you optimize the entire platform faster, everything from what you're doing -- what we're doing with Cosmos DB for a chat interface like ChatGPT or Copilot, is, guess what, going to be the most relevant for any AI application going forward.

The entire data stack that we have now built is going to be optimized for what people describe as one of the hardest challenges of any AI application, called context engineering, right, which is how do you collect your data and then make sure that the context around the problems remain stable over a long period so that you get the intelligence to actually deliver the results you want. So these are workload results that are invaluable for us to learn to build both the products as well as the platform.

And then broadly, they -- or rather over time, there will be broad diffusion. In fact, one of the things that Amy and I track is not just the head app usage, but also what's the sort of all the Tier 2 applications that are being built.

So that sort of -- that speaks a little bit, Keith, to I think your question, is as long as we have head apps shaping the platform and then, after that, we have the broad diffusion happen, which in some sense both of those is what we are seeing. So I feel very good about our being in decent standing going forward.

What do you think is the best way that software companies are going to be able to monetize AI for SaaS? Do you believe there are differences in monetization for horizontal, more general apps like M365 Copilot or Dynamics CRM Copilot versus very targeted capacities on the agentic side?

So if you sort of even subscribe to this point of view that intelligence is basically log of compute, that means compute is going to grow and you've got to use it as efficiently as possible to just keep creating intelligence.

Now how does it manifest beyond just the infrastructure? I talked a little bit about how the infrastructure is getting shaped, data layer is getting shaped, the app server is getting built. These are all classic categories of infrastructure that will continue, but there will be an order 2 of magnitude more.

So literally, like -- in fact, one of the other things we track is every GPU requires storage and compute. That ratio is another thing that is really exponential for infrastructure growth.

So when you go to the app layer, the SaaS apps themselves are now building in effectively agentic and chat interfaces with intelligence. And they're also building autonomous agents. Agents are kind of like applications, like a database application perhaps, but they are being used increasingly inside of a user interaction. I think a good example is GitHub Copilot. It got started as code completions on an IDE. Then we added the chat interface to it. Then we added the Agent Mode to it. And now we have an autonomous agent, which in fact works completely asynchronously, So all those 4 things are now part of essentially GitHub.

And so that's exactly the same thing that's happening with Microsoft 365. That's the same thing that's happening with Dynamics 365. So you have to be very open to taking your data tier, your business logic tier and your UI tier and sort of being more expansive in it. As long as you do that, it's just that usage goes up, and that's what I think shows up in the results.

There's a per user logic, there's tiers of per user. Sometimes those tiers relate to consumption, sometimes there's pure consumption models.

I think you'll continue to see a blending of these. Especially as the AI model capability grows, you'll end up with ways that teams are going to want to throttle that usage, use the best models for the best job. And I think the blending of these models will continue to be something we see on a go-forward basis.

Driving Azure demand acceleration

Just 3 things are really happening. One is the migrations. And it turns out that we're still not anywhere close to the finish line, if at best, maybe in the middle innings of that.

The second thing that's also happening is cloud-native applications that are scaling. This is even excluding all of the AI stuff, just the classic cloud native e-commerce company, let's say. These are scaling in a big way. And some of those customers were not on Azure previously, but now they're increasingly there, because they have come for AI perhaps but they now stay for more than AI. And so to me, that's another thing you see in overall, what's happening across the Azure number.

And then, of course, there are the new AI workloads. So those are 3 things that are all, in some sense, building on each other, but that's kind of what's driving our growth.

What's driving demand in AI

Yes. I don't know, Brent, if anything really surprised us. But I think what we are noticing in our own build-out of these AI applications and in general is the platform is becoming more than, "Here is the model and here is an API. Make some calls," right? I mean that, in some sense, was a bit of the state-of-the-art maybe even a year ago.

Whereas now you have essentially these very stateful app patterns that are emerging that require quite a bit of rethinking of even the app stack. I mean take even the storage tier stuff, right, the degree of sophistication you have, and hey, how much of an index do you really want to build by preprocessing so that your prompt engineering, or context engineering as I call it, can be better and higher quality?

So I think all of that is emerging. So when I look at a product like Azure Search, Fabric and Cosmos DB, all of the things, the frameworks around it, are just becoming robust to build serious applications.

And so that's what I feel great about, is the learning curve inside the company, outside the company, the diffusion of the stack, the speed with which that's emerging, that you can build applications, is much faster.

I always go back and say when relational database came out, it took a while for people to build an ERP system, let's say. And this thing, we're kind of building pretty sophisticated applications at a very, very fast clip based on, I think, the degree of maturity that's emerging.

Expanding use cases

So yes, there is a lot more of it's just not request, respond. It's about spawning essentially applications that then go do work and come back.

But the UI still remains very important, even for asynchronous work. To instruct the asynchronous work, you need UI. And to monitor asynchronous work, you need UI. Maybe different, it may not be a chat interface. And of course, you need a way to then inspect what the asynchronous work is

So even take the example I was giving on GitHub. Even if you're not using GitHub Copilot to create the core check-in or the pull request, interestingly enough, we're seeing massive increase to GitHub Copilot Code Review Agent even if you used maybe Claude Code or whatever else to write the code.

So that's I think what's happening across all of these systems. So you're absolutely right that you need -- it starts with some kind of a UI that's more chat focused, but it quickly goes beyond it. And you see it in M365, you see it in Dynamics 365 and you see it in GitHub.

Capex and returns profile

when you think about the full year comments I've made on CapEx as well as the Q1 guidance of over $30 billion, you first have to ground yourself in the fact that we have $368 billion of contracted backlog we need to deliver, not just across Azure but across the breadth of the Microsoft Cloud.

So in terms of feeling good about the ROI and the growth rates and the correlation, I feel very good that the spend that we're making is correlated to basically contracted on the books business that we need to deliver and we need the teams to execute at their very best to get the capacity in place as quickly and effectively as they can.

And I talked about in January and said I thought we'd be in better supply demand shape by June. And now I'm saying I hope I'm in better shape by December. And that's not because we slowed CapEx. Even with accelerating the spend and trying to pull leases in and get CPUs and GPUs in the system as quickly as we can, we are still seeing demand improve.

And so I am not as focused on trying to pick a date at which revenue growth and CapEx growth will meet and cross. I'm focused on building backlog, building business and delivering capacity, which we are seeing has a good ROI today in terms of our ability to get that done.

 which is that the difference between a hoster and a hyperscaler is software. And the same is going to be true here. That GPT4o example I gave is all software, right, the optimization even in the last year.

So we know how to use the software skills to take any piece of hardware and make it multiple x better. And so that's kind of where the yield will come. But while you're really going and building out the plant, you don't want to sort of serialize it. You just want to go in and paddle on all of these fronts, and that's sort of what will compound over time.

And so I would remind people, that is something that we saw through the prior cloud transition, it's how we operated through that one. And the same sort of skills and logic done at an even faster pace is what will apply the same transition.

Managing margins

I think really the area to focus on is, when you think about margin, I think sometimes people get a lot of energy around cost control as a driver of margin. The other driver is to focus on making sure you deliver a great product that's competitive and innovative and can take share, because that drives revenue. And revenue itself, and revenue growth as you all know better, even perhaps than I do, is a durable way to see margin improvement. It builds on itself.

That being said, the second thing is applying all of our skill set here to deliver efficiencies, whether that's at whatever layer of the stack that exists, the S curves compound, and we are doing that work, and we're focused on it at the same time we're doing the build out. So you'll see improvements there even as we continue to invest.

And then, of course, it's about continuing to have great talent here focused on products and opportunities where we have the biggest markets and the most likelihood of success. And so when we have those 3 things happen and the energy is right and the focus is there, it gives me confidence in terms of margin delivery.

But make no mistake, it starts and ends really with product, which is what we're really focused on here, and delivering that to customers.