Karl Keirstead: Okay, let's get started. I'm Karl Keirstead covering Microsoft here, and we are always so honored to have Microsoft keynote our event. I was saying to Rajesh, it wouldn't be the same without Microsoft up on stage. So Rajesh, thank you so much for flying in for this.

Rajesh Jha: Well, thank you so much for having me, Karl.

Karl Keirstead: Yes. Rajesh, when I went online to look at all the parts of Microsoft that report up to you, it took me a little while because there are so many, but I summed up the revenue stream, and it was a very, very large number. So a very big part of Microsoft's portfolio sums up to this gentleman. Can you talk a little bit about what some of the common threads are between the different parts of the portfolio that report into you?

Rajesh Jha: Yes. So I lead the Experiences and Devices at Microsoft. It's got Office, Teams, so M365. It has our business applications, Dynamics, Power Platform, Windows, Surface and then, of course, M365 Copilot. And the common theme, Karl, for Experiences and Devices, it's what the name suggests, the experiences and devices for information workers on the globe to allow them to be productive, to be collaborative and ultimately drive business outcomes, economic opportunity. So it's a per user. Think of it as we are focused on the users in these organizations, small or large.

Karl Keirstead: Got it. That makes sense. So I think the -- there are several areas we're going to talk about, but clearly, one of the largest pieces is the M365, Office 365 portfolio, where it's still amazing to me that, that business as large as it is and as ubiquitous a product it is, is still growing by 15%. And Amy gave some good stats around seat growth and ARPU growth. But maybe you could just describe a little bit about the underlying growth drivers to get to that 15%. What's really behind the numbers, Rajesh, and in a way that might help us get confidence in the durability of, let's say, a teens growth rate?

Rajesh Jha: Well, M365, as we've said, is we are upwards of 400 million subscribers, paid subscribers. And the seat growth, we continue to see a healthy seat growth, even though we are mature in the enterprise space, small businesses, medium-sized businesses, first-line workers continue to drive seat growth for us. But the biggest drivers of the business now are really on the ARPU growth side. And the ARPU growth are primarily driven out of customers, three things that drive the ARPU growth. The first is customers choosing all of our suite, which is they may have in different flavors, different offers and they go to M365, the entire suite. And then the premium offering of M365, which is our E5 offering, is probably the largest driver of the ARPU growth. And then increasingly, and in fact, the second largest driver of the ARPU growth is Copilot. So we feel good about continued seat growth. We feel good about the ARPU growth. And yes, it's a large PxQ business.

Karl Keirstead: Let's -- we'll talk about a few of those things, but maybe let's start with the seat side. So I think in the most recent quarter, you guys announced 6% seat growth. Again, still amazing given the scale of that business. Obviously, investors for all SaaS businesses are worried about headcount cuts. Now the pace at which that seat growth is declining to me, speaks more to just scale and maturity. I don't really see any strong evidence that there's sort of an AI-induced seat pressure in that number yet. Do you mind opining a little bit on that dynamic?

Rajesh Jha: No, we don't see that, either. I'm not seeing AI as driving down seats in M365. If anything, I think AI is going to be an opportunity for us to drive seat growth. If you think about an organization in the future, it's going to have more agents than people. Many of these agents are going to be embodied. They're going to have an identity. They're going to be in the address book. They're going to have a mailbox. They're going to need a computer to do its computation in a secure way. You want to mention them. It's going to want to chat with you. It's going to want to join a meeting. To me, all of those embodied agents are seat opportunities.

Karl Keirstead: Yes. And then on the ARPU lift coming from customers embracing M365 and in particular, E5, how far into that opportunity, Rajesh, are we? And if you could remind the audience, is that still a security-led decision, given the number of security features you're putting in E5?

Rajesh Jha: The upside on E5 varies vastly by segment. First-line workers, less so, but in the enterprise, in the midsized markets, continue to see opportunity for E5 penetration. Then in terms of is security the biggest driver? I would say, yes. And increasingly, what we call compliance in a world of AI, data classification, data governance has become incredibly important. So the Purview aspect of E5 in addition to the Defender aspect of E5 is also starting to be a meaningful driver and a pull.

As customers want to go more broadly with AI and agents, they want to get the data governance of their data estate in a way that they can set the right policies for what's accessible to AI and what are the handling policies for AI and which so -- it's security end.

Karl Keirstead: Got it. And Rajesh, you mentioned that now, M365 Copilot might rank behind the E5 adoption as key driver of ARPU growth. So given the importance of that, let's talk a little bit about that. Microsoft obviously hasn't yet, at least maybe someday you will, give a metric on Copilot such as seat growth, et cetera. So what's your advice to the audience in terms of what we on the outside can monitor to get some sense of the traction that Copilot is having? Is it more anecdotal comments sort of ranking it as a key driver of ARPU? Is that it? Or is there anything else, Rajesh, you recommend we watch for?

Rajesh Jha: We continue to consider what else we would share and when. But there are a couple of things I can point to. As we recently disclosed, 2 quarters in a row, the daily active engagement with Copilot has more than doubled quarter-over-quarter. That, to me, is a real sign of product with increased intensity of usage and more users engaging with the Copilot experience.

Another one I would point to, maybe a couple of quarters ago, we said, what, 70% of the Fortune 500 had Copilot. Now that's up to 90%. And I do think the ARPU growth is a good one to think about. As we discussed, most of our seat growth today is in lower ARPU base, small businesses, first-line workers. And the fact that our ARPU growth has been stable, Copilot is a contributor to that. So I think the ARPU growth rate is it's a good one to watch. Our engagement rate is a good one to watch.

Karl Keirstead: Okay. That usage improvement, I can tell you, I don't think you were in the audience, but maybe some Microsoft members were. I did a panel this morning with a couple of the lead IT executives at UBS. As you know better than anybody, we've become a very large Copilot customer. So I asked our executives this question. And I think the stuff they shared with me was that UBS employee Copilot usage is up something like 9x on a year-over-year basis. So that's a testimony to what you're describing in terms of usage improvement.

Rajesh Jha: Yes, yes, we see that.

Karl Keirstead: Okay. Is there anything Microsoft can do to help large Copilot customers like UBS drive usage? How is Microsoft helping us get there?

Rajesh Jha: Yes, there's a ton we can do and a ton that we are doing and continuing to invest in, and we learn from our customers what else we have to go do. But let me just talk about a few of those things. The first, of course, is our customer success teams, all the way from deployment to change management, to scenario planning to business value workshop. And by the way, we've decided deliberately to have a bunch of that CSM or customer success management to be core out of the core product team. So the feedback loop between customers and the product team stays super high.

The second one, I would say, as more and more customers, including UBS, are starting to go beyond Copilot as an assistant to agentic workflows. We have FDEs, our forward deployed engineers, again sitting out, of my team, working with customers for the first 5 of the first 10 of these agents that we pick with the customer on either top line drivers or real cost reducers or efficiency or quality drivers. And then we are working with our SI partners so they can scale out and do some of the more -- some of the same.

A third thing that we're building into the product itself is called Copilot Analytics because we want customers to actually be able to measure the ROI and see the business value. So the Copilot Analytics, customers can now do cohort analysis. They can give Copilot to a bunch of users, have a control group and do an agent for one group, not do an agent for the other group. Join the metrics that we see in terms of collaboration and productivity and join that with their own KPIs and see what the ROI is and see what drives the usage at what time across which application. So we want to build more of that stuff in the product itself, and that's what the Copilot Analytics is about.

And finally, I think a big unlock increasingly is going to be agent governance and not just agent governance, broadly governance, even with UBS. Should they enable web grounding for Copilot or should they not enable web grounding for Copilot. So there are a set of controls they would like. When I issue a prompt, what part of the prompt actually leaves the compliance boundary? Do we have the right checks and balances? Because every deployment has to pass risk and governance and security. So we are now year two of this thing, and we are getting more and more mature in the governance. And likewise, on agent governance, it's a huge ask from customers.

So I've never seen an announcement in this realm generate the sort of excitement with the IT community that we had at Ignite, which is Agent 365. Because the big worry for customers is, hey, do we democratize the creation of agents? If so, do I have an agent sprawl where it's like the -- all Access database sprawl or VB Macro sprawl. With Agent 365, we give them one observability plane, one data classification plane, one identity plane, whether the agents are built by Microsoft, built by a third party. So we have a lot of partners in the state. So Agent 365 is going to be the other big product investment that we are making that is going to go and enable customers to go bigger with these things.

Karl Keirstead: And Rajesh, in terms of other drivers that might- the catalyst for unlock needs to come from your partners, not from Microsoft, is the model performance.

Rajesh Jha: Yes.

Karl Keirstead: I think a lot of us listened to Sam Altman a couple of weeks back and a pod he did. Where he was actually almost admitting that OpenAI needs to make the models even better as an unlock to get more people using AI applications like Copilot. So, where do you think we are on the model evolution? And do we need to wait essentially for GPT-6 to get the next big step function improvement in Copilot that would then drive even more usage? How dependent do you think the usage trajectory is on underlying model performance?

Rajesh Jha: I mean, clearly, if the model gets better, the experiences are going to get better. If architected correctly, you want your experiences to be modeled forward. The model gets better, the experiences get better. That's what modern experiences have to be crafted to go to. But I think there are three things that are already elevating the capabilities of Copilot and those -- I think the first is the reasoning model finally unlocks AI and graphical user interfaces to work much more effectively. So I'm very excited in the time -- in the January, February time frame, you're going to see agent mode inside of Office, inside of Excel, inside of Word, inside of PowerPoint, in your calendar, in your meeting, inside your Teams channel. And that is going to be a big one. It's one thing to go and say there's AI off on the side, which I think is a very interesting user experience because you get to express your intent in a natural language. But then to be able to take that same capability and bring that to existing workflows that hundreds of millions of people are already on with a graphical user interface and have those two coexist, I think the agent mode is going to be a big unlock. So that's thing one.

The second thing is what we talked about, enabling more agentic workflows. And this is where Agent 365 as a governance and a compliance plane enables customers to go without the worry of a sprawl or a management issue on their hands. And finally, with Copilot, we brought multiple sources of intelligence into Copilot. Just like if I hire an employee with liberal arts background to work on a project and I hire an employee with a STEM background to work on a project, they're going to bring different strengths. And so with Copilot, it's not just about the model. It's about how the models come together with the graphical user interface, the innate capabilities of the model, multiple lineages of the model to actually deliver the outcome or the workflow that you're planning to go do, whether in our applications or agents that you will build on your own.

Karl Keirstead: So let's press maybe a little bit on the enterprise agentic adoption, which you're describing as some interesting things coming that could be an unlock. So Rajesh, we do talk to some people who are more at the skeptical end of the spectrum where they say that it's going to be a long haul to get companies really embracing agents, especially agents acting relatively autonomously. You sound a lot more optimistic. What's the gap here that gives you that confidence? And where do you think generally enterprises are in investing heavily in agentic apps?

Rajesh Jha: I mean for sure, I mean, I will agree with the fact that it's not a uniform thing. I mean any enterprise -- any new technology goes through its enterprise curve with the risk and management, ROI analysis, business value, all of that stuff. That being said, let me just say, I mean, the word agent is so overused. I'd like to think about agents as three-- think of a spectrum. On one end of the spectrum, you've got what used to traditionally be an end user going and creating a great template or an access database or an Excel, if I'm a lawyer doing IP rebuttals, I have a 20-page contract as a template that my work group uses. Those things can be actually implemented very capably as an agent, built at the departmental level by a power user and that kind of a thing today has been really bottled up by a lot of customers because of the governance issue. And the Agent 365 really unlocks that because now you have governance, you have -- you can see what's been shared by who, how often is it used, what should get aged out. So that's one end of the spectrum. And by the way, companies are going to have to enable that, because no top-level IT or business leader of a large organization have visibility into the workflows that impact the daily lives of a lot of information workers. So anyway, that's one end of the spectrum.

The middle end of the -- in the spectrum is classic high-value applications. And these are applications that might be really important from a cost perspective, revenue perspective, quality perspective. And then agents are a great implementation. Take the GenAI engine, get the right grounding, right enterprise policies and you go enable that.

Now let me give you an example of such a thing that we talked about at Ignite finally getting to general availability with huge excitement by our customers. It's called employee self-service. Think of it as a template for an agent. Every customer that we talk to, every large organization has a help desk for IT. They have HR tickets coming in. They have people making requests for conference rooms, event management, all of those things. And so this is broadly applicable having an agentic workflow that can take all your business policies, quickly be able to tell you, hey, your kid is getting 26 that need to come off your medical plan. It is trivial for such an agent to get the right one click, let me go take care of that when you go to this agent.

But this is not a simple agent. And I was telling somebody like if you're an employee and you ask, hey, what's the paternity leave policy and you happen to be in Norway, HR is very particular for that particular thing. There needs to be no AI. It needs to be the authoritative HR policy that needs to be given back to the employee. If somebody files a ticket saying, "Hey, I'm depressed, I'm looking for resources." You don't want HR adjudicating. You want that employee to be connected to a human. So the ESS is kind of a broadly applicable app pattern, agent pattern that we are starting to go build to enable and bootstrap this kind of an agent deployment.

And then the other end of the spectrum of agents are digital workers. They're going to show up in your org chart. They're going to show up in a meeting roster. They're going to show up as a part of the channel member. You're going to mention somebody who's a new digital marketing employee in your marketing group to go do research and give you back a document that they post back into the Teams channel. That is probably the most immature end, but 2026, you're going to start to see those things happen as well.

Karl Keirstead: Okay. That's exciting. Let me ask you a couple of more questions about Copilot, then we'll move on to other parts of your portfolio. One of the interesting announcements that Microsoft made recently was that, well, Copilot has to date been run largely on OpenAI models. You announced a partnership where customers can access essentially an Anthropic version of Copilot. Can you describe that decision? What's the thinking behind that?

Rajesh Jha: Yes. Again, I mean, with Copilot, our goal here is to make sure you can get to the outcome that you were trying to get done as an information worker or in the context of a business process. And we noticed that the Anthropic model does a pretty good job with different perspective. If I ask OpenAI model to do research on a given topic, it tends to be well written, well crafted. If I ask the Anthropic model to do the same thing, I'm going to see many more charts, it's going to be much more concise, neither is better than the other.

And so I want to give a choice to the user as to what works best for them. And they could run both, pick the one that they want. And so it's no different than like I said, if you hire two employees in your work group and they come from two different backgrounds, two different schools, two different skill sets, they're going to do different -- they're going to do very competent work, but it's going to be different. And so for us, it's about the best possible outcomes.

And by the way, it's not just the Anthropic model, the OpenAI model. I think one of the more interesting things that we've seen customers go do is if you have a business process that is unique to you, that is your differentiated IP as a financial services and insurance company as a pharmaceutical company, you want the model to be tuned to your IP, with the weights belonging to you, not the weights collapsing into the model. And so that's what Copilot tuning is about. We'll let customers take a base model, tune it with no Microsoft eyes on it with their subject matter experts, create a fine-tuned model, measure the efficacy of the model against the base model and then deploy it back into the Copilot experiences that our employees are going to go use. So it's less about the model. It's making sure that the entire experience is optimized for the outcomes you're trying to drive.

Karl Keirstead: Okay. Last one I want to ask you on Copilot is around competition. So I'm sure when you and the leadership team launched M365 Copilot, you were under no illusion that you would have that market to yourself. It's always competitive in every corner of the software space. But your -- one of your key partners, OpenAI, now is trying to scale into their targets, partly on the back of ChatGPT for enterprise, which many organizations might use alongside Copilot, maybe in some cases, instead of. Google with Gemini now is pushing Gemini for enterprise. So getting a little bit more competitive. What are your thoughts, Rajesh, on the ability of Microsoft to stay ahead of those two rivals in particular?

Rajesh Jha: It's a great question. So let me first just say, look, I mean, with -- let me talk about Copilot. What's differentiated, what's unique. The first thing we got to do is to make sure we meet users' expectations with what they expect generative AI to do, be a great writer, be a great analyzer, be able to tell you the weather, create an image and all of that stuff. So that's table stakes. We're going to go do that, and we're going to be competitive like any other Gen AI tool on that. Now let's talk about what's unique and what's differentiated.

The first thing is what we call Work IQ, which is understanding your work context. Most of the people powering economic activity around the globe are on M365. So Work IQ gives us a pretty good understanding of the projects that matter to you, who your work group is, what events are interesting, who are your customers, your e-mails, your meetings, your documents. We have a pretty good understanding of that stuff. Then you'll hear the other tools talk about connectors. Connector is trying to drink through a very thin straw and understand your work context. Now you can take many sips from a thin straw, it is still a thin straw. And so we have customers who've done side-by-side analysis of Copilot in the context of your work and connector-based things and the gap is very significant and growing. So anyway, that's just thing one.

Thing two, though, as people use Copilot both as a new endpoint as a peer to what Excel, PowerPoint, Outlook, Teams, as a pure endpoint. But they have billions of transactions every hour that go through these applications. We have an opportunity to serve the same Work IQ intelligence with agent mode inside of these existing applications that people use, we can uniquely do that well. That's thing two.

Thing three, human-to-human collaboration, communication, productivity, highly regulated. We have 15 years' experience on how to do eDiscovery, sensitivity label, all sorts of things, legal hold, data classification, data governance. All of that works with human to AI conversations in Copilot automatically for customers. Our 15 years of maturity on that stuff is enterprise-grade maturity and human-to-human productivity. Human and AI productivity gets all of that for free. The other providers are going to have to go build all of that capability.

Thing four, can I keep going. So thing four, though, it's like can I go back to we are not beholden to a model. We are beholden to the best outcome. And so we will build experiences that are powered by whether it be our IP partner, OpenAI, whether it be Anthropic, whether it be copilot tuning, whether it be an open source model whose weights you want to go create as your own unique IP. So we are multi-model.

Finally, the more important thing that I go back to the comment I made earlier, if you think that the future workforce is going to have more agents than humans, and this is going to be true in every organization. How is the human supposed to get work? I thought that the beauty of AI was I don't have to worry about tools anymore. I have one natural language interface that abstracts away the tools, and I express my intent. In a world where now I'm surrounded by hundreds of agents that are semiautonomous, some that I'm managing, some that I have to rendezvous with, how does a human navigate all of that stuff? Copilot is going to be the UI through which they orchestrate the agent. We are going to be the search engine for these agents. We're going to be the relevance engine for these agents. We're going to be the orchestration engine for these agents. IT is going to have a bunch of controls. Karl, you're in this department. The following agents are the most relevant to you. You work group created an agent that you tend to use a lot. Copilot will know to use that. So when you put all of these things together, I really like our ability to go serve M365 customers with M365 Copilot.

Karl Keirstead: Yes. Rajesh, I had so many other questions on other parts of your portfolio like Teams and Windows that I don't even have time for. But I noticed we have 2 minutes left, and I do want to get to one last one that I know is of interest to this group, and that is the compute capacity. So Microsoft obviously needs to stand up an enormous amount of compute capacity for multiple constituents. You've obviously got partners like OpenAI that have demands on you. You've got enterprise customers like UBS that over time, if not today, need Azure-based compute capacity.

Rajesh Jha: Absolutely.

Karl Keirstead: But this conversation is about really Microsoft's first-party applications because you need to ensure that the Copilot and Agentic AI experience is robust. So you need to make sure that you've got enough compute capacity to serve your first-party apps. So I guess the question is, how big a constraint is that? How big of a problem is it, given that Microsoft, as Amy described to all of us, is very compute constrained right now. So how do you ensure, Rajesh, that you knock on Amy's door and make sure that she's carving out sufficient compute for your business?

Rajesh Jha: Yes. You're right, Karl. I mean this is a multidimensional thing that we spend a lot of time on. But holistically, it's what you would expect. We take a left to right view across our third-party commitments, our first-party commitments. Inside of the first-party commitments, clearly, M365 Copilot, GitHub Copilot, these are the huge priorities. But it isn't as simple as which is priority one, which is priority two. There are multiple dimensions to this. I mean, not all scenarios need all sorts of hardware. Not all load happens at the same time across the globe.

We have different geo ring-fencing constraints in different parts of our businesses. Saturday morning peak, Saturday, 3:00 a.m. is our lowest use time. What parts of the AI can be done asynchronously during that time? How much latency is affordable for which segment? How much optimization can we bring out, not just at the chip level, but in the global routing level to optimize for all of these things. And so we work this multidimensional thing even as we add more and more capacity, and we look left to right against all the prioritization. So suffice it to say, this is top of mind, and I feel good about the process we have in place to meet all the stakeholders and navigate that.

Karl Keirstead: Got it. Okay. I think that's all the time we have. Rajesh, I learned a lot. Thank you. And I'm very proud to work for what's now become a pretty significant Microsoft Copilot and Azure customer.

Rajesh Jha: Keep the feedback coming, Karl.

Karl Keirstead: Thank you. Thank you so much.

Rajesh Jha: Thank you, Karl.