Company Management
Amy Hood - EVP & CFO |
Brett Iversen - General Manager, IR |
Satya Nadella - Chairman & CEO |
Analysts
Aleksandr Zukin - Wolfe Research |
Brent Thill - Jefferies |
Karl Keirstead - UBS |
Kasthuri Rangan - Goldman Sachs Group |
Keith Weiss - Morgan Stanley |
Kirk Materne - Evercore ISI |
Mark Moerdler - Sanford C. Bernstein & Co. |
Mark Murphy - JPMorgan Chase & Co. |
Keith Weiss - Morgan Stanley - Analyst
A very nice end to a great fiscal year. Satya, you started your comments talking about how every customer conversation has the customer asking you about utilizing generative AI technology and how fast they could utilize that generative AI technology. What's the answer? What do you tell them in terms of the pace with which that could get into the marketplace and your customers can start using it?
And then for Amy, how should investors think about just the fundamental gross margins behind these generative AI technologies? We understand there's going to be a lot of CapEx to ramp up underneath these. But what should we expect in terms of what the ultimate gross margin looks like underneath all these new generative AI solutions?
Satya Nadella - CEO
Thank you, Keith, for the question. The fundamental guidance and conversation that we have with customers is twofold. One is the easiest path to value out of generative AI is to adopt certain solutions, for example, GitHub Copilot. In some sense, it's sort of a no-brainer to add productivity leverage for all of the software developers in any organization. Whether you're a bank, you're a retailer or you're a software company, it applies to everyone. So that's probably one of the things that we have seen very good -- even productivity data and great adoption.
And then obviously, the excitement that there is already around the M365 Copilot. So first thing we sort of talk about is how we ourselves are deploying all these Copilots across, whether it's Sales Copilot or M365 Copilot or GitHub Copilot, how do you get maximum value out of these horizontal tool chain? And then on top of that, we have taken what we did underneath these products and built it out as a first-class tech stack, right, which we talked at our developer conference, called the Copilot Stack, and then with Azure AI tooling, made it possible for a someone like Moody's to build their own Copilot for their people.
So to us, we want to be able to help customers build their generative AI applications on top of Azure AI, and with speed, if you will. And so those are the 2 things that we ask them to identify where they can get the maximum productivity leverage. And then we even swung with our own resources to help them get those things done. And the last comment I'd make is the cloud and data in the cloud enables all this because I think the diffusion cycle here, in some sense, we have a new set of cloud meters that are getting adopted faster because of everything else that came before it in the cloud. So those would be the observations.
Amy Hood - CFO
And to your question, Keith, on gross margins and how I think about those going forward, the first thing I would say is that I expect gross margins here to transition over time, just like they did in the prior cloud transitions. I would also say I expect workloads and the gross margins of the workloads to be different, just like they are in the cloud today.
I would also add one thing that's different than last time, we talked a bit about this before, is that we start out in a different place with more of a shared platform, which allows us to scale those gross margins a bit faster than last time. And we do expect, as you asked and Satya talked about, the pace of this adoption curve, we do expect to be faster. So you're seeing the CapEx spend accelerate in Q4 and then again in Q1, and we've talked about what it should look like the rest of the year.
Now that being said, we're talking about all that and going through that transition while delivering in FY '24 over FY '23, effectively 1 point higher operating margins. Because if it's flat year-over-year, as we guided, with the headwind from the useful life change, when you correct for that, it's about 1 point higher. So I think the real focus here is being able to be aggressive in meeting the demand curve and focusing on the transition and growth in gross margins and delivering the operating leverage.
Brent Thill - Jefferies - Analyst
Satya, on the optimization headwinds that you continue to see, when do you think we hit peak optimization? Are we getting close to hitting that peak and getting some relief in the back half of the year and maybe AI helping provide us a tailwind? Any color from what you're seeing from your perspective would be helpful.
Satya Nadella - CEO
Sure, Brent. Thank you for the question. Yes, a couple of observations. One is, I think, overall in the cloud, you do see new project starts and then those project starts get optimized and then you sort of time-series all of that, and that's sort of what you see in the normal course. What happened here was during the pandemic, obviously, there were lots of new project starts and optimization in some sense was postponed, and that's where you're seeing, I'll call it, catch-up optimization. And that's something that, to your point, we will lap. Going into the next couple of quarters, I think, it will come down.
And we are seeing new project starts, both traditional type of project starts, even cloud migrations, data applications and, of course, obviously, the AI applications. But we'll get back to I'll call the normal pace of new project starts and optimizations going forward, that we will cycle through, I think, in the next couple of quarters, what is the last catch-up optimization.
Amy Hood - CFO
I would just add, Brent, I think to Satya's point and maybe to build a bit of a line for you, I think it felt very similar to last quarter where we made the same comments, which is we're seeing sort of the normal optimization plus we're seeing new workload starts across these workloads Satya talked about. And I think that's what we're saying going forward and really what the change is just that lapping of, I think, a bit of a catch-up from a year ago. And you're right, we'll continue to do that through H2.
Mark Moerdler - Sanford C. Bernstein & Co. - Analyst
And congrats on the quarter. Amy, CapEx moved up significantly Q-over-Q and year-over-year and it's increasing moving forward. Can you give us some color? Is it physical data centers? Is it predominantly servers? Is it predominantly AI-driven? How should we think about the useful life of it? And then quickly for Satya, can you give us some -- status on the general availability of the full Copilot development stack? And how long it's taking clients and partners to build Copilots?
Amy Hood - CFO
Why don't I start on the CapEx question, Satya, then I'll turn it over to you. Mark, really, first of all, both in Q4 and then talking about Q1, the acceleration is really quite broad. It's both on -- both the data centers and a physical basis plus CPUs and GPUs and networking equipment, think of it in a broad sense as opposed to a narrow sense. So it's overall increases of acceleration of overall capacity.
And I think if you look back over really FY '23, you wouldn't have seen some of the pace on normal, what I would say, capacity adds, even for the normal Azure workload. So you're seeing both accelerations, the normal Azure workloads plus some of the AI workloads, is partially the reason. So it's why I do comment quite often that it's both overall Commercial Cloud demand and building out capacity for AI. It's both.
Satya Nadella - CEO
Yes. And I think just for perspective, I think it's sort of always good to think about it, right, where we have, what, $111 billion commercial cloud business growing at, what, 22% year-over-year. And then you had a CapEx growth, which is around the same number, 23%, 24%. So in some sense, it's sort of replacement capital plus some new capital that is going to drive new growth. So that's, I think, the scale. And we feel good about that structure of overall growth rates and how it translates into future TAM opportunity for us.
And then to your other question on how all this translates into project starts effectively, the Copilot stack is available today on Azure. So we have everything from Azure AI tool chain where you can use obviously, Azure OpenAI or even you can use open models from Llama and Hugging Face models. You have all the Fabric and all of our operational data stores for what is one of the most useful patterns around generative AI as what is called Retrieval Augmented Generation, which is you take the data that you have in the data stores, use it in a prompt to generate completions, summaries, what have you. And so that's something that we've seen a lot of and the Copilots are fundamentally orchestrations of that. And so we have these services available.
The thing that's fascinating is when you use something like Power Virtual Agent, you have a low-code, no-code tool to build effectively these AI products or full-fledged Copilots like we've built. And all the underlying primitives for that are available on Azure. The tool chain is available on Azure and the speed with which customers are able to deploy them, ISVs are able to build them, is pretty impressive.
Kasthuri Rangan - Goldman Sachs - Analyst
Congratulations on the quarter. If I could, I just wanted to get your thoughts to shift the discussion away from COGS and the CapEx to more of the top line outlook. It looks like Azure growth rate is definitely starting to stabilize and generative AI contribution to Azure is measurably improving quarter-over-quarter, and optimization in a broader sense is also starting to settle down.
Where does this leave with the company's outlook for Azure growth rate in the future quarters? Are we at a point where we've bottomed out, and we could start to see some acceleration due to the trends we discussed? And also if we take the superset of Microsoft Cloud, when you throw in the new pricing for Copilot, it certainly looks like the TAMs are opening up in a pretty significant way. So when you take the broader lens, that 21%, 22% growth rate that Satya and Amy referred to, what could be the outlook? Could we be too optimistic in entertaining hopes of some kind of acceleration in the years ahead? Or how do you think about the outlook on the top line?
Satya Nadella - CEO
Sure. Kash, thanks for the question. So maybe I'll start and then, Amy, you can add because I think -- we do think about what's the long-term TAM here, right? I mean this is -- you've heard me talk about this as a percentage of GDP, what's going to be tech spend? If you believe that, let's say, the 5% of GDP is going to go to 10% of GDP, maybe that gets accelerated because of the AI wave. Then the question is how much of that goes to the various parts of our Commercial Cloud and then how competitive are we in each layer, right?
So if you sort of break it down, you sort of talked about how Microsoft 365, we think of this Copilot as a third pillar, right? We had the creation tools. We then had all the communication and collaboration services, and we think the AI Copilot is a third pillar. So we are excited about it. Amy talked about how we want to get it out first and part of this preview. And then in the second half of the next fiscal year, we'll start getting some of the real revenue signal from it. So we're looking forward to it.
But we think of it long term as a third pillar, like we thought about something like, say, Teams or SharePoint back in the day, or what have you. Then Azure, the way I think about it is we still are, whatever, you're inning 2 or inning 3 of even the cloud migration, especially if you view it, right, whether by industry moves to the cloud, segment move to the cloud as well as country adoption of the cloud, right? So there's still early innings of the cloud migration itself. So there's a lot there still.
And then on top of that, there's this complete new world of AI driving a set of new workloads. And so we think of that, again, being pretty expansive from a TAM opportunity and we'll play it out. But at the same time, we are a $111 billion commercial cloud that has grown in 20s, and so therefore, we do hit law of large numbers. But that said, we do think that this is a business that can have sustained high growth, which is something that we are excited about.
Amy Hood - CFO
And I think the only thing, Kash, I would add is, I think in some ways, what we're really pointing to is there's a process here. We see the demand signal is quite strong. It remains strong. I'm thrilled with all the product announcements we've made. I'm thrilled with them moving to paid preview and then moving to GA. They absolutely are expansive in terms of addressable market. They reach new budget pools is almost the way I talk about it a lot in terms of how CIOs or CFOs that I talk to think about that investment. So a growing opportunity.
And as you know, we're focused on executing against that. And then revenue is an outcome. But it certainly does require -- the demand signal requires the capital expense and then creates the opportunity. And that's why I think, in some ways, we're spending a little more time talking about some of that investment is because it is the demand signal.
Karl Keirstead - UBS - Analyst
Okay, great. Amy, if I could double-click a little bit on the exciting news around M365 Copilot as everybody on the line looks to layer that opportunity into our models, I just wanted to get your views. Are there any guardrails you'd offer us to sort of keep us in line? Is there a degree of gross margin pressure in the Office segment? In other words, is it a fairly cost-intensive new product that we should keep in mind? And also, could it pull along Azure in the sense that you need Azure AD and perhaps some of the other cybersecurity products? So a little color there might help everybody with their modeling exercise tonight and in the coming weeks.
Amy Hood - CFO
Thanks, Karl. I think maybe I'll first start with the process we have when we release new products. And I absolutely understand we are excited, too, by the demand signal, the customer reaction, really the requests we're getting to be in the paid preview. It's all encouraging. As you know, we've -- last week, we announced pricing, then we'll continue to work through the paid preview process get good feedback. Then we'll announce the general availability date, then we'll get to the GA date. Then we'll, of course, be able to sell it and then recognize revenue.
And that is why I continue to say that I am just as excited as everyone else about this, and it should be more H2 weighted. And we've, I think, given you some sizing opportunities. And I think I would use all that. But I do think this is really about pacing. And of course, we've still got to get our Security Copilot and some of the Dynamics workloads priced and released. And we'll continue to work toward that.
And of course, I think one of the things that people often, I think, overlook is, and Satya mentioned it briefly when you go back to the pull on Azure, I think in many ways, lots of these AI products pull along Azure because it's not just the AI solution services that you need to build an app. And so it's less about Microsoft 365 pulling it along or any one Copilot. It's that when you're building these, it requires data and it requires the AI services. So you'll see them pull both core Azure and AI Azure along with them. And I think that's an important nuance as well.
Satya Nadella - CEO
Yes. If I could just add to what Amy said, the platform effect here is really all about the extensibility of the Copilots. You see that today when people build applications in Teams that are built on Power Apps and those Power Apps happen to use something like SQL DB on Azure. That's like a classic line of business extension. So you'll see the same thing. When I have a Copilot plug-in, that plug-in uses Azure AI, Azure meters, Azure data sources, Azure semantic search. So you'll see, obviously, a pull through not only on the identity or security layer, but in the core PaaS services of Azure plus the Copilot extensibility in M365.
Mark Murphy - JPMorgan - Analyst
Satya, there's so much evidence now that GitHub Copilot is boosting developer productivity by 40% to 50% or more, and it's resulting in higher quality code. Do you envision a similar level of productivity boost for the Microsoft 365 Copilots or the Security Copilot or the Sales Copilot? In other words, can every room in the house be remodeled to a similar extent such that, that value proposition is pretty elevated across the entire stack?
Satya Nadella - CEO
Yes. Judson Althoff would love you for having used his metaphor of remodeling every room of the house with AI because you're absolutely right. I mean that's the opportunity we see. I think what you're also referencing is now there's good empirical evidence and data around the GitHub Copilot and the productivity stats around it. And we're actively working on that for M365 Copilot, also for things like the role-based ones like Sales Copilot or Service Copilot. We see these business processes having very high productivity gains. And so yes, over the course of the year, we will have all of that evidence.
And I think at the end of the day, as Amy referenced, every CFO and CIO is also going to take a look at this. I do think for the first time -- or rather, I do think people are going to look at how can they complement their OpEx spend with essentially these Copilots in order to drive more efficiency and, quite frankly, even reduce the burden and drudgery of work on their OpEx and their people and so on. So therefore, I think you're going to see all of that translated into productivity stats, and we're looking forward to getting that data out.
Aleksandr Zukin - Wolfe Research - Analyst
I guess maybe just a multi-parter. You mentioned a couple of times that with the AI workload adoption that you're seeing on Azure, it's starting to look maybe a little bit different from an incremental share gain perspective versus previous generations. Can you maybe expand upon that? How should that drive for Azure consumption, particularly as we get through the year? And do you see a scenario where either the combination of lapping the optimization headwind, plus the AI contribution, plus this incremental tailwind that you're seeing around the workloads actually does drive a reacceleration in Azure, particularly in the second half when you're going to start to see some of those things kick in?
Satya Nadella - CEO
Yes. I mean the thing that we are both seeing and excited about is both the new workloads. I mean if you think about Azure, we have grown Azure over the years coming from behind. And here we are as a strong #2 in the lead when it comes to these new workloads. So for example, we are seeing new logos, customers who may have used out of the cloud for most of what they do, or for the first time, sort of starting to use Azure for some of their new AI workloads.
We also have even customers who've used multiple clouds who use that for a class of sort of workloads also start new projects when it's transferred in data and AI, which they were using other clouds. So what I think you will see us is more share gains, more logo gains, reducing our CAC even. And so those are the things of points of leverage. But at the same time, we are not a small business anymore in any of these things. We're significantly -- we have significant scale. And so, yes, we celebrate. That's why we're even giving you the visibility at 1 point of it showing up this quarter, a couple of points showing up next quarter. And those are material numbers.
And so that's kind of what I think will track. And I think Amy mentioned it because we want -- there are 2 parts to even AI, right? There's the models themselves with our partnership with OpenAI. That's sort of one type of spend on compute. And the other is much more revenue-driven, right, which is we will track the inference cost to the revenue and demand. And you're already seeing both of those play out.
Kirk Materne - Evercore ISI - Analyst
Satya, I was wondering if you could expand a little bit on your comments on data platforms. I think we've heard a lot over the last quarter or so about if you don't have a data strategy, it's tough to have an AI strategy. Can you just talk about where customers are right now in that journey to have a more, I guess, thoughtful data strategy? And what does that mean in terms of their ability to adopt AI services? Meaning do they have to sort of tackle the data issue first before they can really take advantage of all the AI services? Or how should we think about that sort of juxtaposition?
Satya Nadella - CEO
Yes, sure. Thank you for the question. Yes, absolutely. I think having your data, in particular, in the cloud is sort of key to how you can take advantage of essentially these new AI reasoning engines to complement, I'll call it, your databases because these AI engines are not databases, but they can reason over your data and to help you then get more insights, more completions, more predictions, more summaries, and what have you.
So those are the things when we say Copilot design pattern, that's sort of what that design pattern is all about. The thing that perhaps even in the last quarter, and I had that in my remarks, that's most exciting is how with Microsoft Fabric, especially for the analytics workloads, we brought together compute, storage, governance with a very disruptive business model.
I mean to give you a flavor for it, right, so you have your data in an Azure data lake. You can bring SQL Compute to it. You can bring Spark to it. You can bring Azure AI or Azure OpenAI to it, right? So the fact is you have storage separated from all these compute meters, and they're all interchangeable, right? So you don't have to buy each of these separately. That's the disruptive business model. So I feel that we are well -- Microsoft is very well positioned with the way our data architecture lays out our business model around data and how people will plan to use data with AI services. So that's kind of what I mean by getting your data estate in order. And it's just not getting data estate in order but you have to have it structured such that you can have the flexibility that allows you to exercise the data and compute in combinations that makes sense for this new age.
Brett Iversen - General Manager, Investor Relations
Thanks, Kirk. That wraps up the Q&A portion of today's earnings call. Thank you for joining us today, and we look forward to speaking with all of you soon.
(Tips:This transcript is converted by recording, we will do our best, but cannot fully guarantee the accuracy of the conversion, it is for reference only.)
公司管理
Amy Hood-執行副總裁兼首席財務官 |
Brett Iversen-投資者關係總經理 |
薩蒂亞·納德拉——董事長兼首席執行官 |
分析師
Aleksandr Zukin-沃爾夫研究 |
Brent Thill-傑富瑞集團 |
Karl Keirstead-瑞銀 |
Kasthuri Rangan-高盛集團 |
Keith Weiss-摩根士丹利 |
Kirk Materne-Evercore ISI |
Mark Moerdler-Sanford C. Bernstein & Co. |
Mark Murphy-摩根大通公司 |
基思·魏斯 -摩根士丹利-分析師
爲一個偉大的財政年度畫上了非常好的句號。Satya,你在評論開始時談到了每次客戶對話中客戶是如何詢問你使用生成式 AI 技術的,以及他們能以多快的速度利用這種生成式 AI 技術。答案是什麼?就它進入市場的速度以及你的客戶可以開始使用它的速度而言,你能告訴他們什麼?
然後對艾米來說,投資者應該如何看待這些生成式人工智能技術背後的基本毛利率?我們知道在這些之下會有大量的資本支出增加。但是,就所有這些新的生成式人工智能解決方案之下的最終毛利率而言,我們應該期待什麼?
薩蒂亞·納德拉 - 首席執行官
謝謝你,基思,提問。我們與客戶之間的基本指導和對話是雙重的。從生成式 AI 中獲得價值的最簡單途徑之一是採用某些解決方案,例如 GitHub Copilot。從某種意義上說,爲任何組織中的所有軟件開發人員增加生產力槓桿都是不費吹灰之力的。無論你是銀行、零售商還是軟件公司,它都適用於所有人。因此,這可能是我們所看到的非常不錯的事情之一,甚至是生產率數據和很好的採用率。
然後很明顯,M365 Copilot周圍已經令人興奮了。所以我們首先要談的是我們自己是如何部署所有這些副駕駛的,無論是 Sales Copilot、M365 Copilot 還是 GitHub Copilot,你如何從這些橫向工具鏈中獲得最大價值?最重要的是,我們利用了我們在這些產品之下所做的事情,將其構建爲一流的技術堆棧,對,我們在開發者大會上談到了這個堆棧,叫做 Copilot Stack,然後使用 Azure AI 工具,讓像穆迪這樣的人能夠爲自己的員工構建自己的Copilot。
因此,對我們來說,我們希望能夠幫助客戶在 Azure AI 之上快速構建他們的生成式 AI 應用程序,如果你願意的話。因此,這是我們要求他們確定在哪裏可以獲得最大生產率槓桿的兩件事。然後我們甚至動用自己的資源來幫助他們把這些事情做好。我要說的最後一句話是雲端和雲端的數據可以實現所有這一切,因爲我認爲這裏的擴散週期,從某種意義上說,我們有一套新的雲計被更快地採用,因爲雲中還有其他所有東西。因此,這些就是觀察結果。
艾米胡德 - 首席財務官
對於你的問題,基思,關於毛利率以及我如何看待未來的毛利率,我要說的第一件事是,我預計這裏的毛利率將隨着時間的推移而發生變化,就像之前的雲過渡一樣。我還要說,我預計工作負載和工作負載的毛利率會有所不同,就像今天在雲端一樣。
我還要補充一件與上次不同的事情,我們之前談過這個問題,那就是我們從另一個地方開始,有了更多的共享平台,這使我們能夠比上次更快地擴大毛利率。而且,正如你所問和薩蒂亞所說的那樣,我們確實預計,這種採用曲線的步伐會更快。因此,你會看到資本支出在第四季度加速,然後在第一季度再次加速,我們已經討論了今年剩餘時間應該是什麼樣子。
話雖如此,我們正在談論所有這些,並在24財年比23財年交付的同時經歷了這種過渡,營業利潤率實際上提高了1個百分點。因爲如果按照我們的指導,同比持平,受使用壽命變化的不利影響,當你糾正這個問題時,它會高出大約1個百分點。因此,我認爲這裏真正的重點是能夠積極滿足需求曲線,專注於毛利率的過渡和增長以及提供運營槓桿作用。
布倫特·蒂爾 -傑富瑞-分析師
Satya,關於你繼續看到的優化不利因素,你認爲我們什麼時候達到優化峯值?我們是否快要達到這個峯值並在下半年得到一些緩解,也許人工智能可以爲我們提供順風?從你所看到的角度來看,任何顏色都會有所幫助。
薩蒂亞·納德拉- 首席執行官
當然,布倫特。謝謝你的提問。是的,有幾點觀察。一個是,我認爲,總的來說,在雲端,你確實會看到新的項目開始然後這些項目開始得到優化,然後你會對所有這些進行時間序列,這有點像你在普通課程中看到的。這裏發生的事情發生在疫情期間,很明顯,有許多新的項目啓動,從某種意義上說,優化被推遲了,這就是你所看到的,我稱之爲追趕優化。就你而言,這是我們要圈的東西。我認爲,進入接下來的幾個季度,它會下降的。
而且我們看到新的項目開始了,傳統類型的項目都開始了,甚至是雲遷移、數據應用程序,當然還有人工智能應用程序。但是我們會回過頭來談談我稱之爲新項目啓動和未來優化的正常節奏,我認爲,在接下來的幾個季度中,我們將循環進行最後一次追趕優化。
艾米胡德 - 首席財務官
我只想補充一點,布倫特,我想對於 Satya 的觀點,也許可以爲你劃一句話,我認爲這與上個季度我們發表了同樣的評論非常相似,那就是我們看到了有點正常的優化,而且我們看到在 Satya 所說的這些工作負載中開始了新的工作負載。而且我認爲這就是我們未來要說的話,我認爲,實際的變化只是與一年前相比有點追趕。你說得對,我們將在 H2 繼續這樣做。
Mark Moerdler -Sanford C. Bernstein & Co.-分析師
恭喜這個季度。艾米,資本支出環比和同比大幅上漲,而且未來還在增加。你能給我們點顏色嗎?是物理數據中心嗎?主要是服務器嗎?它主要由人工智能驅動嗎?我們應該如何看待它的使用壽命?然後對於 Satya 來說,你能不能給我們一些 —— 關於完整 Copilot 開發堆棧的全面可用性情況?客戶和合作夥伴建立 Copilots 需要多長時間?
艾米胡德 -首席財務官
我爲什麼不從資本支出問題開始,Satya,然後我會把它交給你。馬克,實際上,首先,無論是在第四季度還是在談到第一季度,加速確實相當廣泛。它兩者兼而有之 —— 無論是數據中心還是物理基礎再加上 CPU、GPU 和網絡設備,從廣義上而不是狹義上來看待它。因此,這是整體容量加速的總體增加。
而且我認爲,如果你回顧一下23財年,你也不會看到正常的節奏,我想說的是,容量增加,即使是普通的Azure工作負載。因此,你會看到兩種加速,即普通的 Azure 工作負載以及一些 AI 工作負載,是部分原因。因此,這就是爲什麼我經常評論說,這既是商業雲的整體需求,也是人工智能能力的建設。兩者兼而有之。
薩蒂亞·納德拉 -首席執行官
是的。而且我認爲,從角度來看,我認爲考慮一下總是件好事,對吧,我們有什麼,1110億美元的商業雲業務同比增長22%。然後你的資本支出增長了,差不多是同樣的數字,分別爲23%、24%。因此,從某種意義上說,推動新增長的是替代資本加上一些新資本。所以我想,這就是比例。我們對這種整體增長率結構以及它如何轉化爲我們未來的TAM機會感到滿意。
然後關於所有這些如何有效啓動項目的另一個問題,Copilot 堆棧現已在 Azure 上線。因此,我們擁有所有東西,包括你可以使用的 Azure AI 工具鏈、Azure OpenAI,甚至你可以使用 Llama 和 Hugging Face 模型中的開放模型。你擁有所有的 Fabric 和我們所有的運營數據存儲,這是圍繞生成式 AI 最有用的模式之一,比如所謂的檢索增強生成,也就是說,你獲取數據存儲中的數據,在提示中使用它來生成完成內容、摘要,以及你擁有什麼。所以這是我們經常看到的東西,Copilots 從根本上講就是精心策劃的。因此,我們有這些服務可用。
令人着迷的是,當你使用像 Power Virtual Agent 這樣的東西時,你就有了低代碼、無代碼的工具來有效地構建這些 AI 產品或像我們構建的那樣成熟的 Copilots。所有底層原語都在 Azure 上可用。該工具鏈可在Azure上使用,客戶部署工具鏈的速度以及ISV能夠構建它們的速度令人印象深刻。
Kasthuri Rangan -高盛-分析師
恭喜本季度。如果可以的話,我只是想聽聽你的想法,將討論從 COGS 和 CapEx 轉移到更多的收入前景上。看來Azure的增長率肯定開始穩定下來,人工智能對Azure的創造性貢獻逐季度明顯改善,從更廣泛的意義上講,優化也開始穩定下來。
這與該公司對未來幾個季度Azure增長率的展望將走向何方?我們是否已經觸底反彈,由於我們討論的趨勢,我們可能會開始看到一些加速?而且,如果我們以微軟雲的超集爲例,當你爲Copilot設定新的定價時,看來TAM正在以相當大的方式開放。因此,當你從更廣泛的角度來看,薩蒂亞和艾米提到的21%、22%的增長率時,前景會怎樣?我們能否過於樂觀地抱有未來幾年某種加速的希望?或者你如何看待收入前景?
薩蒂亞·納德拉 -首席執行官
當然。Kash,謝謝你的提問。所以也許我會開始然後,艾米,你可以補充一點,因爲我想 —— 我們確實在考慮這裏的長期 TAM 是多少,對吧?我的意思是 —— 你聽過我談論這個佔國內生產總值的百分比,科技支出將是多少?比方說,如果你相信,GDP的5%將達到GDP的10%,那麼由於人工智能浪潮,這種情況可能會加速。那麼問題是其中有多少流向了我們商業雲的各個部分,然後我們在每個層面的競爭力如何,對吧?
因此,如果你把它分解一下,你有點談微軟 365,我們如何將這款 Copilot 視爲第三支柱,對吧?我們有創作工具。然後,我們擁有了所有的通信和協作服務,我們認爲 AI Copilot 是第三個支柱。因此,我們對此感到興奮。艾米首先談到了我們想如何發佈它,也是本次預覽的一部分。然後在下一財年的下半年,我們將開始從中獲得一些實際收入信號。所以我們很期待。
但是從長遠來看,我們將其視爲第三個支柱,就像我們過去想過的(比如)Teams 或 SharePoint 之類的東西,或者你有什麼。那麼 Azure,我的看法是,不管怎樣,你仍然處於雲遷移的第 2 局或第 3 局,特別是如果你看的話,對吧,無論是行業向雲遷移、細分市場遷移到雲端還是國家對雲的採用,對吧?因此,雲遷移本身仍處於初期階段。所以那裏還有很多。
除此之外,還有一個由人工智能驅動一系列新工作負載的全新世界。因此,我們再想一遍,這與 TAM 的機會相比相當廣泛,我們會試一試。但與此同時,我們是一個價值1110億美元的商用雲,在20年代發展壯大,因此,我們確實達到了大量定律。但話雖如此,我們確實認爲這是一項可以持續保持高增長的業務,這讓我們感到興奮。
艾米胡德 -首席財務官
我想唯一要補充的是,卡什,我想在某些方面,我們真正指向的是這裏有一個過程。我們看到需求信號相當強烈。它仍然很強大。我對我們發佈的所有產品公告感到非常興奮。我很高興他們轉到付費預覽版然後轉到 GA。就潛在市場而言,它們絕對是廣闊的。就我經常談論的首席信息官或首席財務官如何看待這項投資而言,他們達到新的預算池幾乎就是我經常談論的方式。因此,機會越來越大。
如你所知,我們專注於解決這個問題。然後收入就是結果。但這確實需要——需求信號需要資本支出,然後創造機會。這就是爲什麼我認爲,在某些方面,我們多花一點時間談論其中一些投資,是因爲它是需求信號。
Karl Keirstead -瑞銀-分析師
好吧,太棒了。艾米,如果我能稍微雙擊一下圍繞 M365 Copilot 的激動人心的消息,因爲在線上的每個人都希望將這個機會分層到我們的模型中,我只想聽聽你的看法。你能給我們提供護欄來讓我們保持排隊嗎?辦公板塊存在一定程度的毛利率壓力嗎?換句話說,這是一款成本相當密集的新產品,我們應該記住嗎?而且,從某種意義上說,你需要 Azure AD,也許還有其他一些網絡安全產品,它能否與 Azure 相提並論?因此,在今晚和接下來的幾周裏,稍微塗一點顏色可能會對每個人的建模練習有所幫助。
艾米胡德 -首席財務官
謝謝,卡爾。我想也許我會先從我們發佈新產品時的流程開始。而且我完全理解,需求信號、客戶的反應,以及我們即將進入付費預覽版的請求,也讓我們感到興奮。這一切都令人鼓舞。如你所知,我們已經 —— 上週,我們宣佈了定價,然後我們將繼續完成付費預覽流程,以獲得良好的反饋。然後我們將宣佈正式上市日期,然後我們將進入正式發佈日期。當然,這樣我們就能出售它然後確認收入。
這就是爲什麼我繼續說我和其他所有人一樣對此感到興奮,而且應該更加 H2 的權重。我認爲,我們已經給了你一些規模調整的機會。而且我想我會用到所有這些。但我確實認爲這實際上與節奏有關。當然,我們仍然需要對我們的 Security Copilot 和一些 Dynamics 工作負載進行定價和發佈。我們將繼續爲此努力。
當然,我認爲人們經常忽略的一件事是,當你回過頭來談談 Azure 時,Satya 簡短地提到了這一點,我認爲從很多方面來說,這些人工智能產品中有很多都使用 Azure,因爲構建應用程序所需的不僅僅是人工智能解決方案服務。因此,與其說是微軟 365 的支持,不如說是任何 Copilot。就是說,當你構建這些時,它需要數據,也需要人工智能服務。因此,你會看到他們同時使用核心 Azure 和 AI Azure。我認爲這也是一個重要的細微差別。
薩蒂亞·納德拉 -首席執行官
是的。如果我能補充一下艾米所說的話,這裏的平台效應實際上完全與 Copilots 的可擴展性有關。今天,當人們在 Teams 中構建基於 Power Apps 的應用程序時,你就會看到這一點,而那些 Power Apps 恰好在 Azure 上使用 SQL DB 之類的東西。這就像經典的業務線擴展。所以你會看到同樣的東西。當我有 Copilot 插件時,那個插件會使用 Azure AI、Azure 儀表、Azure 數據源、Azure 語義搜索。因此,很明顯,你不僅會看到身份或安全層的突破,還會在 Azure 的核心 PaaS 服務以及 M365 中的 Copilot 可擴展性中看到。
馬克·墨菲 -摩根大通-分析師
Satya,現在有太多的證據表明 GitHub Copilot 正在將開發者的生產力提高了 40% 到 50% 或更多,從而產生了更高質量的代碼。你是否設想 Microsoft 365 Copilots、Security Copilot 或 Sales Copilot 的工作效率會有類似的提升?換句話說,能否將房屋中的每個房間都改造到類似的程度,以至於整個堆棧中的價值主張都得到了相當高的提升?
薩蒂亞·納德拉 -首席執行官
是的。賈德森·阿爾索夫(Judson Althoff)會很高興你用他的比喻用人工智能改造房子的每個房間,因爲你說得絕對正確。我的意思是這就是我們所看到的機會。我想你還指的是現在有很好的經驗證據和數據圍繞 GitHub Copilot 以及圍繞它的生產率統計數據。我們正在爲 M365 Copilot 積極研究這個問題,也爲諸如 Sales Copilot 或 Service Copilot 等基於角色的角色開發這個問題。我們看到這些業務流程具有非常高的生產率提升。所以是的,在這一年中,我們將擁有所有這些證據。
而且我認爲,歸根結底,正如艾米所提到的那樣,每位首席財務官和首席信息官也會看看這個問題。我確實第一次認爲 —— 或者更確切地說,我確實認爲人們會考慮如何用這些 Copilots 來補充運營支出支出,以提高效率,坦率地說,甚至減輕運營支出和員工等的工作負擔和繁瑣工作。因此,我想你會看到所有這些都轉化爲生產率統計數據,我們期待着這些數據公佈。
亞歷山大·祖金 -沃爾夫研究-分析師
我想可能只是一個多方參與者。你曾幾次提到,隨着你在 Azure 上看到的人工智能工作負載採用情況,與前幾代產品相比,它看起來可能與增量份額增長的角度略有不同。你能再詳細說明一下嗎?這應該如何推動 Azure 的消費,尤其是在我們度過這一年之際?而且,你是否看到這樣的場景:無論是優化逆風,再加上人工智能的貢獻,再加上你在工作負載周圍看到的這種增量順風,確實推動了 Azure 的重新加速,尤其是在下半場你將開始看到其中一些事情開始出現的時候?
薩蒂亞·納德拉 -首席執行官
是的。我的意思是,我們既看到又興奮的是兩個新的工作負載。我的意思是,如果你想一想 Azure,這些年來,我們已經從後面發展了 Azure。在這些新工作負載方面,我們在 ****2 中處於領先地位。因此,舉例來說,我們看到了新的徽標,客戶可能已經在雲端使用了大部分工作,或者是第一次開始使用 Azure 來處理一些新的 AI 工作負載。
我們甚至還有使用過多個雲的客戶,他們將其用於一類工作負載,當它們在數據和人工智能中傳輸時,他們也會開始新的項目,而他們使用的是其他雲。因此,我想你會看到更多的股票收益,更多的徽標收益,甚至減少我們的CAC。因此,這些都是槓桿點的東西。但與此同時,在任何這些事情上,我們都不再是一家小企業了。我們意義重大 —— 我們的規模很大。所以,是的,我們慶祝。這就是爲什麼我們甚至在本季度爲你提供1點的知名度,下個季度有幾個百分點的曝光度。這些是物質數字。
所以我認爲這將是可以追蹤的。而且我想艾米之所以提到它,是因爲我們想要 —— 即使是 AI 也有 2 個部分,對吧?還有我們與 OpenAI 合作的模型本身。這有點像一種計算支出。另一個更受收入驅動,對,那就是我們將追蹤推理成本與收入和需求的關係。而且你已經看到這兩者都在發揮作用了。
Kirk Materne -Evercore ISI-分析師
Satya,我想知道你能否稍微擴展一下你對數據平台的評論。我想在上個季度左右的時間裏,我們聽說了很多關於如果你沒有數據策略,就很難制定人工智能策略。我猜你能否談談客戶在制定更周到的數據策略的旅程中現在所處的位置?就他們採用人工智能服務的能力而言,這意味着什麼?這意味着在真正利用所有的人工智能服務之前,他們必須先解決數據問題嗎?或者我們應該如何看待這種並置?
薩蒂亞·納德拉 -首席執行官
是的,當然。謝謝你的提問。是的,絕對可以。我認爲,特別是將你的數據放在雲端是你如何利用這些新的人工智能推理引擎來補充(我稱之爲數據庫)的關鍵,因爲這些人工智能引擎不是數據庫,但它們可以推理你的數據,幫助你獲得更多的見解、更多的完成、更多的預測、更多的摘要,以及你擁有的東西。
因此,當我們說 Copilot 設計模式時,這就是設計模式的全部內容。即使在上個季度,也可能最令人興奮的是,通過微軟Fabric,尤其是對於分析工作負載,我們將計算、存儲、治理與極具顛覆性的商業模式融爲一體。
我的意思是給你一個味道,對吧,這樣你的數據就在 Azure 數據湖裏了。你可以把 SQL Compute 引入其中。你可以把 Spark 帶到它身上。你可以把 Azure AI 或 Azure OpenAI 帶進去,對吧?所以事實是,你的存儲空間與所有這些計算計量器是分開的,而且它們都是可以互換的,對吧?因此,您不必單獨購買每個。這就是顛覆性的商業模式。所以我覺得我們很好 —— 微軟在我們的數據架構圍繞數據佈局商業模式的方式以及人們計劃如何將數據用於人工智能服務方面處於有利地位。所以我所說的整理好你的數據資產就是這個意思。而且它只是無法按順序排列數據資產,但你必須對其進行結構化,這樣你才能靈活地使用數據和計算組合,這對於這個新時代來說是有意義的。
佈雷特·艾弗森 - 投資者關係總經理
謝謝,柯克。今天財報電話會議的問答部分到此結束。感謝您今天加入我們,我們期待儘快與大家交談。
(提示:此筆錄是通過錄音轉換的,我們會盡力而爲,但不能完全保證轉換的準確性,僅供參考。)