Microsoft Corporation (MSFT) Earnings Call Transcript & Summary

Excellent. Thank you, everyone, for joining. I'm Keith Weiss, I run the software equity research franchise in the U.S. here at Morgan Stanley. And really thrilled to have with us from Microsoft, Satya Nadella, Chairman and CEO. Satya, thanks so much for joining us.

Thank you so much. It's thrilled to be here.

Excellent. So it's really an amazing time to be talking to you about what's going on in software, partly because of how much innovation is going on in software right now, partly because of how much uncertainty there is in this room amongst investors, and we're seeing it in the stock market. And I'd say over the past several weeks, we've seen even renewed pressure, even more uncertainty about real fundamental questions on how software is going to be built, how it's going to be delivered, how it's going to be priced on a go-forward basis. So maybe we could start there and get your perspective. What's your view on how software is fundamentally going to change over the next 3 years, over the next 5 years?

Yes. I mean it's fascinating, right? Here we are in 2026. And you sit around and you say, God, there are start-ups that are getting founded and funded in massive amounts. If you're an Excel plug-in, you are a VS Code fork, people are in love with file systems again. I mean yesterday, there was a tweet which I loved, which is somebody said, oh, instead of just using grep, I can even do an index now. And I mean like this is mind-blowing in the sense that something is happening where we are rediscovering some of the oldest things we had, like CLIs and IDEs and Excel plug-ins. So it's a good question. Like what has changed? I think to me, I go back to what is this AI thing all about, right? It's a pretty powerful capability we now have to essentially predict trajectories, right? That's what AI does. AI sort of takes what is, call it, knowledge work or a consumer sort of task, right? It could be a shopping task or a research task or I'm trying to create a sophisticated Excel model or I'm trying to do a forecast. Those are just basically knowledge work, their trajectories and AI is just great at predicting them. So a couple of things are happening as you put these models as they get better and better into our work and into our workflow. The first thing that's happening is the velocity is going up. If you think about -- there's all the stats, right, which is Dario, I think, was here last night, and he talked about sort of what's happening in coding. And you see that even what he's seeing in -- with Claude, we see it in GitHub in the sense the repos are sort of skyrocketing, right, where the public repos have what, 4%, 5% are all basically generated by these coding agents. And the same equivalent is happening in office. I mean it's crazy. I mean our SharePoint, OneDrive, I mean, the artifact creation has become the thing that everybody does. And because it's cheaper, it's so much easier to create sophisticated. And it's not just bad artifacts. These are sophisticated artifacts that are getting created as part of a trajectory, as part of a task, as part of a workflow. And so in fact, last night, I was playing with this where I wanted to track all start-ups and said this is funding in start-ups. So I put up -- we have tasks now in Copilot that's in research preview. Think of it as our coworker. And it created this fantastic spreadsheet, right? It went off, did a bunch of work. And the spreadsheet -- the problem -- so what it did is it generated an unbelievable spreadsheet at the end of a long-running sort of horizon task. Then it was great because I handed my cognitive load to it, but then it transferred it all the way back to me by creating an artifact and said, now go, here is the output, go make sense of it. So this back and forth between human and AI is going to be the next thing, which is AI is going to be great at doing cognitive work because it offloads cognitive work. But then it also is great, like a GitHub repo that was sort of completely white coded, what the heck are you going to do with it? I mean you got to then go again, apply AI to understand it. So the same thing is happening even in office and in knowledge work. So what I did, in fact, was go into Excel agent mode and use it essentially as a new linter, new reasoner, a new profiler because that's kind of what Excel does, right, which is it allows you to make sense of -- sort of my tool to reason over sophisticated outputs. In the past, only humans created it. Now humans and AI create it. And so that is sort of what's happening. And the one other thing, Keith, to your point, which is also fascinating, the network effects of intelligence is how I think of it. Think about -- I'm sitting in front of my CLI and GitHub and coding away and I say, God, we have all these design meetings that are going on. I updated -- I know one of my colleagues updated sort of a spec. It's in SharePoint. I want to make sure that the code that is in my repo is in sync with all of that, right? Literally, meetings and some document. I can go to Work IQ, which is the database underneath M365, right? In fact, I always said that's the most important database in the company that is least used as a database because they use it as just a transactional store. But now you can. I can load it up as an MCP server and GitHub. And I can say, please go check all my meeting notes, transcripts and SharePoint documents and make sure that the repo is in sync. And literally, it goes off and creates a plan and then starts executing a plan. That unlock of intelligence or the network effects of intelligence. In fact, I'd like to say that the next office, which is bigger than all of the office that came before, may be headless. And that is sort of going to be the TAM expansive part for us.

Right. Let's dig into that TAM expansive part and maybe focusing on Microsoft 365 and that franchise. It's always been a core franchise for Microsoft. You're talking about the increase in volume in Artifacts and GitHub. One of the other things we've seen is an increase in subscriptions. I think over 2025, we're over a 20% increase in subscriptions. So the users are increasing as well. And Microsoft, particularly Microsoft 365 has always been about enabling those users. So when you're thinking about this Agentic future, is it more users? Or is it just more agents? And how does Microsoft make sure that they stay in front of that curve?

Yes. I mean I think -- remember, subscriptions are just entitlements because it's easier to budget, right? Like why doesn't everybody just do consumption? The reason why everybody doesn't do consumption is sometimes it's easier to forecast. In fact, we are running into this now, right? With coding agents, we're running into it, which is because you kind of have this effect of sort of -- there are people who are using lots of tokens. There are people who are using what I'll call normal sort of volume of tokens. And so that by modality or the distribution is not yet stable. And so I think what's going to happen there, first, even for just users because there's -- if you think about there are 3 types of modes, right? There's chat, let's call it, what we will call tasks or cowork, right? It's delegated access. So I give something else, which is a synchronous, my credentials and say, please work on my behalf. So that's the second thing. And the third would be a full digital worker, right? So which is a -- it will have its own identity. It will have its own tools, it will have its own desktop, whatever, right? That sort of is the third thing. And so if you take all these 3, I think the combination of subscriptions with some limits of usage plus a meter is where I think we will end up. And it doesn't matter if it's a person or an agent. And I think the first place where this is happening already with the business models is in coding. And I think information work also will happen. So from a TAM expansive perspective, for us, I look at all agents as users and with maybe more flexibility on how people license that.

Got it. Got it. And if we think about sort of the conversation of evolutionary versus revolutionary, when I look at a lot of the dynamics of Microsoft 365 Copilot, but also what we're seeing more broadly in the environment and what the AIs are trying to do with their generic computing vision, it feels to me like an extension of what we've been talking about for a decade with Power Automate and Power Flow and Power BI of just bringing more visibility in terms of your systems, your data, who you're communicating with into one place. So do you see Copilot really emerging as a new AI-powered user interface for all that, for the systems, for the data, for your teammates for your communication?

Yes. I mean the interesting thing on this design side as to what happens to UI in general or what have you is -- the dream was always the case that can you have some form of a universal interface to all of computing. I mean that's kind of how operating systems evolved. The browser came next and so on. And so this -- the power of natural language and the access to all of the tools with an agentic loop, I think, makes it very powerful. The question is, if you look at even a model company, right, it sort of -- they started with chat and now there's multiple apps. So everybody has to -- this is where the power of UI, right? I mean what did OpenAI do with Codex? They have a Codex app. and makes sense, right? Because when you have something that is so strong in the sense of usage, then having a heads down usage app for that makes sense. But the workflow between this is what you have to manage. Like for example, even in the thing that I posted this morning was I kind of generate -- I assigned a task, it generated the spreadsheet. I actually use the spreadsheet right on Canvas inside of "task interface, right, inside of Copilot. I even have fantastic edit capability. By the way, this has been going on forever, right, which is how does Google Docs work versus Office? I mean it has an IR, an intermediate format. So basically, you kind of take office docs and you have an intermediate format in which you manipulate. So all these things will have some intermediate format in which you will work. And then ultimately, you can export out back to the full UI if you want to, so that you can go deep. And the other big thing is sharing, right? One thing, a lot of AI still is not yet fully cracked. In fact, you see this in coding. We've not fully cracked multiuser. So the next phase is inside of Teams for us, how do you crack agent to agent to human inside a channel. And that's where UI will matter because even if AIs are all doing their work, I as a human need to reason about it. I need the UI that I use. And that, I think, is where it will all come down to. Oh, by the way, the one other thing I should mention is we are looking at -- like I was looking at why are we spending so many tokens on all this, right? Sometimes it's kind of the most token inefficient things, right? The smart thing that I think everybody is going to start doing in the next year is tools use. That's sort of all software. And that is the way you make AI token efficient. So don't think of this as like tools. Think of it as even if you're all AI pilled, go and say, oh my God, I need a lot more software to make my AI efficient. That's another way this new world will be born.

Got it. Can we talk about sort of with Microsoft 365 Copilot and the -- getting this into your customer base. You have 450 million information workers that are using the suite. Investors got concerned by some demos that we saw from Claude with Claude Cowork. And for the first time in really the last, I would say, definitely 5 years, maybe a decade, there's more concern about the positioning that Microsoft has with Copilot. But then on the other side of the equation, when I look at my CIO surveys, 80% of the CIOs say that they're either using Copilot today or expect to use in the next 12 months. So CIOs are seeing something in Copilot that I think investors are missing. Can you help us bridge that gap? Like what are the CIOs looking for from Copilot that investors aren't seeing?

Yes. I mean I think, first of all, it's great to see, again, this is where the model capability and also these form factors, right? The -- and this happened even in coding, right, which is get up Copilot, pave the way. And then now we have, quite frankly, a lot of good competition. But the market is kind of massive, right? It's no longer the tools business that I grew up with for the last, whatever, 40 years, and this is a very different market, which is 100x what we were competing for. And so the form factor innovation that's happening, right, whether it's Chat or Now Cowork or Worker, that's sort of the direction. So for us, we want to do what we have always done, right, which is what we did even in the previous era, which is we have our permission in especially commercial customers through IT. And so we want to love our IT customers because they are the ones who care about lots of things. They care about security, they care about compliance. They care about all of the observability, right? I mean the reality is come on. I mean I can't launch open claw as Microsoft. I mean, it just wouldn't work. I don't have permission to do that because that would be considered Microsoft launching a virus. I mean that's just not a thing. And so what we have to do -- but at the same time, it's a fantastic innovation, right? That's where -- I mean, the fact is think about like what the last 15-year journey in enterprise was. They didn't want local file systems. And this is about exposing a full-on local file system. I mean, Morgan Stanley, if I go to [ 10 ] and say, hey, I have news for you, like please I launch something that where I want all the state and the local file system. I mean you'll keep me out of the room. So the thing that we have to be mindful of is really know where our permission comes from and also know what the expectations of our customers are and do a fantastic job of putting the form factors that people love. That's kind of one -- that's the path we are on. And if you -- to your point, what's happened is the unlock of Work IQ, which is, again, the database underneath M365. So you were showing me the one note. I mean, think about it, right? I prepped for a meeting. I just go in and say, hey, I'm meeting Keith, can you prep my meeting brief, right? It will literally know everything from 2014 to now, every meeting I've had with you, everything you said and which our folks noted and reason over it, not like a search, right? It's a state full agent. In fact, you can think of WorkIQ as our frontier model, right? It's basically the data plus the model embedded together. That's what the CIOs see the value, right? It's sort of compounding. When I say network effects of intelligence, that's a massive value for them, which is they've invested for 15 years on all of this, and now you can even compound the value.

Got it. It's a good segue into talking about the model layer. And there's definitely a lot of debate in the industry about the AI model layer and whether it's going to concentrate to a small number of frontier models that are just going to get bigger and better over time or whether we should be thinking about a broader set of models, more SaaS-specific models, to open source models. So how do you think about that trade-off between is this market going to consolidate? Or should we be thinking about an ecosystem of models?

I think there are a couple of things. One is, I think at this point, it's fairly clear industry structure-wise when it comes to the narrow way we talk about frontier models, like the American ones are closed, a lot of the Chinese are open. That, I think, is going to be multi-model, right? So there is not going to be a company or a product company other than the model companies, of course, are going to be homogenous, right? Any one of them -- but the reality is everyone sort of cotton on to look, if you're building any product, whether it's for coding agents or for knowledge work or wealth management or whatever, you want to access multiple models, right? That's going to be the case. And that means there's lots of very careful design that you want to do, which is you want to have the harness not get coupled with the model layer. So people are getting pretty sophisticated in making sure that the harness layer is decoupled. The other is the context layer also should be decoupled, right? You don't want effectively the one model to, in fact, vertically integrate into these 2. And that will be the game that will be played. But I'm pretty clear industry structure-wise, where we will go. Then the other question in the -- by the way, the other thing is people also will use a frontier model, like, let's say, there's something -- you have an eval, like everything is all about evals, right? So you have an eval, you want to max your eval, you use all these models. Let's say, one particular model was doing well on that eval. The next thing you do is you take all your traces and then you train the model that's the cheapest to be better and hill climb on that eval. And so that's what everybody does, right? So it's no one wants to sort of be inefficient in their token spend, whether it's a company app or whether it is an ISV. And so the game would always be about continuous optimization of these models. And then the next thing that also -- you asked the question, how many models should be there, right? I think there should be as many models as companies because if you think about it, the real sovereignty question in the world, it's not about even country sovereignty. It's about -- look, if really knowledge work, tacit knowledge of any enterprise of a firm is in the human capital they have, then it also needs to be in some model weights that they control. Otherwise, there's just going to be enterprise value transfer. Forget the software companies. It's like the rest of the economy. I mean that's where that [ Citrini ] thing sort of goes off on, which is that is what -- like -- and everybody is going to wake up. I mean I just don't think we live in a real world and a real political economy. And so therefore, people are going to say, oh, no, that's not going to happen in my house. I'm going to have my model that is sovereign and independent of any frontier model. And that's the other sort of direction of travel.

Got it. Can we talk about the model that Microsoft is building. Of course, you have a great relationship with OpenAI. You have research IP, right? So you get access to their models. But Mustafa is also working on models within Microsoft. Is there a differentiation between what Mustafa is working on versus what OpenAI is working on?

Yes. So we have 2 sort of -- we have the OpenAI models and the OpenAI IP. And so we have -- essentially, if you look inside of Copilot, whether it's GitHub or M365, we have lots of models. It's not a single model. The one model would be a midtrained OpenAI lineage or an MAI model. And so we basically are continuing to optimize these models. And what are we optimizing for our evals, right? So all of us now at this point, the game is about private evals because we know the benchmarks are all saturated. So the question is, how do you really make sure that any flops we assign to any research compute, right, whether it's post training of an OpenAI model or even our own model is all about maxing the evals that are private to -- so that means some product impact. That's the job #1. The second piece inside of that is all about COGS reduction, right, which is the auto mode, right? One of the things that I think this week or last week, there was a nice paper by the vLLM guys, the semantic router, right? If you remember when GPT5 came out, they had a router. And now even the sophistication of the routers are getting good, right? That means the models that you choose, the modes of the models you choose, the tools that you choose with it. That's kind of -- that's -- think of it as a meta model, right? That's the most important thing. So our auto mode inside a Copilot, M365 Copilot, GitHub Copilot, is essentially doing that optimization of maxing the evals, reducing the COGS on a continuous basis. And so our frontier work, our super intelligence work will all be about really getting good and hill climbing on it. So the great news for us is we have access for whatever, 5 more years or what have you until '32. So therefore, we want to max the value of what the OpenAI R&D is while also making sure we have all the capability. And it's no different than, by the way, what we are doing in silicon. I think you have Jensen here next, and we work deeply with him there, which he's doing lots of the innovation. And then we are also working on Maia and so a similar approach.

Got it. Got it. If we talk about the OpenAI relationship? It started 2018, very early before we were talking about any large language models or generative AI, but it's evolved a lot since then. What's the current status of that relationship? And how should we expect that to evolve on a go-forward basis? It's a very important relationship for Microsoft.

Yes. I mean I think -- yes, I mean, going back to 2018, I don't think any of us thought of -- we'll be here in 2026 talking about what is it, like close to $1 trillion company, right? I mean, that OpenAI is. And so we are thrilled to have invested in them, partnered with them. And although none of those things were sort of in my head at that time, who would have thought that I'll sort of earn the credit of being a good investor, but here I am. That's a great investment. But the thing that was foundational to it, it's fascinating. I always think back at it. The paper I read, which, by the way, was authored, one of the authors was Dario, when he was at OpenAI on scaling laws. And that was the bet, which is when they all sort of sort of have the conviction, Ilya, Dario, Sam, all of these chaps were really into, hey, look, the scaling stuff works and we should go at it. They showed me those charts, and I kind of understood it, but then I sort of said, now, these chaps are really good at this and they -- and I was always obsessed about NLP. So therefore, I wanted to take that bet. And so it's an important partnership. It's worked very well for them. It's worked very well for us. We also know that they're now a big company that they need some flexibility, and we've given them the flexibility. But they're also going to be a customer. We're an investor. We are going to be a partner. And they're also -- even the latest partnerships they have are all fine by us because at some level, our exclusivities, our rev share, our equity partnership is all sort of what's going to be healthier because of all this.

For me, one of the things that has marked your tenure as CEO at Microsoft is really embracing openness and open ecosystems, right? I think one of the foundational moments for me is when you came on stage and said, we're going to treat Linux as a first-class citizen on Azure. It almost feels like OpenAI and OpenAI relationship is similar, right, that it behooves both parties to have more flexibility, more openness to let them grow, you get the IP, you get the revenue share, and you both benefit from a more open relationship.

Yes. I mean I think since this is an investor conference and not a feel good conference, right, the thing that I go back to is there are very few zero-sum battles. And I think we overstate that a lot. And so when the big strategic mistakes are made, when you're not clear about, wow, what could be an expansive way for me to think about my opportunity versus getting narrowly stuck on everything being a zero-sum battle. In fact, our biggest mistakes, I would say, strategically would have been historically made when we didn't view -- like somebody else's success doesn't need to be a failure if you can write it. And it's sort of a thing that needs to be talked about more. And in fact, it is, like without Intel, I don't know if Windows would have happened, right? Without -- in fact, without Mac, I wonder whether Office would have happened, right? I mean that's sort of the world I come from, and I'm always looking for, first, what's the non-zero sum where we can add value to our customers. And then, of course, there are zero-sum battles and we'll compete.

Excellent. So if we talk about vertical integration. You talked about it a little bit in terms of needing to maintain flexibility with the harnesses and the context layers within the model. But there's also some really great innovation going on from Google, where they're integrating the TPU layer with the model layer. Is that something that Microsoft has to pursue more aggressively? Because I know you guys do have your own silicon initiative. How important it is to have that strong integration between sort of the silicon layer and the evolving software layers on top of it?

It's -- I think the way I think about all of this is if you take the -- like the broad perhaps investor question on this, which is what's the best way to think about ROIC on capital spend? I would say there are a couple of different dimensions to it, right? One is you want TCO to be great. You can't be upside down on cost. Now my belief is, since this is a multi sort of generation thing, it's not about any one time, right? So you really want to make sure you are always going to have the best TCO. And so that's why my fundamental bet is you want to have system software over a heterogeneous infrastructure. That way, then the latest innovation, right? I'm sure Jensen will come talk about sort of some very cool stuff he's working on next and let's call it, on some low latency inference. God, I want that, right? Why would I not -- like -- and maybe I'm also working on it, but it may be 2 years from now or 1 year. But no, I want the best always in my fleet. And then I want my system software laid out on top of right? So that's kind of where I like our thing about, hey, we have a Maia 300, 200 today that does competitively, right? It's, in fact, marked on TCO per dollar -- performance per dollar, it's leading, in fact. But that's leading today that is not a guarantee that it's leading all the time. So therefore, I shouldn't get too high on my own supply here just because I have this means that's the end of the game. No, I'm on that. And then let me then sort of make sure I'm also getting everybody else's innovation in, use software to then schedule across all of this and manage TCO by generation. Then the next layer, of course, is utilization, right? That's again a software game, really max the utility on it. Then make sure you have a diverse demand, right? We have 1P and 3P, even 3P. We have OpenAI book, we have Anthropic book, but we want to also have the long tail of enterprise IT. And so all 3 of these, I think, are more important than just like, oh, I have a model and sort of an accelerator, like TCO and cost economics is -- you got to have diverse customers, great utilization, multi-generation TCO curve. So it's a lot more sophisticated than just one simple thing.

Got it. You're talking about unit economics and the ROI of the CapEx spend. I think it's equally as surprised as we would have been in 2018 to be talking about how big OpenAI is. I think we'd be equally surprised to see how much we're spending on CapEx today, how much infrastructure we're building out in terms of data center. And it has caused concern amongst investors, does this fundamentally change the economics for Microsoft? Does this fundamentally make it a more capital-intensive business that's going to bring down gross margins? How do you see that equation playing out in the near term and then longer term?

Yes. I mean I think the -- I mean that capital intensity has been true even in the Claude era. And that, by the way, is the other thing that is probably worth pulling the thread on, right? We talk a lot about AI accelerators, which are obviously super important. But these agents are really driving up, guess what, regular compute uses, right? We like the innovation on the micro VMs and the containers and the security boundaries on this and storage requirements. So basically, it's a full-on system upgrade of everything, the network, the compute, the storage, this AI accelerator. And that's all obviously all exploding. And so therefore, the capital intensity increases. So I fundamentally think that this is a capital-intense business, but it's a knowledge-intense business as well, right? So that's a software business. So that's sort of the way I think that this industry is probably unique in the sense that the -- you can't think of it as just a pure industrial. This is where interestingly enough, even on the schedule of how profit comes, right, you think about it, it's not like we have retired any GPUs yet. Even though we have all the power constraints and so on, just because we have gotten our software so good and some of the workloads optimized, so good on that, that we are able to take the life of these things and really max them out. And so overall, I would say, yes, we have to manage a capital-intensive business, but using all the levers software gives us in managing TCO, managing utilization, optimizing the kernels by workload, ensuring that there's a diverse class of customers, using the diurnal curve even of utilization to create new SKUs to clear markets. I mean those are all things that I think will generate great ROIC. And this is probably unique. I know the way we have set it up is you track the Azure KPI. The thing that I keep complaining to Amy always is like, hey, I love the Azure KPI, but I don't allocate my capital to Azure KPI, right? I allocate my capital to the Microsoft KPI because I have these -- all these other businesses that are using the same capital. So my 1P, and it has a different gross margin profile. So that's kind of at least how we will, between Amy and me, will take a look at the long-term ROIC and margin profile of the business. And the margin dollars, not even just the margin percentage because even if it's a capital-intensive business, and we have the ability to use software to generate margin dollars, this will be a much bigger business than we ever had. I mean that was the thing. If you remember, Keith, it's funny that you've tracked us all through, right? I remember when I became CEO, everybody said, oh my God, isn't it too late man, like why bother to even build a public cloud because Amazon is so far ahead. And we knew it was going to be multiplayer. We knew that there is going to be margin, and we kept building. And so that is, I think, what -- and the reason why that was the case is it's software.

Got it. You touched on the allocations and capacity constraints, definitely a hot button topic for investors, the need to allocate towards R&D and first party versus just Azure. I was having dinner with [ Johnson Nielsen ] last night and said, the real solve to all of this is more capacity. It's kind of the first problem -- first-class problem to have of you have too much demand versus your capacity. How should we think about the time frame for that settling out for the capacity coming online that you could feed all of the mouths within Microsoft?

Yes. I think -- look, I think the challenge is what we are seeing is not just linear growth in some of the demand. And so therefore, I think the capacity challenge -- and it's also not any one thing, right? It's not just power, it's sort of silicon, it's wafers, it's substrates, it's memory, it's storage, it's everything. It's compute. And so I feel like it's going to take a lot more upstream capacity to get built, quite frankly, before we have some relief. So this is where -- this is there to stay. Then the question is what you said, which is how do we make sure we allocate things here that are strategic. And that's where I think the tension is, right, which is -- and I get it, which is you would like -- and not all of you uniformly, but some of you would like that allocation to work in ways that just maximize the short term. That makes no strategic sense for Microsoft, right, or Microsoft investors who are long term because you want to be careful, right? You don't want to sacrifice your own 1P, which is going to be higher margin by just not feeding that product. I mean that's not a sensible thing. Even like when we say, well, we're going to allocate to our R&D, as I said, we are not allocating to our R&D in ways to just sort of win some contest. No, I want to allocate my R&D to create a model that's going to COGS reduce, which is, again, sort of margins for investors long term, right? So therefore, that is the asymmetry we will have, right, between what decisions I'll make versus what you may want me to make in the short term, given the supply constraint. And so that's where we will just have to be very disciplined and by the way, one other thing that I'll mention is we also want to be careful about pricing, which is -- look, we see this even in our supply side, which is people are going to take different strategies. Some are going to be very long-term oriented. Some will be short-term oriented. And we'll remember that, by the way. And the thing that we want to be is long-term oriented even with our customers because these cycles will go -- come and go, and we don't want -- we want to earn trust in periods like this with customers who depend on us. And so these are all fairly important sort of criteria for us.

Outstanding. Unfortunately, that takes us to the end of our time, but really exciting times in software, really exciting times for Microsoft. feels like you guys are really positioned well for this opportunity. So thank you for coming.

And thank you, Keith, for your covering of us over all these years throughout my entire tenure, I deeply appreciate it. I know you're going off to do newer and better things. And so we wish you all the best on that one.

Thank you so much.