微軟 (MSFT) 2027 財年第一季法說會：Azure 成長達 48%

重點摘要

• 微軟公布 2027 財年第一季營收達 923 億美元，年增 19%，而營業利益成長 21%，營業利益率達 50%。
• 微軟雲端營收成長 30%至 639 億美元，主要受 Azure 48% 的成長所帶動。管理層將此亮眼表現歸因於 Foundry、更強勁的 CPU 貨幣化效益，以及基礎設施效率提升。
• Microsoft Foundry 營收較去年同期翻增逾兩倍。該平台擁有超過 120,000 名客戶，而 Foundry 上開源模型的營收則成長 10 倍。
• 資本支出總計達 452 億美元，包含 74 億美元的融資租賃。自由現金流為 186 億美元，反映出基礎設施支出的增加。
• 管理層預估 2027 財年第二季營收將介於 960 億美元至 971 億美元，相當於成長 18% 至 19%。預計 Azure 營收將成長 49% 至 50%（按固定匯率計算）。
• AI 需求持續超過可用供給。部分第三方 GPU 產能交付延後至 2027 財年下半年，管理層預計第二季資本支出將超過 500 億美元。

主要財務結果

業務與營運表現

Azure、Foundry 與 AI 基礎設施

Azure 營收成長 48%，得益於 Foundry 的支援及現有 CPU 產能變現能力的提升。微軟表示，其 CPU 與 GPU 叢集的工程進步使公司能在不增加相應基礎設施成本的情況下，滿足額外的需求。

Foundry 營收成長逾兩倍，產能配給增加與每 token 營收提升共同推動了成長。已有超過 120,000 名客戶 目前正在使用 Foundry。建構多模型代理（agentic）解決方案的客戶數量成長了 5 倍，而該平台上開源模型的營收則成長了 10 倍。

微軟在本季度新增了 跨越五大洲的 24 座資料中心。該公司還將 Copilot 工作負載的吞吐量提升了超過 50%（較上季）。管理層表示，需求仍高於可用產能。

Copilot 與 Microsoft 365

Microsoft 365 商業雲端營收成長 17%，或 按固定匯率計算成長 18%。 扣除上年同期營收認列效益後，成長率為 18%，或 按固定匯率計算成長 19%。 業績主要受惠於 GitHub Copilot 的採用率與使用量提升，但部分被 Microsoft 365 E3 及獨立產品銷售執行力較弱所抵銷。

Microsoft 365 商業付費席位成長 5%。 每使用者平均收入得益於 Microsoft 365 Copilot、E5 和 E7，以及按用量計費的 GitHub Copilot 營收。

Copilot 日活躍使用者成長近 50%（季增），且成長超過 5 倍（年增）。 擁有超過 50,000 個 Copilot 席位 的客戶數量成長超過 8 倍，而積極消耗按用量計費之 Copilot 點數的客戶數量成長超過 75%（當季）。

GitHub Agent 生成的 Pull Request 成長 6 倍（六個月內），且佔該平台所有 Pull Request 的三分之一以上。引進按用量計費後，Agent 式 GitHub 功能的點數消耗量翻倍以上。

資料、安全性與企業 Agent

Microsoft Fabric 擁有 44,000 名付費客戶，成長超過 50%（年增）。超過 19,000 名客戶 同時使用 Foundry 和 Fabric，而近 60,000 名客戶 透過 Microsoft IQ 存取情境資訊，成長 25%（季增）。

超過 5,000 萬個 Agent 已在 Agent 365 註冊，成長超過 30%（季增）。Microsoft Purview 已稽核超過 76 億次 Agent 活動，成長 5 倍（季增）。

管理層強調企業對多模型 Agent 系統的採用，並表示客戶越來越關注工作負載所有權、成本管理、可靠性與安全性，而非僅止於實驗。

裝置與消費者

扣除流量取得成本後，搜尋與廣告營收成長 12%，受惠於 LinkedIn、Edge 與 Bing 流量與費率同步成長。

Xbox 營收以及 Xbox 內容與服務營收各自下滑 2%。第三方內容與 Xbox Game Pass 營收減少，部分被第一方內容的成長所抵銷。

Windows OEM 與裝置營收下降 22%。Windows OEM 營收下滑 27%，或 按固定匯率計算為 28%，主因去年同期受益於 Windows 10 停止支援帶動的高基期比較、通路庫存偏高以及 PC 需求疲軟所致。

管理層財測指引

管理層預計，Microsoft 365 商業雲端的成長主要由每使用者平均收入 (ARPU) 提升與席位數成長所推動。不含流量取得成本的搜尋與廣告營收預估將以低雙位數率成長。

Windows OEM 與裝置營收預計將下滑 30% 中段範圍。管理層預期通路庫存偏高、PC 需求疲軟以及 Windows 10 高基期比較，將在整個 2027 財年持續影響業務。

微軟預計日曆年資本支出約為 1,700 億美元，此為第三方產能交付延遲後的預估。由於 CPU、GPU、記憶體、儲存設備以及延遲的第三方產能，預計資本支出將在 2027 財年下半年加速。

風險與觀察重點

• 產能限制： 客戶對 Azure 與 AI 基礎設施的需求持續超出可用供應。
• 交付延遲： 原預計於第二季交付的部分第三方 GPU 即服務 (GPU-as-a-Service) 產能已推遲至 2027 財年下半年。
• 成長波動性： Azure 成長可能會隨著工程效率提升、產能擴充、Token 定價與模型組合而有所波動。
• 雲端毛利率組合： 儘管產品層面的毛利率有所改善，但隨著 Azure 占營收比重增加，微軟雲端 (Microsoft Cloud) 的毛利率預計將會下滑。
• 商用業務基期比較： 簽約金額下降 12%，部分原因在於去年同期包含較大的 Azure 承諾訂單。管理層預計這些合約簽署時程將繼續帶來季度波動。
• Windows 業務壓力： 庫存水位偏高、PC 需求疲弱以及去年同期基期偏高，預計將對 Windows OEM 與裝置業務營收造成壓力。
• 資本支出強度： 較高的基礎設施投資使自由現金流減少，儘管管理層預計微軟在 2027 財年仍將保持自由現金流正數。

分析師問答重點

AI 基礎設施回報： Satya Nadella 表示，回報應來自基礎設施效率提升，以及 Azure、Fabric、Foundry、Copilot、Agent 365 和安全產品的變現能力。微軟將這些產品視為由可替代產能池支持的相連技術堆疊進行管理。

Azure 成長動能： Amy Hood 將第二財季 Azure 展望歸因於 CPU 和 GPU 效率持續提升。這些改善必須部分抵銷第三方產能延遲的影響，同時 Token 定價的預測性仍然較低。

企業 AI 採用情況： Nadella 強調企業正在各個營運流程中擴大部署代理系統 (Agentic Systems)。他將廣泛的企業採用描述為一項長期機遇，而不是依賴少數客戶購買大量產能的成長。

模型策略： 微軟預計客戶將根據品質、速度、成本和工作負載需求，在前沿模型、開放權重模型與微軟自身的 MAI 模型之間動態切換。Foundry 的設計宗旨在於支援這種多模型策略。

Copilot 變現能力： 管理層預計按用量計費的採用方式在軟體開發領域進展更快，因為該領域客戶早已熟悉隨用隨付 (Pay-as-you-go) 模式。在程式寫作以外的領域，採用進度可能會較慢，並需要調整微軟的銷售策略。

融資策略： 微軟表示，當條件具吸引力時，公司具有靈活運用租賃、債券市場及其他融資管道的彈性。管理層對資本支出的回報表達信心，並預期公司在 2027 財年將繼續保持自由現金流正數。

法說會完整逐字稿

完整財報電話會議逐字稿

管理層陳述

Operator

Greetings, and welcome to the Microsoft Fiscal Year 2027 First Quarter Earnings Conference Call. [Operator Instructions] As a reminder, this conference is being recorded. It is now my pleasure to introduce Jonathan Neilson, Vice President of Investor Relations.

Jonathan Neilson

Good afternoon, and thank you for joining us today. On the call with me are Satya Nadella, Chairman and Chief Executive Officer; Amy Hood, Chief Financial Officer; Alice Jolla, Chief Accounting Officer; and Brian DeFoe, Deputy General Counsel and Corporate Secretary.

On the Microsoft Investor Relations website, you can find our earnings press release and financial summary slide deck, which is intended to supplement our prepared remarks during today's call and provides the reconciliation of differences between GAAP and non-GAAP financial measures. More detailed outlook slides will be available on the Microsoft Investor Relations website when we provide outlook commentary on today's call.

On this call, we will discuss certain non-GAAP items. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the measures of financial performance prepared in accordance with GAAP. They are included as additional clarifying items to aid investors in further understanding the company's first quarter performance in addition to the impact these items and events have on the financial results. All growth comparisons we make on the call today relate to the corresponding period of last year, unless otherwise noted. We will also provide growth rates in constant currency when available as a framework for assessing how our underlying business performed, excluding the effect of foreign currency rate fluctuations. Where growth rates are the same in constant currency, we will refer to the growth rate only.

We will post our prepared remarks to our website immediately following the call until the complete transcript is available. Today's call is being webcast live and recorded. If you ask a question, it will be included in our live transmission, in the transcript and in any future use of the recording. You can replay the call and view the transcript on the Microsoft Investor Relations website.

During this call, we will be making forward-looking statements, which are predictions, projections or other statements about future events. These statements are based on current expectations and assumptions that are subject to risks and uncertainties. Actual results could materially differ because of factors discussed in today's earnings press release, in the comments made during this conference call and in the Risk Factors section of our Form 10-K, Forms 10-Q and other reports and filings with the Securities and Exchange Commission. We do not undertake any duty to update any forward-looking statements.

And with that, I'll turn the call over to Satya.

Satya Nadella

Thank you very much, Jonathan. It was a fast start to our fiscal year. Microsoft Cloud revenue surpassed $63 billion with growth accelerating to 30% year-over-year. We are focused on 3 things: designing AI to empower people, ensuring every organization has sovereignty over its own learning and building trust with controls that ensure agent safety and security.

Now let's talk about how we are making progress on those goals as we build the new tech stack, starting with Copilot. We announced our biggest update to Copilot to date this quarter, bringing together Chat, Cowork, Autopilot and code into one unified experience. It's one product experience across commercial and consumer and comes with all of Office built in. We think of Copilot as the new OS for work. Customers are increasingly turning to Copilot to get real work done. Automated tasks has nearly doubled since July. Daily users are up nearly 50% quarter-over-quarter and over 5x year-over-year. User satisfaction improved nearly 20% quarter-over-quarter to another all-time high. And 90% of Copilot queries use Auto Mode, which dynamically routes tasks across models optimizing for quality, speed and cost. These improvements are translating into larger purchases.

The number of customers with more than 50,000 Copilot seats increased over 8x year-over-year, including Capgemini, HCL Tech, Hitachi Group, Truist Financial and U.K. Revenue and Customs Department. And just last week, Volkswagen announced plans to deploy Copilot to more than 330,000 employees, one of the largest deployments to date in Europe. We're also seeing strong momentum with E7, which brings together Copilot, E5, Entra and Agent365. Thousands of customers in every industry have purchased the suite to date, including Amadeus, BlackRock, Fiserv and New South Wales Health Department and ZEISS. Our business model is expanding from per seat subscriptions to include consumption, expanding our TAM and ARPU. The subscription brings increasingly capable everyday intelligence to every user.

Typically, IT funds this, consolidating frontier advances for everyone across the organization. And as agents take on higher-value work, consumption opens up business funded demand with spending tied directly to the value these agents deliver. The number of Copilot customers actively consuming credits through usage-based billing grew over 75% over the quarter. When it comes to software development, all major coding agents have shown up to work on GitHub. Agent-generated PRs have increased 6x over the past 6 months and agents now open more than 1/3 of all PRs on the platform. We are very hard at work on reliability as agentic activity on GitHub sores. At GitHub Universe this morning, we shared how we are expanding capacity and rebuilding the core Git architecture for the Agentic wave.

Also at Universe, we announced broad availability of Copilot Fusion, which is all about bringing multi-model orchestration to software development. It delivers frontier level quality up to 40% faster and at up to 77% lower cost. Credit consumption from agentic features on GitHub has more than doubled since usage-based billing went into effect. And we're also helping developers secure their code and turn AI-generated code into high-quality software. GitHub Advanced Security revenue increased over 50% year-over-year as customers use its AI capabilities to scan entire repos and fix vulnerabilities in real time.

In the business application space, we are extending this vision of Copilot as the new OS for work, bringing the business logic and capabilities of Dynamics 365 directly into Copilot and helping every organization stand up their own infinite SaaS factory. This quarter, we introduced 30 new Copilot skills across Dynamics 365 which enables customers to access CRM and ERP capabilities directly in the flow of work. In recruiting, more than 10 million LinkedIn members use our LinkedIn AI-powered job search daily and 25,000 customers are using our agentic hiring solutions. Recruiters using hiring Assistant are finding interview quality applicants 33% faster while reviewing 83% fewer profiles to find qualified match. In health care, we automated 30 million patient encounters this quarter, up 70% year-over-year, helping clinicians spend less time on administrative work and more time with patients.

10 providers, including Advocate Health, Mass General Brigham, Mercy, Intermountain Health and others have used our solutions to document over 1 million encounters each since the beginning of the calendar year. And in science, our FE teams are working with customers to use discovery to accelerate scientific progress. A great example of Saint-Gobain, which used Discovery to accelerate the development of low-carbon construction materials. Underneath our first-party agentic experience is a common platform. It starts with foundry, which is becoming an increasingly important driver of our growth.

Foundry helps organizations build learning loops grounded in their business context and deploy agents safely at scale. We now have over 120,000 foundry customers with revenue more than tripling year-over-year. Foundry's model choice and feature set, coupled with its deep integration across our stack is driving differentiation. Azure OpenAI directly benefited in the last quarter with big advances in OpenAI models. And when you couple this with our model choice built into foundry, customers are able to build solutions optimizing across quality, cost and performance. In fact, the number of customers building agentic solutions with multiple models increased 5x year-over-year and revenue from open source models on foundry increased 10x.

We also continue to make rapid progress with our first-party models. Our goal is to advance the cost-to- outcome frontier, which means delivering capabilities comparable to leading models within 3 to 6 months of their release at a fraction of the training cost, thereby allowing us to transfer those cost benefits to customers. And you see this in our products today. MAI Cyber now powers over 40% of the scans in our Agentic M-Code scanner at 18% lower cost per scan. MAI Transcribe is the most accurate and cheapest transcription model in the world, supporting Dragon Copilots multilingual workflow. MAI Code Flash has 3 million users in GitHub Copilot last month alone, helping developers get more out of their AI credits.

Microsoft Decision One is our new model for structured decision-making, outperforming both LLMs and other decision models in latency and quality. Over 4,000 customers, including Atos Group, Equinor and RBI have already used it in the first month since its release. And we recently completed pretraining MAIbase 2, which outperforms other Open weight models we tested with 4 to 12x greater training compute efficiency. This base model will be used in the upcoming MAI models across thinking, code and cyber. Beyond models, we are making the harness behind our own Copilot experience available to customers in foundry. It gives customers a Microsoft managed way to build agents that reason, use tools, complete complex long-running work while preserving their choice of model. Another critical layer is data. We now have 44,000 paid fabric customers, up more than 50% year-over-year. We are bringing Foundry and Fabric closer together so you can build your own agents right next to data.

Over 19,000 customers now use Foundry and Fabric as enterprises connect and operate agents over real-time operational, analytical and unstructured data. Customers are also rapidly deploying our AI optimized databases, including PostgreSQL, SQL DB, Hyperscale, Cosmos DB to give agents fast, secure access to the data and context they need. PostgreSQL growth accelerated for the fourth consecutive quarter, and the number of PostgreSQL customers also using Foundry accelerated to 90% year-over-year. We also have one of the most important databases for any enterprise, which is the knowledge underneath Microsoft 365 spanning people, their relationships, documents, e-mails, meetings, chats, projects and other artifacts. Work IQ makes this context available to every Agentic workload.

And with Microsoft IQ, we are bringing together Work IQ, Fabric IQ and Foundry IQ as a unified context for Agentic systems. Nearly 60,000 customers are accessing context across Microsoft IQ, up 25% quarter-over-quarter. As enterprises deploy more agents, they also need to govern them at scale. With Agent 365, we provide a platform for AI observability, enabling customers to manage, secure and optimize the performance and cost of their agents. Over 50 million agents are now in the registry, up over 30% quarter-over-quarter. And finally, as agents gain greater access to enterprise data and systems, security becomes even more critical. Our approach is to separate intelligence from authority, enforcing identity, permissions, monitoring and containment outside the model itself.

Last week, we expanded perception with new capabilities to help customers secure and contain agentic insiders, including expanded agent discovery across local and cloud environments, dynamic permissions that enforce least privileged access for each task and continuous risk assessment. We also introduced Teams of Guardian agents that continuously monitor agent activity to help prevent unsafe actions before they occur. And we are seeing encouraging feedback on perception overall from preview customers, including KPMG, Nationwide Building Society, Northern Trust, Stellantis.

More broadly, we are helping customers secure and govern AI use across the enterprise. Customers have used Microsoft Purview to audit over 7.6 billion agent activities to date, up 5x quarter-over-quarter. Underlying everything I've talked about so far is our infrastructure. We are building against a growing book of business with a fungible fleet that allows us to dynamically allocate capacity to the highest value opportunities across compute data, foundry and Copilot. Accelerating demand led to us adding 24 new data centers across 5 continents this quarter. And we are bringing capacity online faster, reducing doctor lifetimes by about 20% quarter-over-quarter for new GB300s in our biggest regions, which make up the majority of the GPU deployments.

At the same time, we continue to get more from the infrastructure we already have by optimizing across the data center design, silicon systems, software and models. For example, we increased the throughput for Copilot workloads by over 50% quarter-over-quarter. We continue to scale our fleet with the latest innovations from NVIDIA AMD alongside our own Maia systems. We have docked our first NVIDIA Vera Rubin GPUs and are very excited about it. Maia 200 is already delivering up to 1.7x more tokens per watt across the AI experiences in Teams and Copilot, and Maia 300 will drive further gains, delivering 40% more tokens per watt compared to the leading GPU-based systems. Our growth extends beyond GPUs. We continue to see strong adoption of our cloud-native cobalt CPUs, improving price performance for general-purpose cloud workloads. All up, Azure growth was broad-based across both enterprises and small and medium business segments and spanning both core cloud services and AI infrastructure.

Finally, let me turn to devices and consumer. In Windows, we are executing on our vision to bring hybrid intelligence to every desk and every home, making every PC the secure agent box. As more capable models run locally, we see an opportunity to make more intelligence effectively unmetered. We are working with the broader hardware ecosystem to bring these capabilities to a new generation of PCs across AMD's Ryzen AI 400 Series, Intel Core Ultra Series 3, Qualcomm Snapdragon X2 series. And earlier this month, we also announced new PCs powered by NVIDIA's RTX Spark and DGX Station for Windows.

With these new devices, you can run last year's frontier models on your laptop and last quarter's model at your desk. We are bringing together Windows and Agent 365, so agents can work with secure boundaries on device. We introduced Microsoft Execution Containers, a policy-driven execution layer that governs and contains agents across Windows and other platforms integrated with Agent 365 for governance and observability. Agents like OpenAI [indiscernible], Anthropic Cloud Code, Meta Muse are adopting MXC and customers like Meta are starting to deploy it across their enterprise environments. In search and advertising, Bing and Edge once again took share.

In LinkedIn, engagement continues to deepen across our more than 1.4 billion members with time spent viewing content in the feed up 15% year-over-year. And finally, in gaming, we remain focused on building great games and reaching players wherever they choose to play across console, PC, mobile and cloud. Minecraft delivered a record quarter, reaching all-time highs in both engagement and revenue, while World of Warcraft had its largest beta in franchise history. We entered the holiday season with one of our strongest first- and third-party lineups in years, including Modern Warfare 4, which launched last week to the best reviews for a Call of Duty game in more than a decade; and Grand Theft Auto 6, which is coming to Xbox next month.

In closing, based on the demand we see, the strength of our products and the efficiency we are driving across the stack, I've never been more confident in the long-term returns for our investments. With that, let me turn it over to Amy.

Amy Hood

Thank you, Satya, and good afternoon, everyone. Our results exceeded expectations across revenue, operating income and earnings per share, driven by strong demand across the Microsoft Cloud. This quarter, revenue was $92.3 billion, up 19%. Gross margin dollars increased 17% and gross margin percentage was 68%. Operating income increased 21% and 22% in constant currency. Earnings per share was $4.89, an increase of 18% and 19% in constant currency when adjusted for the impact for our investment in OpenAI. And FX was roughly in line with guidance. Operating expenses increased 6%, driven by continued investments in R&D compute capacity and talent. Operating margins increased slightly year-over-year to 50%, driven by strong revenue growth, platform efficiency gains and focused investments across our portfolio, partially offset by sales mix shift to Azure.

When adjusted for the impact for our investments in OpenAI, other income and expense was negative $234 million, slightly lower than expected. Capital expenditures were $45.2 billion as some third-party capacity deliveries we expected in Q1 were delayed. Roughly 3/4 of our CapEx was for short-lived assets, primarily CPUs and GPUs, including higher memory and storage costs as we continue to invest in the infrastructure required for our customers to build and scale AI applications. The remaining spend was for long-lived assets. This quarter, finance leases were $7.4 billion. As a reminder, we recognize the full principal value of finance leases and CapEx at the time of lease commencement. And cash paid for PP&E was $39.4 billion. Cash flow from operations was $58 billion, up 29%, driven by strong cloud billings and collections.

And free cash flow was $18.6 billion, reflecting higher capital expenditures. And finally, we returned $10.2 billion to shareholders through dividends and share repurchases. Now to our segment results reported under the updated segment structure announced in September. Revenue from Agents and Infra was $76.8 billion and grew 25%, reflecting strength across the connected layers of our platform. Commercial bookings decreased 12% and 11% in constant currency, driven by the impact from large Azure commitments in the prior year, partially offset by healthy growth in our commercial sales motions, including a large Azure commitment this quarter.

Commercial remaining performance obligation grew 73% to $677 million, with a smaller sequential decline relative to historical seasonality due to the large Azure commitment this quarter. Our RPO has a weighted average duration of 2.3 years and roughly 30% will be recognized in revenue in the next 12 months, up 29% year-over-year. The remaining portion recognized beyond the next 12 months increased 98%. Now to Microsoft Cloud. Revenue was $63.9 billion and growth accelerated to 30% and 31% in constant currency with sequential dollars added nearly doubling year-over-year, reflecting strong demand across Azure and M365 Commercial Cloud.

Azure revenue was ahead of expectations and increased 48%, even with the 3P capacity delays noted earlier. driven by foundry and improved CPU monetization. Foundry revenue more than tripled year-over-year with upside driven by efficiency gains across our GPU fleet that allowed us to allocate additional capacity to customers as well as higher revenue per token that we benefited from in the quarter. Across our CPU fleet, engineering work enabled us to identify and monetize underutilized capacity this quarter, helping us serve more of the growing demand with our existing capacity. The timing of engineering efficiencies like these as well as 3P GPU lease deliveries, our own capacity build-outs and ARPU changes from model mix can create quarterly variability in the year-over-year growth rate.

M365 Commercial Cloud revenue increased 18% and 19% in constant currency when adjusted for the prior year comparable that benefited from 1 point of in-period revenue recognition. On a reported basis, revenue growth was 17% and 18% in constant currency. Results were ahead of expectations, driven by stronger GitHub Copilot adoption and usage, partially offset by weaker sales execution in our M365 E3 and stand-alone SKUs. We continue to evolve our sales motions to balance those more traditional SKU per seat rhythms with the newer premium E7, M365 Copilot and usage-based productivity offerings. Year-over-year growth was driven by both ARPU and seats.

ARPU growth was led by our premium seat-based offerings, including M365 Copilot, E5 and E7, which has already reached millions of paid seats with additional contribution from usage-based offerings, primarily GitHub Copilot. And Copilot revenue growth accelerated quarter-over-quarter with continued adoption across M365, GitHub and Security. Paid M 365 commercial seats grew 5% with some impact from the weaker sales execution noted earlier. Growth was driven by installed base expansion across all customer segments, though primarily in our SMB and frontline worker offerings.

M365 Consumer Cloud revenue increased 17% and 16% in constant currency, down sequentially as we begin to lap the benefit from the price increase in the prior year. Productivity and server licensing revenue decreased 3% and 2% in constant currency, primarily driven by a decrease in transactional purchasing as we lap the benefit from product launches in the prior year, partially offset by a greater mix of contracts that carry higher in-period revenue recognition. Industry Solutions Cloud revenue increased 10% with growth in Dynamics 365 and LinkedIn Talent Solutions, though booking trends continued to moderate. And in Frontier and Support Services, revenue increased 4% and 5% in constant currency, driven by support.

Microsoft Cloud gross margin percentage declined year-over-year to 66%, driven by sales mix shift to Azure, partially offset by product level margin improvements, primarily in Azure and for this segment. Gross margin dollars increased 20% and 21% in constant currency. Operating expenses increased 10%, driven by the R&D investments noted earlier. Operating income grew 24% and 25% in constant currency, and operating margins decreased slightly year-over-year to 53% as strong revenue growth, platform efficiency gains and focused investments across our portfolio were more than offset by sales mix shift to Azure.

Now to Devices and Consumer. Revenue was $15.5 billion and declined 3%. Search and advertising revenue ex TAC increased 12% and was ahead of expectations, driven by higher volume and rate across LinkedIn, Edge and Bing. Xbox revenue decreased 2% and Xbox Content and Services revenue decreased 2% and 1% in constant currency, driven by declines in third-party content and Xbox Game Pass, partially offset by growth in first-party content. And Windows OEM and devices revenue decreased 22%. Windows OEM revenue was below expectations and decreased 27% and 28% in constant currency, driven by the Windows 10 end of support demand in the prior year, inventory drawdowns by OEM and channel partners and weaker PC market demand.

Inventory levels remain elevated. Segment gross margin dollars were relatively unchanged year-over-year and operating expenses decreased 3%, driven by Xbox, partially offset by the continued investments in R&D noted earlier. Operating income increased 2% and 3% in constant currency, and operating margins increased year-over-year to 35%, driven by lower amortization of intangible assets from the Activision acquisition, partially offset by the impact from a lower mix of Windows OEM revenue.

Now moving to the outlook for our second quarter, which unless specifically noted otherwise, is on a U.S. dollar basis. Based on current rates, we expect FX to have no meaningful impact on total revenue, COGS or operating expense growth or on revenue growth in either segment. Starting with segment guidance. We expect revenue from Agents and Infra of USD 80.1 billion to USD 80.7 billion or growth of 24% to 25%. In commercial bookings, we expect healthy growth in our commercial sales motions, though results will be impacted by the significant Azure commitments signed in the prior year. Timing related to significant Azure commitments like these will result in material volatility in bookings, making quarterly growth rates less indicative of underlying sales execution.

In Azure, we expect revenue growth of 49% to 50% in constant currency with continued efficiency gains across our CPU and GPU fleet, helping to offset some 3P GPU-as-a-Service contracts that have been delayed to H2. Customer demand continues to exceed available supply. And looking beyond Q2, year-over-year growth will continue to reflect the timing and scale of engineering efficiencies delivered in the quarter and new capacity adds as well as a strong prior year comparable that included accelerating growth in the second half. In M365 Commercial Cloud, we expect growth of approximately 19% in constant currency with FX expected to reduce reported growth by less than 1 point. We expect continued momentum across our premium per seat offerings and usage-based offerings, along with some improvement in execution across E3 and our stand-alone SKUs.

Growth will be driven primarily by ARPU with additional contribution from seats, and we continue to expect revenue growth to accelerate through the year. M365 Consumer Cloud revenue should grow in the low teens, down sequentially as we lap the price impact noted earlier. Productivity and server licensing revenue should decline in the mid- to high single digits, down sequentially due to a lower expected mix of contracts that carry higher in-period revenue recognition. Quarterly growth can vary materially based on contract mix, product launch timing and other transactional purchasing trends.

In Industry Solutions Cloud, we expect revenue growth to be in the mid- to high single digits with continued impact from the bookings trends noted earlier. And in Frontier and Support Services, we expect revenue to grow in the low to mid-single digits. Microsoft Cloud gross margin percentage should be roughly 65%, down year-over-year as continued improvement in product level margins is more than offset by sales mix shift to Azure. In Devices and Consumer, we expect revenue to be USD 15.9 billion to USD 16.4 billion.

Search and advertising revenue ex TAC growth should be in the low double digits, driven by consistent trends in rate and volume with overall search and advertising revenue expected to grow at a similar rate. And in Xbox Content & Services, we expect revenue growth to be in the mid- to high single digits, up sequentially, driven by the timing of content launches across both third and first party. With content launch patterns through the year, we expect growth to be the strongest in the second quarter with some deceleration in Q3 and further moderation in Q4.

Hardware revenue in Q2 should decline year-over-year. Windows OEM and devices revenue should decline in the mid-30s. Growth will continue to be impacted by elevated inventory levels, PC market demand and a prior year comparable that benefited from Windows 10 end of support. As in prior quarters, the range of potential outcomes remains wider than normal. We expect these trends to continue through the rest of the fiscal year. Therefore, at a total company level, revenue should be between USD 96 billion and USD 97.1 billion or growth of 18% to 19%. We expect COGS of USD 32.7 billion to USD 32.9 billion or growth of 26% to 27% and operating expense of USD 18.5 billion to USD 18.6 billion or growth of 9%, driven by continued investment in R&D compute capacity and talent. Our cost guidance across both COGS and OpEx includes an estimate for the recently announced employee voluntary exit offer.

Operating margins should be down slightly year-over-year. Excluding any impact from our investments in OpenAI, other income expense is expected to be roughly negative $300 million as interest income will be more than offset by interest expense, which includes the interest payments related to data center finance leases. And we expect our Q2 effective tax rate to be approximately 20% Next, capital expenditures. In Q2, we expect CapEx spend will be over $50 billion.

Therefore, for the calendar year, spend should be approximately $170 billion due to the 3P capacity delays noted earlier. In the second half of the fiscal year, we currently expect CapEx spend to accelerate primarily from CPUs, inclusive of higher memory and storage costs and GPUs as well as the 3P capacity deliveries that shifted to H2. And as we continue to improve the efficiencies of our infrastructure, each dollar of CapEx has the potential to support more revenue and higher returns over time. Given our strong business performance, we expect to continue to remain free cash flow positive in FY '27. To complement cash generated by the business and preserve financial flexibility, we will access additional sources of funding when we believe it is attractive to do so.

In closing, we are off to a strong start to FY '27 with accelerated growth across the Microsoft Cloud. Product improvements, along with efficiency gains across our data center infrastructure and our first-party apps and agents are increasing the value and improving the outcomes we deliver to our customers. Delivering that value to our customers positions us for durable long-term growth. With that, let's go to Q&A, Jonathan.

Jonathan Neilson

Thanks, Amy. We'll now move over to Q&A. [Operator Instructions] Operator, can you please repeat your instructions?

Operator

[Operator Instructions] And our first question comes from the line of Adam Wood with Morgan Stanley.

分析師問答

Adam Wood

Alongside lower-than-expected CapEx and those better cloud gross margins sequentially. Can I ask, as the incremental AI capacity comes online, what do you see as likely to be the more important driver of returns over the next few years, improving utilization and unit cost within Azure or your ability to monetize more layers of each workload across Fabric, Foundry and Copilot.

Satya Nadella

Thanks for the question, Adam. I'd say all of the above. But I think the way we are coming at this is we have one pool, and we want to get the pool to be as efficient and fungible, right? That's sort of the place where if I sort of think about all of the physics of how we're building out the data centers, all of the operational rigor with which we can bring up the capacity. And then, of course, how do we run the workloads that are optimized on that infrastructure. And once you do that, then it's just a function of how we allocate it by looking at the demand signal. And even there, even in our new segment reporting, I think you kind of see it, which is copilot Copilot state full database underneath it is Work IQ. That gets used in foundry, which is where people will build, let's say, a multi-agent system for supply chain that spans both unstructured and structured.

Of course, it uses a post-Cris database in Azure. And so -- and then, by the way, all the agentic work is registered in the Agent 365 and perception manages the security of it, right? So to us, at least we look at all of this as the same infrastructure. Of course, we report to you in a variety of different products. But your core question of where is the margin going to come from? Where is the leverage is going to come from? It's not going to come from any -- it's going to come from every one of them, and it compounds when we work them across.

Amy Hood

I think that's -- and Adam, I'm sorry if we missed the front half of your question. I think we at least caught the back half.

Operator

The next question comes from the line of Karl Keirstead with UBS.

Karl Keirstead

Amy and Satya, I'm wondering if you could unpack what I thought was one of the key metrics from this call, and that is the guidance for Azure growth of 49% to 50% constant currency in December. I can imagine there's a number of variables, the capacity you're putting up, the allocation to third-party customers, probably OpenAI strength. But perhaps you could comment a little bit on what some of the key drivers are given how good that number seems at least to me.

Amy Hood

Thanks, Karl, for the question. Maybe I'll start by talking a little bit about Q1, and I think that will help to think through Q2 and even going forward. And it's not unrelated really to Adam's question at some level as well. In Q1, I would say the engineering teams have really delivered very, very good work in terms of improving efficiency at the platform layer. That is not just a statement around the efficiency of GPUs. It's a statement around the efficiency of every layer, how the app utilizes the platform and how foundry utilizes the platform as well as the Azure platform itself. Those efficiencies they're sort of ground out every week and you have good ideas, a lot work, some don't, and you stay at it.

So they're not maybe as predictable in terms of how much impact we'll get in quarter. Q1, they did a very good job. And you saw some of that result in us being able to put more allocation into foundry in the quarter. That's a great thing because we're -- as I said in the call, we still have demand that exceeds supply. So where we can have our engineering teams deliver those efficiencies, we do really try to put it into foundry when we can because it's so important, as Satya talked about, into how customers broadly are building what I would call against the new stack. Secondly, and you mentioned it, token pricing will create a little bit of variability. We had higher token pricing than we expected in the quarter.

Listen, high-quality models that we're able to take advantage of and see good margins on do benefit us in the quarter, and that did happen in Q1. And I think also in that number in Q1 was the efficiencies I talked about applied not just to our GPU fleet. But I think people sort of underestimated when the example Satya gave for Adam's question, that's a GPU, CPU storage memory workload. I mean it takes all of the pieces. And so our ability to also create additional capacity within our existing fleet gave us some room to be able to convert that actually pretty quickly as well in Q1.

So in Q2, we've got those efficiency gains, which is great, and those will continue into Q2. We need to find some more, which we're counting on enable to get to that guidance that I gave because I have faith in the team's work in Q1 continuing into Q2. But we also need that work to be able to help us a little bit because we had some supply we were counting on Q2 move out into H2. And so I think -- and to your point, there's also some unknown on some token pricing through the quarter, that stuff can change. So I think I feel good in terms of the efficiency gains that we saw when we're able and when I'm able to see those and put them in, I feel good about guiding to that. But as other things are less predictable. I mean I hope that's helpful on the levers, Karl.

Operator

The next question comes from the line of Mark Moerdler with Bernstein Research.

Mark Moerdler

Congratulations on the solid quarter and the solid guidance. It's really nice to see how well you guys are executing. I'd like to get a sense on the drivers of the AI strength in Azure being from enterprise versus digitally native in general or AI native. With inferencing starting to ramp and Microsoft the go-to for enterprises, how should we think, Amy, about the mix of enterprise customer workloads within overall workloads at this point? And Satya, with the strong growth of the Azure AI platform offering, can you give us color on what's driving that? Is it, again, enterprise? Is it digitally native? Obviously, it's a mix of both. But any color that shows the ramp of that enterprise, I think, would be valuable.

Satya Nadella

Yes. Thanks for the question, Mark. Maybe I'll start and maybe you can add to it. I was even here in Europe just last week, and it was great to see the qualities of the Agentic systems, right, that are just broadly getting deployed, right? When Unilever deploys what is their automated order taking and trade coupon dispute management stuff, all as a fully agentic touchless system. Rolls-Royce deploys a system to really manage all of their maintenance or whatever their jet engines with 30,000 parts, a pretty complex supply chain, both planning, execution, inventory management system, all built on foundry Agentic systems. RBI, which is an Austrian bank, showed me 20-plus business processes end-to-end. And they were talking about like whether it's in for credit or what have you, how they are able to now do that so much more optimally, right?

So the breadth, the quality, their ability -- oh, by the way, the multimodel nature of it, right? They look -- they start with a frontier model. Many of them, in fact, the Unilever one, they just dropped an MAI model trained using our traces. So even the degree of sophistication of what I think of as model optimization, workload optimization, token optimization was just great to see. So the breadth is starting.

Finally, it does feel like the enterprise workloads. They feel like to me, like the database applications enterprises built in the past that I grew up with is happening now when it comes to AI. And in fact, if anything, some of the shiny object stuff is waning, right, which is not about the next big thing. They're really more about, wow, can I build the system? Can I own the weights? Can I manage my costs? Can I have reliability? What about security? And so in that sense, the enterprise breadth motion is starting. But like everything else, the enterprise stuff is not like a quarter-over-quarter. It's a decade-long thing, and that's what I've been waiting for as opposed to like 4 customers who buy a lot of capacity from you and you can show a few quarters of growth. And that's not a business as far as I'm concerned.

So I want the breadth. We are well positioned on the breadth. And we have large customers who want to buy from us, and we're open for business with it. And as long as the pricing is right, we may sell them some. If not, we will be patient about building the breadth of business.

Operator

The next question comes from the line of Gabriela Borges with Goldman Sachs.

Gabriela Borges

Satya, I want to stay on this topic of breadth because you had a comment in the prepared remarks talking about how MAI can now be comparable to leading models within 3 to 6 months of their release. At the same time, you have OpenAI at 11% of revenue in the quarter. So maybe just take a step back and give us your latest thinking on how you think token mix and token value is going to evolve between the frontier MAI and maybe what some of your more sophisticated enterprise customers are doing from a proprietary AI strategy standpoint?

Satya Nadella

Yes. So I think -- in fact, I would say that you should think of 3 things perhaps as in the toolbox for any workload. The first is a new model drops and it's got some great performance and you want -- you can eval Max on whatever that matters to you, i.e., the outcome that matters to you by using it, people should use it. We saw that with some of the OpenAI models in the last quarter. They were fantastic models. And we're obviously very thrilled about the progress OpenAI has made with Astra and also what's to come.

And I thought we saw some good demand on that. Then the next thing people do is, hey, can I actually put multiple of the frontier models because these got -- these are very different prices. In fact, this morning, artificial analysis had the -- what I think is the real benchmark, which is the coding agents using our Fusion, and I think we were #2 or #3 there, which is awesome to see, right, which is you can now get frontier performance, 45% faster, 75% cheaper. Like why -- who would want to not take that, right, which is like if you're a coding agent user, you want, in fact, Anthropic and OpenAI, by the way, to compete for your workload, not like once a quarter, but for every task.

And that, to me, is what the value of these routers and auto fusion stuff routing does, and we are very excited about it. And then the last thing is another important one. A lot of customers are saying, "Hey, look, take the Unilever one, right? It's their system. They will ultimately take even the traces after having done even a bunch with frontier models, and they just want to train their own model. So it can be open weight or in this case, it was MAI model. And so I think all of that needs to be as options that are available.

And then depending on pricing, depending on the need of the customer, they will exercise it. And there's a temporality to it. It's never like, oh, I start one place and that's where I stop, right? It's like I may start at the frontier, I may go to an open weight, I may go to an MAI model. I may go back to the frontier for the next drop for a few months, come out. Like that's how I think -- how dynamic these workloads are. And that's where when we think about foundry or when we think about fabric or when we think about Copilot and GitHub Copilot, we really want to build a model system that delivers customers value continuously versus them being stuck in any one thing.

Operator

The next question comes from the line of Brent Thill with Jefferies.

Brent Thill

Amy, good to see Azure approaching 50%. You have another line item approaching 50%, and that's your operating margin. I think many ask how can you sustain this level of growth with 50% on the top and a 50% on the bottom? Maybe you can discuss the operational improvements you continue to put forward to maintain that high level on the bottom line.

Amy Hood

Thanks, Brent. Let me first say, the best solution here is revenue growth. And so I would say I tend to start and focus there, even though I think many people seem to think I start at the bottom of the P&L and work up. The right answer is you always start at the top of the P&L and work down. And so what we've been focused on, and I think really, it's almost inherent in all of the commentary is we changed segments because we're changing how we deliver products and services to customers. We're changing it because we're delivering new and different products with a lot of value in them. And those products are far more integrated than they were before. I think when you see that revenue accelerate at the top line, of course, it does in a pretty healthy way, contribute to positive margin. And part of the positive margin dollars, which I think I need people to also focus on.

The second piece is the real focus on efficiency because efficiency, when we say the word, I think people believe it's cost related. The outcome is cost related. But the real benefit of efficiency is stability, it's security, it's reliability. It's that it delivers the highest quality unit at the lowest possible cost. And so it's operational excellence. And so I think when you think about you can deliver product excellence, which is what we're really focused on, I think we did a very good job on product quality in the past quarter, which I think team should be proud of in lots of places. I think then you have this sort of operational focus on improvement. And then it is a real focus in terms of operating expense to make sure it's going toward building the new thing or providing security and quality.

And I think that's -- we've made, I think, a very active choice to be really focused on those 2 things, especially in this environment and how important it is. And I think when you do those things and you happen to be in a good market with breadth and breadth in customers and a global business, we've seen a good result. This quarter, in particular, when you're delivering a lot of efficiency gains in the quarter and you can deliver revenue growth without spending additional costs, you, of course, see a benefit, which we did. But I feel good about what's behind that number, which is, I think, a focus on the right levers.

Operator

Our next question comes from the line of Brad Reback with Stifel.

Brad Reback

Great. Sorry about that. I did not hear my name. On M365 consumption, when you all shifted GitHub from a per seat model to a consumption model, it unlocked a ton of revenue growth for you all. As you think about the tools in place now unlock -- on the consumption side for the core M365 customer, do you think the unlocks is fast and without sales effort? Or is it going to take a fair amount of effort to get those meters spinning?

Satya Nadella

Yes. Thanks for the question. I think on the coating side, it will be faster just because I think people are used to paying on this PayGo as the sort of the general market and how it works. And if anything, hopefully, some of the things that we announced even at GitHub Universe today with Fusion are a more attractive way, right? Because you even -- if you think about it, right, you buy a bunch of credits and you want to use those credits most efficiently. That's the promise of GitHub Copilot Fusion. So we are very optimistic about making progress on that. And then when it comes to Copilot itself, right, we are trying to make sure that we, in some sense, are driving more and more value into the subscription with every model drop and essentially consolidating the frontier gains for broad deployment.

And in many instances, as my remarks said, IT funds this, right, as the thing that you want to have standard issue across the board. And at the same time, you have your pay-as-you-go or consumption meters for places where you need it. And so -- so both of those options are open. And I think that's why the -- with Copilot, Amy referenced, which is we are trying to make sure that customers understand both options. They're able to use the 2 options in the optimal way that benefits them. We don't want them to overbuy one thing and then feel like they're token maxing because that doesn't serve anybody's purpose.

We want to make sure that they understand the value of the subscription and how it's a continually improving value. It's not even static. And at the same time, you can exercise this consumption meter. And so that's a little bit of the degree of sophistication in both in our sales motions, even our customers' understanding that's, I think, coming together. We feel very good about the progress, but a lot more to do.

Amy Hood

And I think I would say it's also why we've made the investment into the frontier company here, coupled with changes in our sales motion, which I talked a little bit about, we need both of those things to make sure customers are -- because what I think Satya is saying, we want them to utilize both the Copilot license to its fullest and understand when the consumption meter is delivering value to them. The investment in the FDE organization or the Frontier core as well as new motions within our modern work and Microsoft 365 sales teams are both meant to do that. And I think to Satya's point, it will be a slower move outside of coding. But I also still think we're still seeing encouraging signs, and I feel positive about that.

Jonathan Neilson

Operator, we have time for one last question.

Operator

The next question will come from the line of Tal Liani with Bank of America.

Tal Liani

Just a clarification on something you just said. Did you disclose the Copilot numbers this quarter? But my question is more about the capital commitment or the capital strategy. You said in the prepared remarks that you will approach raising capital if need be in the future. Can you discuss your strategy around it between debt and equity and other sources? How do you intend to raise capital if need be?

Amy Hood

Great. I'll take that. Listen, I think what I said is that if it's attractive and makes sense, we're lucky. We have a lot of flexibility in terms of our capacity to raise financing. I've talked about this before. There's a form of financing called leasing, and we've been using that one as a vehicle. There's also -- we're fortunate to have access in the debt markets, given that where our ratings are and sort of we haven't been able to -- and we haven't yet, I would say, tapped that. And then, of course, there's other options.

But I think the way I see it is we're feeling good that we are free cash flow positive. We feel good that the return on every dollar of CapEx we're spending, we're confident in that. And therefore, we feel like we have lots of options to be able to tap the financing markets when they make sense and they're attractive. And we did not disclose, to answer your direct question, an update on the Copilot number this quarter. We talked about momentum in revenue and usage.

Jonathan Neilson

Thanks, Tal. 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. Thank you all.

Operator

Thank you. This concludes today's conference. You may disconnect your lines at this time, and we thank you for your participation.