微軟 (MSFT) 2025 Q4 法說會逐字稿

Greetings and welcome to the Microsoft fiscal-year 2025 fourth-quarter earnings conference call. (Operator Instructions) As a reminder, this conference is being recorded.

大家好，歡迎參加微軟 2025 財年第四季財報電話會議。（操作員指示）提醒一下，本次會議正在錄音。

It is now my pleasure to introduce Jonathan Nielson, Vice President of Investor Relations.

現在我很高興介紹投資者關係副總裁喬納森尼爾森。

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 Keith Dolliver, Corporate Secretary and Deputy General Counsel.

下午好，感謝您今天加入我們。與我一起參加電話會議的還有董事長兼首席執行官薩蒂亞·納德拉 (Satya Nadella)、首席財務官艾米·胡德 (Amy Hood)、首席會計官愛麗絲·喬拉 (Alice Jolla) 以及公司秘書兼副總法律顧問基思·多利弗 (Keith Dolliver)。

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 a 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.

在微軟投資者關係網站上，您可以找到我們的收益新聞稿和財務摘要幻燈片，旨在補充我們在今天電話會議上的準備好的發言，並提供 GAAP 和非 GAAP 財務指標之間差異的對帳。當我們在今天的電話會議上提供展望評論時，微軟投資者關係網站上將提供更詳細的展望幻燈片。

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 fourth-quarter performance in addition to the impact these items and events have on the financial results.

在本次電話會議中，我們將討論某些非 GAAP 項目。所提供的非 GAAP 財務指標不應被視為替代或優於依照 GAAP 編製的財務績效指標。它們作為額外的澄清項目，旨在幫助投資者進一步了解公司第四季度的業績以及這些項目和事件對財務結果的影響。

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 businesses 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.

除非另有說明，我們今天在電話會議上進行的所有成長比較均與去年同期有關。我們還將提供以固定匯率計算的成長率（如有），作為評估我們基礎業務表現的框架，不包括外匯匯率波動的影響。如果以不變貨幣計算的成長率相同，我們將只參考成長率。

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.

我們將在電話會議結束後立即將準備好的發言發佈到我們的網站上，直到完整的記錄可用為止。今天的電話會議正在進行網路直播和錄音。如果您提出問題，它將包含在我們的直播、記錄以及錄音的任何未來使用中。您可以在微軟投資者關係網站上重播該通話並查看記錄。

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 and the comments made during this conference call and in the Risk Factors section of our Form 10-K, Form 10-Q and other reports and filings with the Securities and Exchange Commission. We do not undertake any duty to update any forward-looking statement.

在本次電話會議中，我們將做出前瞻性陳述，即對未來事件的預測、預期或其他陳述。這些聲明是基於當前的預期和假設，但存在風險和不確定性。由於今天的收益新聞稿中討論的因素以及本次電話會議期間和我們向美國證券交易委員會提交的 10-K 表、10-Q 表和其他報告和文件中的風險因素部分所作的評論，實際結果可能會有重大差異。我們不承擔更新任何前瞻性聲明的義務。

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

說完這些，我將把電話轉給 Satya。

Thank you, Jonathan. It was a very strong close to what was a record fiscal year for us. All up, Microsoft Cloud surpassed $168 billion in annual revenue, up 23%.

謝謝你，喬納森。對我們來說，這是一個創紀錄的財政年度，這是一個非常強勁的結局。整體而言，微軟雲端運算的年收入超過 1,680 億美元，成長 23%。

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

創新的速度和傳播的速度是我們從未見過的。為此，我們正在大規模建構最全面的人工智慧產品和技術堆疊。為了提供更多背景信息，我想從 Azure 開始逐步介紹整個堆疊。

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

Azure 的年收入超過 750 億美元，成長 34%，這得益於所有工作負載的成長。我們持續引領人工智慧基礎設施浪潮，今年每季都佔一定份額。我們在六大洲開設了新的資料中心，目前在 70 個地區擁有 400 多個資料中心，比其他任何雲端供應商都多。

There is a lot of talk in the industry about building the first gigawatt and multi-gigawatt data centers. We stood up more than 2 gigawatts of new capacity over the past 12 months alone. And we continue to scale our own data center capacity faster than any other competitor.

業界對建置首個千兆瓦和多千兆瓦資料中心有很多討論。光是在過去的 12 個月裡，我們就新增了超過 2 千兆瓦的發電容量。我們將繼續以比任何其他競爭對手更快的速度擴大我們自己的資料中心容量。

Every Azure region is now AI First. All of our regions can now support liquid cooling, increasing the fungibility and the flexibility of our fleet and we are driving and riding a set of compounding S curves across silicon, systems and models to continuously improve efficiency and performance for our customers. Take, for example, [GP40] family of models, which have the highest volume of inference tokens. Through software optimizations alone, we are delivering 90% more tokens for the same GPU compared to a year ago.

每個 Azure 區域現在都是 AI First。我們所有的地區現在都可以支援液體冷卻，從而提高了我們設備的可互換性和靈活性，並且我們正在推動和駕馭跨矽晶片、系統和模型的一系列複合 S 曲線，以不斷提高客戶的效率和性能。以 [GP40] 系列模型為例，它有最多的推理標記。僅透過軟體優化，我們為相同 GPU 提供的令牌數量就比一年前增加了 90%。

Beyond the AI fleet, we continue to build our commercial cloud to address customers' unique data residency and sovereignty requirements. This quarter, we introduced the Microsoft Sovereign Cloud, the industry's most comprehensive solution spanning both public and private cloud deployments.

除了人工智慧叢集之外，我們還將繼續建立商業雲，以滿足客戶獨特的資料駐留和主權要求。本季度，我們推出了 Microsoft Sovereign Cloud，這是業界最全面的涵蓋公有雲和私有雲部署的解決方案。

All of this innovation is driving our strong results. We saw accelerating growth from migrations again this quarter. Nestle, for example, migrated more than 200 SAP instances, 10,000-plus servers, 1.2 petabytes of data to Azure with near zero business disruption. That makes it one of the largest and most successful migrations in business history.

所有這些創新都推動著我們取得強勁的業績。本季我們再次看到遷移加速成長。例如，雀巢將 200 多個 SAP 執行個體、10,000 多台伺服器、1.2PB 的資料遷移到 Azure，而業務幾乎沒有中斷。這使得它成為商業史上最大、最成功的遷移之一。

The next big accelerator in the cloud will be Quantum, and I'm excited about our progress. In fact, earlier this month, we announced the world's first operational deployment of a Level 2 Quantum computer in partnership with Atom Computing. This is how we will continue to think and make investments, with decade-long arcs while making progress every quarter.

雲端的下一個大型加速器將是 Quantum，我對我們的進展感到非常興奮。事實上，本月早些時候，我們與 Atom Computing 合作宣布了世界上第一個 2 級量子電腦的運行部署。我們將這樣繼續思考和投資，以十年為週期，每個季度都取得進步。

The next layer is data, which is foundational to every AI application. Microsoft Fabric is becoming the complete data and analytics platform for the AI era, spanning everything from SQL to no-SQL to analytics workloads. It continues to gain momentum with revenue up 55% year over year and over 25,000 customers. It's the fastest-growing database product in our history. Fabric OneLake spans all databases and clouds, including semantic models from Power BI, and therefore, it is the best source of knowledge and grounding for AI applications and context engineering.

下一層是數據，它是每個人工智慧應用的基礎。Microsoft Fabric 正成為人工智慧時代的完整資料和分析平台，涵蓋從 SQL 到 no-SQL 再到分析工作負載的所有內容。公司繼續保持成長勢頭，營收年增 55%，客戶數量超過 25,000 名。這是我們史上成長最快的資料庫產品。Fabric OneLake 涵蓋所有資料庫和雲，包括來自 Power BI 的語義模型，因此，它是 AI 應用和上下文工程的最佳知識來源和基礎。

Azure Databricks and Snowflake on Azure both accelerated as well. Cosmos DB and Azure PostgreSQL are both powering mission-critical workloads at scale. OpenAI, for example, uses Cosmos DB in the hot path of every ChatGPT interaction, storing chat history, user profiles and conversational state. And Azure PostgreSQL stores metadata critical to the operation of ChatGPT as well as OpenAI's developer APIs.

Azure Databricks 和 Azure 上的 Snowflake 也都加速了。Cosmos DB 和 Azure PostgreSQL 皆能大規模支援關鍵任務工作負載。例如，OpenAI 在每個 ChatGPT 互動的熱路徑中使用 Cosmos DB，儲存聊天歷史記錄、使用者設定檔和對話狀態。Azure PostgreSQL 儲存了對 ChatGPT 以及 OpenAI 開發人員 API 的運作至關重要的元資料。

This year, we launched Azure AI Foundry to help customers design, customize, and manage AI applications and agents at scale. Foundry features best-in-class tooling, management, observability, and built-in controls for trustworthy AI. Customers increasingly want to use multiple AI models to meet their specific performance, cost, and use case requirements. And with Foundry, they can provision inferencing throughput ones and apply it across more models than any other hyperscaler, including models from OpenAI, DeepSeek, Meta, xAI's Grok and, very soon, Black Forest Labs and Mistral AI.

今年，我們推出了 Azure AI Foundry，幫助客戶大規模設計、客製化和管理 AI 應用程式和代理商。Foundry 具有一流的工具、管理、可觀察性和內建控制，可實現值得信賴的 AI。客戶越來越希望使用多種 AI 模型來滿足其特定的效能、成本和用例要求。借助 Foundry，他們可以提供推理吞吐量，並將其應用於比任何其他超大規模器更多的模型，包括來自 OpenAI、DeepSeek、Meta、xAI 的 Grok 以及即將推出的 Black Forest Labs 和 Mistral AI 的模型。

We SIM-shipped 15 models from OpenAI alone on Foundry this year, providing same-day access to state-of-the-art models deeply integrated with our infrastructure and tools. And we are seeing accelerated adoption of our new Foundry Agent Service, which is now being used by 14,000 customers to build agents that automate complex tasks.

今年，我們僅在 Foundry 上就透過 SIM 運送了來自 OpenAI 的 15 個模型，讓用戶可以當天訪問與我們的基礎設施和工具深度整合的最先進的模型。我們看到新 Foundry Agent Service 的採用速度正在加快，目前已有 14,000 名客戶使用該服務來建立可自動執行複雜任務的代理程式。

For example, Nasdaq is using Foundry to build agents that help customers prepare for Board meetings, cutting prep time by up to 25%. And all up, 80% of Fortune 500 already use Foundry. And when we look narrowly at just the number of tokens served by Foundry APIs, we processed over $500 trillion this year, up over 7x. This is a good indicator of true platform diffusion beyond a few head apps and services.

例如，納斯達克正在使用 Foundry 建立代理，幫助客戶準備董事會會議，將準備時間縮短高達 25%。整體而言，財富 500 強企業中有 80% 已在使用 Foundry。當我們仔細查看 Foundry API 所服務的代幣數量時，我們今年處理的代幣數量超過 500 兆美元，增加了 7 倍以上。這是平台真正擴散到少數頭部應用程式和服務之外的一個很好的指標。

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

談到應用層，這些應用程式正在融入我們的日常工作和生活中。我們的 Copilot 應用程式系列在商業和消費者領域每月活躍用戶已超過 1 億。當你更廣泛地了解我們產品中人工智慧功能的參與度時，我們每月有超過 8 億活躍用戶。

Microsoft 365 Copilot is becoming the new way to organize work and workflow and work artifacts. We rolled out our biggest update to Microsoft 365 Copilot to date this quarter, bringing together chat, search, create, notebooks as well as agents into one intuitive scaffolding. With this innovation and continued product improvements, we are seeing real momentum. Customers continue to adopt Copilot at a faster rate than any other new Microsoft 365 suite, with strong usage intensity as shown by our week-over-week retention. And we saw the largest quarter of seat ads since launch with a record number of customers returning to buy more seats.

Microsoft 365 Copilot 正在成為組織工作、工作流程和工作成果的新方式。本季度，我們推出了迄今為止對 Microsoft 365 Copilot 的最大更新，將聊天、搜尋、創建、筆記本以及代理整合到一個直觀的框架中。透過這項創新和持續的產品改進，我們看到了真正的發展勢頭。客戶繼續以比任何其他新 Microsoft 365 套件更快的速度採用 Copilot，並且我們的周環比保留率顯示出很高的使用強度。我們看到了自推出以來座位廣告數量最多的一個季度，回頭購買更多座位的顧客數量也創下了歷史新高。

Barclays, for example, will roll out Microsoft 365 Copilot to 100,000 employees globally following a successful initial deployment of 15,000. UBS is expanding its deployment to all of its employees after initially rolling it out to 55,000 of them. And Adobe, KPMG, Pfizer, Wells Fargo, all purchased over 25,000 seats this quarter.

例如，巴克萊銀行在成功初步部署 15,000 名員工後，將向全球 10 萬名員工推廣 Microsoft 365 Copilot。瑞銀最初向 55,000 名員工推廣此系統，現在正將其推廣至所有員工。本季度，Adobe、畢馬威、輝瑞、富國銀行均購買了超過 25,000 個席位。

Tens of thousands of organizations have already used our researcher and analyst deep reasoning agents in the first weeks of availability. And we have introduced group level agents and teams like Facilitator and Interpreter, which generate real-time translation and notes in meetings. Hundreds of partners like Adobe, SAP, ServiceNow and Workday have built their own third-party agents that integrate with Copilot and Teams.

在推出後的最初幾週內，已有數以萬計的組織使用了我們的研究人員和分析師深度推理代理。我們還引入了團體級代理和團隊，例如協調員和口譯員，它們可以在會議中產生即時翻譯和筆記。Adobe、SAP、ServiceNow 和 Workday 等數百家合作夥伴已經建立了自己的第三方代理，並與 Copilot 和 Teams 整合。

We are also seeing more customers use Copilot Studio to extend Microsoft 365 Copilot and build their own agents. This year, customers created 3 million agents using SharePoint and Copilot Studio. And with Copilot tuning, they can easily create agents fine-tuned on their company's data, workflow, and style that reflect the unique tone, language and expertise.

我們也看到越來越多的客戶使用 Copilot Studio 來擴充 Microsoft 365 Copilot 並建立自己的代理程式。今年，客戶使用 SharePoint 和 Copilot Studio 創建了 300 萬個代理程式。透過 Copilot 調整，他們可以輕鬆地創建根據公司數據、工作流程和風格進行微調的代理，以反映獨特的語氣、語言和專業知識。

We're also seeing great traction among specific roles and functions, starting with developers. GitHub Copilot continues to have great momentum in IDE with agent mode and new form factors like Coding Agent which is capable of a synchronously executing developer task. We have 20 million GitHub Copilot users. GitHub Copilot enterprise customers increased 75% quarter over quarter as companies tailor Copilot to their own code bases, and 90% of the Fortune 100 now use GitHub Copilot.

我們也看到特定角色和功能的巨大吸引力，首先是開發人員。GitHub Copilot 在 IDE 中繼續保持強勁發展勢頭，具有代理模式和新形式因素，例如能夠同步執行開發人員任務的 Coding Agent。我們有 2000 萬 GitHub Copilot 用戶。隨著各公司根據自己的程式碼庫客製化 Copilot，GitHub Copilot 企業客戶數量較上季成長了 75%，目前 90% 的財富 100 強企業都使用 GitHub Copilot。

More broadly, GitHub usage and reports are seeing explosive growth because of AI. AI projects on GitHub more than doubled over the last year. The surge in wide-coding projects and AI coding agents, whether it is Cloud Code, Codecs, Cursor, or GitHub Copilot are generating more pull requests and more repos on GitHub. And our Code Review Agent is being used heavily across the platform, performing millions of code reviews each month.

更廣泛地說，由於人工智慧，GitHub 的使用和報告正在呈現爆炸性增長。去年，GitHub 上的人工智慧專案數量增加了一倍以上。廣泛編碼專案和 AI 編碼代理的激增，無論是 Cloud Code、Codecs、Cursor 或 GitHub Copilot，都在 GitHub 上產生了更多的拉取請求和更多的儲存庫。我們的程式碼審查代理商在整個平台上被廣泛使用，每月執行數百萬次程式碼審查。

In health care, we had a breakout year for Dragon Copilot. Customers used our ambient AI solutions to document over 13 million physician-patient encounters this quarter, up nearly 7x year over year. For example, at Mercyhealth System, more than 1,000 physicians are already using Copilot to reduce administrative burden so that they can focus on providing better care. They have saved more than 100,000 hours to date and plan to expand to all 5,000 providers. As one physician put it, the best thing to happen to my practice in 10 years.

在醫療保健領域，Dragon Copilot 取得了突破性的進展。本季度，客戶使用我們的環境 AI 解決方案記錄了超過 1,300 萬次醫病會面，年增近 7 倍。例如，在 Mercyhealth System，超過 1,000 名醫生已經在使用 Copilot 來減輕行政負擔，以便他們可以專注於提供更好的護理。迄今為止，他們已節省了超過 100,000 小時，並計劃擴展到所有 5,000 家供應商。正如一位醫生所說，這是我十年來行醫過程中遇到的最好的事情。

And in security, we were the first in the industry to introduce agents to help defenders autonomously handle high-volume security and IT tasks. More broadly, AI is driving a fundamental change in the biz apps market as customers shift from legacy systems to agentic business applications.

在安全方面，我們在業界率先引入代理，幫助防禦者自主處理大量安全和 IT 任務。更廣泛地說，隨著客戶從傳統系統轉向代理業務應用程序，人工智慧正在推動商業應用程式市場的根本性變革。

Dynamics 365 took share this year, and we are winning customers in every industry, like Verizon with sales, Domino's Pizza Group with ERP, 1-800-Flowers with contact center. When it comes to consumer apps, we are innovating across all surfaces. In fact, on Monday, we introduced Copilot mode in Edge. It's especially exciting to see the innovation coming back to browsers. Copilot Mode brings together Copilot Composer, Chat, Discover, Search, and Actions to build the next generation of browser for the AI age.

Dynamics 365 今年佔據了市場份額，我們在各行各業都贏得了客戶，例如 Verizon 的銷售客戶、Domino's Pizza Group 的 ERP 客戶、1-800-Flowers 的聯絡中心客戶。當談到消費者應用程式時，我們正在各個方面進行創新。事實上，週一我們在 Edge 中引入了 Copilot 模式。看到創新再次回歸瀏覽器，尤其令人興奮。Copilot Mode 將 Copilot Composer、聊天、發現、搜尋和操作結合在一起，為人工智慧時代建立下一代瀏覽器。

Our Copilot Consumer app also continued to see strong growth in engagement and successful sessions. And we are bringing Copilot to every Windows 11 PC. With Copilot Vision, you can share your screen with Copilot and get real-time insights and assistance on anything. And we are well positioned as we approach Windows 10 end of support in October, thanks to Windows 11 and Copilot+ PCs, which offer customers compelling security as well as AI value.

我們的 Copilot Consumer 應用程式在參與度和成功會話方面也持續呈現強勁成長。我們將把 Copilot 引入每台 Windows 11 PC。透過 Copilot Vision，您可以與 Copilot 分享螢幕，並獲得任何內容的即時洞察和協助。由於 Windows 11 和 Copilot+ PC 為客戶提供了強大的安全性和 AI 價值，我們在 10 月 Windows 10 支援終止之際已做好了充分準備。

Talking about security, it underlies our cloud and AI infrastructure as well as our Copilots and agents. We have launched over 100 new capabilities over the past year. Just last week, we added a modern data lake to our SIM, Microsoft Sentinel, bringing together customer data across our first-party tools as well as third-party ecosystem over 350 connectors. We're also extending the systems customers already use for governance, identity, security, and management to protect every AI agent.

說到安全，它是我們的雲端和人工智慧基礎設施以及我們的副駕駛和代理的基礎。過去一年我們推出了 100 多項新功能。就在上週，我們在 SIM 中新增了一個現代資料湖 Microsoft Sentinel，將我們第一方工具以及超過 350 個連接器的第三方生態系統中的客戶資料整合在一起。我們也正在擴展客戶已經使用的治理、身分、安全和管理系統，以保護每個人工智慧代理。

Entra now extends identity permissions, policies and access controls to agents. Defender secures nearly 2 million general AI apps. Purview is used by three quarters of the Microsoft 365 Copilot customers to protect their data. And all up, we now have nearly 1.5 million security customers and continue to take share across all major categories we serve.

Entra 現在將身分權限、政策和存取控制擴展到代理程式。Defender 保護近 200 萬個通用 AI 應用程式。四分之三的 Microsoft 365 Copilot 客戶使用 Purview 來保護他們的資料。總而言之，我們現在擁有近 150 萬安全客戶，並繼續在我們服務的所有主要類別中佔據份額。

Before I wrap, I want to talk about two consumer businesses of ours with massive end-user reach: LinkedIn and Xbox. LinkedIn is home to 1.2 billion members with four consecutive years of double-digit member growth. All up, comments on LinkedIn rose over 30% and video uploads increased over 20% this year. We continue to bring AI to every part of LinkedIn experience, introducing agents across hiring as well as sales.

在結束之前，我想談談我們的兩家擁有大量終端用戶的消費者業務：LinkedIn 和 Xbox。LinkedIn 擁有 12 億會員，會員數連續四年維持兩位數成長。總體而言，今年 LinkedIn 上的評論數量增加了 30% 以上，影片上傳數量增加了 20% 以上。我們將繼續把人工智慧引入 LinkedIn 體驗的各個部分，在招聘和銷售領域引入代理。

When it comes to Gaming, we have 500 million monthly active users across platforms and devices. We are now the top publisher on both Xbox and PlayStation this quarter with successful launches of Forza Horizon 5 and Oblivion Remastered. The Call of Duty franchise has never been stronger. 50 million people have played Black Ops 6, total hours surpassed $2 billion.

就遊戲而言，我們每月在各個平台和裝置上擁有 5 億活躍用戶。憑藉《極限競速：地平線 5》和《上古卷軸 4：湮沒》重製版的成功發布，我們本季已成為 Xbox 和 PlayStation 上最頂尖的發行商。《決勝時刻》系列從未如此強大。已有 5,000 萬人玩過《決勝時刻：黑色行動 6》，總遊戲時長超過 20 億美元。

Minecraft saw record monthly active usage in revenue this quarter, thanks in large part to the success of the Minecraft Movie. And we have nearly 40 games in development, so much, much more to come. We surpassed over 500 million hours of gameplay stream via the cloud this year. And Game Pass annual revenue was nearly $5 billion for the first time.

本季度，Minecraft 的月活躍使用收入創下了歷史新高，這在很大程度上要歸功於 Minecraft 電影的成功。我們有近 40 款遊戲正在開發中，未來還會有更多遊戲推出。今年，我們透過雲端進行的遊戲串流傳輸已超過 5 億小時。而Game Pass年營收首次接近50億美元。

In closing, we are going through a generational tech shift with AI, and I have never been more confident in Microsoft's opportunity to drive long-term growth and define what the future looks like.

最後，我們正在經歷人工智慧的代際技術變革，我從未像現在這樣對微軟推動長期成長和定義未來的機會充滿信心。

With that, let me turn it over to Amy to walk through our financial results as well as the outlook.

接下來，讓我將主題交給艾米，讓她介紹我們的財務表現和前景。

Thank you, Satya, and good afternoon, everyone. This year, we delivered over $281 billion in revenue, up 15% year over year, which reflects the broad strength of our products and services. Operating income was over $128 billion, up 17% year over year as we invested against the expansive opportunity ahead. And in our largest quarter of the year, we significantly exceeded expectations with strong execution by our sales and partner teams. As Satya shared, we're innovating faster than ever to deliver new value to our customers.

謝謝你，薩蒂亞，大家下午好。今年，我們的收入超過 2,810 億美元，年增 15%，這反映了我們產品和服務的廣泛實力。由於我們投資於未來的擴張機會，營業收入超過 1,280 億美元，較去年同期成長 17%。在我們今年最大的一個季度，憑藉銷售和合作夥伴團隊的出色執行，我們大大超出了預期。正如 Satya 所說，我們正在以前所未有的速度進行創新，為客戶提供新的價值。

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

本季營收為 764 億美元，成長 18%，以固定匯率計算成長 17%。毛利率以固定匯率計算成長了 16% 和 15%，而營業收入以固定匯率計算成長了 23% 和 22%。每股收益為 3.65 美元，成長 24%，以固定匯率計算成長 22%。

For the first time, commercial bookings were over $100 billion, increasing 37% and 30% in constant currency on a strong prior year comparable. Strong execution across our core annuity sales motions, including healthy renewals as well as an increase in the number of $10 million and $100 million-plus contracts for both Azure and Microsoft 365 helped drive these results.

商業預訂額首次超過 1,000 億美元，較上年同期的強勁成長 37%（以固定匯率計算為 30%）。我們核心年金銷售計畫的強力執行，包括健康的續約以及 Azure 和 Microsoft 365 的 1000 萬美元和 1 億美元以上合約數量的增加，有助於推動這些業績。

Commercial remaining performance obligation increased to $368 billion, up 37% and 35% in constant currency. Roughly 35% will be recognized in revenue in the next 12 months, up 21% year over year. The remaining portion recognized beyond the next 12 months increased 49%. And this quarter, our annuity mix was again 98%. FX was roughly in line with expectations on total company revenue, segment level revenue, COGS, and operating expense growth.

商業剩餘履約義務增至 3,680 億美元，成長 37%，以固定匯率計算成長 35%。約有 35% 將在未來 12 個月內實現收入，年增 21%。未來 12 個月後確認的剩餘部分增加了 49%。本季度，我們的年金組合再次達到 98%。外匯與公司總收入、分部收入、銷貨成本和營業費用成長的預期大致一致。

Microsoft Cloud revenue was $46.7 billion, ahead of expectations, and grew 27% and 25% in constant currency. Microsoft Cloud gross margin percentage was slightly better than expected at 68%, down 2 points year over year from the impact of scaling our AI infrastructure, partially offset by continued efficiency gains in Azure and M365 Commercial Cloud. Company gross margin percentage was 69%, down 1 point year over year, driven by sales mix shift to Azure and the lower Microsoft Cloud gross margin noted earlier.

微軟雲端運算業務營收為 467 億美元，超出預期，以固定匯率運算成長 27% 和 25%。微軟雲端毛利率略好於預期，為 68%，受擴大 AI 基礎設施的影響，年減 2 個百分點，但 Azure 和 M365 商業雲的持續效率提升部分抵銷了這一影響。公司毛利率為 69%，年減 1 個百分點，原因是銷售組合轉向 Azure 以及先前提到的 Microsoft Cloud 毛利率下降。

Operating expenses increased 6% and 5% in constant currency, and operating margins increased 2 points year over year to 45%. Better-than-expected revenue growth coupled with a focus on operating efficiently drove the margin expansion. At a total company level, head count at the end of June was relatively unchanged year over year.

營業費用以固定匯率計算成長了 6% 和 5%，營業利潤率年增 2 個百分點至 45%。優於預期的收入成長加上對高效能營運的關注推動了利潤率的擴大。從整個公司層級來看，六月底的員工人數與去年同期相比基本上沒有變化。

Now to our segment results. Revenue from Productivity and Business Processes was $33.1 billion and grew 16% and 14% in constant currency, better than expected, driven by M365 Commercial products in cloud services and M365 consumer products in cloud services. M365 Commercial cloud revenue was ahead of expectations and increased 18% and 16% in constant currency, with 2 points of benefit from in-period revenue recognition. Business trends remained relatively stable to the prior quarter when excluding the end-period revenue recognition, with ARPU growth again driven by E5 and M365 Copilot.

現在來看看我們的分部業績。生產力和業務流程收入為 331 億美元，成長 16%，以固定匯率運算成長 14%，優於預期，這得益於雲端服務中的 M365 商業產品和雲端服務中的 M365 消費產品。M365 商業雲端收入超出預期，成長 18%，以固定匯率計算成長 16%，期間營收確認帶來 2 個點的收益。剔除期末收入確認後，業務趨勢與上一季相比保持相對穩定，ARPU 成長再次受到 E5 和 M365 Copilot 的推動。

Paid M365 commercial seats grew 6% year-over-year with installed base expansion across all customer segments, though primarily in our small and medium business and frontline worker offerings. M365 Commercial Products revenue increased 9% and 7% in constant currency, ahead of expectations to higher-than-expected Office 2024 transactional purchasing. M365 Consumer cloud revenue was better than expected, increasing 20% driven by ARPU growth following the January price increase and subscriber growth of 8%.

付費 M365 商業席位年增 6%，安裝基數擴大至所有客戶群，但主要集中在我們的中小型企業和第一線員工產品。M365 商業產品營收成長 9%，以固定匯率計算成長 7%，超出預期，Office 2024 交易購買量高於預期。M365 消費者雲端收入優於預期，在 1 月價格上漲和用戶成長 8% 的推動下，ARPU 成長了 20%。

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

LinkedIn 營收成長 9%，以固定匯率計算成長 8%，所有業務均實現成長，但人才解決方案業務持續受到招聘市場疲軟的影響。Dynamics 365 營收成長了 23%，以固定匯率計算成長了 21%，我們核心年金銷售計畫的強勁執行帶動了所有工作負載的成長。

Segment gross margin dollars increased 16% and 15% in constant currency, and gross margin percentage increased slightly, driven by the efficiency gains noted earlier, even as we deliver more AI features across our products and scale our AI infrastructure. Operating expenses increased 7% and 6% in constant currency, and operating income increased 21% and 19% in constant currency.

儘管我們在產品中提供了更多 AI 功能並擴展了 AI 基礎設施，但分部毛利率按固定匯率計算增長了 16% 和 15%，毛利率百分比略有增加，這得益於前面提到的效率提升。營業費用以固定匯率計算成長了 7%（以固定匯率計算為 6%），營業收入以固定匯率計算成長了 21%（以固定匯率計算為 19%）。

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

接下來是智慧雲部分。在 Azure 和我們的內部伺服器業務的推動下，營收達到 299 億美元，成長 26%，以固定匯率計算成長 25%，超出預期。在 Azure 和其他雲端服務方面，營收成長了 39%，大大超出預期，這主要得益於我們核心基礎設施業務的加速成長，主要來自我們最大的客戶。提醒一下，新的雲端和人工智慧工作負載是利用我們廣泛的服務來建構和擴展的。

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

Azure AI 服務的收入基本上符合預期。儘管我們本季增加了資料中心容量，但需求仍然高於供應。

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

在我們的內部伺服器業務中，收入按固定匯率計算下降了 2% 和 3%，高於預期，這主要受到交易採購的推動，該業務的期末收入確認也較高。企業和合作夥伴服務收入以固定匯率計算分別成長 7% 和 6%，其中企業支援服務的成長被產業解決方案的下降部分抵銷。

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

由於擴大了我們的 AI 基礎設施，分部毛利率增長了 17%，以固定匯率計算增長了 16%，毛利率百分比同比下降了 4 個百分點，但先前提到的 Azure 效率提升部分抵消了這一影響。營業費用以固定匯率計算成長了 6% 和 4%，營業收入成長了 23%。

Now to More Personal Computing. Revenue was $13.5 billion and grew 9%, exceeding expectations, primarily due to Windows OEM as well as Xbox content and services. Windows OEM and Devices revenue increased 3% year over year, ahead of expectations, as inventory levels remained elevated. Search and news advertising revenue ex TAC increased 21% and 20% in constant currency, driven by continued growth in both volume and revenue per search, as well as roughly 8 points of favorable impact from third-party partnerships, including the benefit of a low prior-year comparable.

現在開始更個人化地計算。營收為 135 億美元，成長 9%，超出預期，主要歸功於 Windows OEM 以及 Xbox 內容和服務。由於庫存水準保持高位，Windows OEM 和設備收入年增 3%，超出預期。扣除 TAC 後的搜尋和新聞廣告收入按固定匯率計算分別增長了 21% 和 20%，這得益於搜尋量和每次搜尋收入的持續增長，以及第三方合作夥伴關係帶來的約 8 個百分點的有利影響，包括去年同期較低的可比價格帶來的好處。

And in Gaming, revenue increased 10%. Xbox content and services revenue increased 13% and 12% in constant currency, driven by better-than-expected performance from first-party content and Xbox Game Pass. Segment gross margin dollars increased 15%. Gross margin percentage increased 3 points year over year with improvement across all businesses. Operating expenses increased 4% and 3% in constant currency. Operating income increased 34% and 33% in constant currency, driven by continued prioritization of higher margin opportunities.

遊戲業務的收入成長了 10%。Xbox 內容和服務收入以固定匯率計算分別成長 13% 和 12%，這得益於第一方內容和 Xbox Game Pass 表現優於預期。分部毛利率成長了15%。毛利率年增 3 個百分點，所有業務均有所改善。營業費用以固定匯率計算成長了 4%，以固定匯率計算成長了 3%。由於繼續優先考慮更高利潤機會，營業收入成長了 34%，以固定匯率計算成長了 33%。

Now back to total company results. Capital expenditures were $24.2 billion, including $6.5 billion of finance leases where we recognize the full value at the time of lease commencement. Cash paid for PP&E was $17.1 billion. The difference is primarily due to finance leases. More than half our spend was on long-lived assets that will support monetization over the next 15 years and beyond. The remaining spend was primarily for servers, both CPUs and GPUs and driven by strong demand signals.

現在回到公司整體業績。資本支出為 242 億美元，其中包括 65 億美元的融資租賃，我們在租賃開始時確認全部價值。用於 PP&E 的現金支付額為 171 億美元。差異主要是由於融資租賃造成的。我們的支出有一半以上用於支持未來 15 年及以後貨幣化的長期資產。剩餘的支出主要用於伺服器，包括 CPU 和 GPU，並受到強勁需求訊號的推動。

Cash flow from operations was $42.6 billion, up 15%, driven by strong cloud billings and collections, partially offset by higher supplier payments. And this quarter, free cash flow was $25.6 billion. Other income and expense was negative $1.7 billion, primarily due to losses on investments accounted for under the equity method. Our effective tax rate was approximately 17%. And finally, we returned $9.4 billion to shareholders through dividends and share repurchases, bringing our total cash return to shareholders to over $37 billion for the full fiscal year.

營運現金流為 426 億美元，成長 15%，這得益於強勁的雲端帳單和收款，但部分被更高的供應商付款所抵消。本季自由現金流為 256 億美元。其他收入和支出為負 17 億美元，主要由於權益法核算的投資損失。我們的有效稅率約為17%。最後，我們透過股利和股票回購向股東返還了 94 億美元，使我們整個財年向股東返還的現金總額超過 370 億美元。

Now moving to our outlook. My commentary for both the full year and next quarter is on a US-dollar basis, unless specifically noted otherwise. Let me start with some full year commentary for FY26.

現在轉向我們的展望。除非另有特別說明，我對全年和下一季的評論都是以美元為基礎的。首先，我想對 26 財年做一些全年評論。

First, FX. Assuming current rates remain stable, we expect FX to increase full year revenue growth and COGS growth by approximately 2 points and to increase operating expense growth by 1 point.

首先，FX。假設當前匯率保持穩定，我們預計外匯將使全年收入成長和銷貨成本成長增加約 2 個百分點，並使營運費用成長增加 1 個百分點。

Next, building on the strong momentum we saw this past year, we expect to deliver another year of double-digit revenue and operating income growth in FY26. We will continue to invest against the expansive opportunity ahead across both capital expenditures and operating expenses given our leadership position in commercial cloud, strong demand signals for our cloud and AI offerings, and significant contracted backlog.

接下來，基於去年強勁的發展勢頭，我們預計 2026 財年的營收和營業收入將再次實現兩位數成長。鑑於我們在商業雲領域的領導地位、對我們的雲端和人工智慧產品的強勁需求訊號以及大量的合約積壓，我們將繼續在資本支出和營運費用方面投資以抓住未來的廣闊機會。

Capital expenditure growth, as we shared last quarter, will moderate compared to FY25 with a greater mix of short-lived assets. Due to the timing of delivery of additional capacity in H1, including large finance lease sites, we expect growth rates in H1 will be higher than in H2. We remain focused on delivering revenue growth and increasing our operational agility. And as a result, we expect operating margins to be relatively unchanged year over year. And finally, we expect our FY26 effective tax rate to be between 19% and 20%.

正如我們上個季度所分享的，與 25 財年相比，資本支出成長將有所放緩，短期資產組合將會增加。由於上半年新增產能的交付時間，包括大型融資租賃站點，我們預計上半年的成長率將高於下半年。我們仍然專注於實現收入成長和提高營運靈活性。因此，我們預期營業利潤率將比去年同期保持相對不變。最後，我們預計 26 財年有效稅率將在 19% 至 20% 之間。

Now to our outlook for the first quarter. Based on current rates, we expect FX to increase total revenue growth by 2 points. Within the segments, we expect FX to increase revenue growth by roughly 3 points in Productivity and Business Processes and roughly 1 point in Intelligent Cloud and More Personal Computing. We expect FX to increase COGS and operating expense growth by roughly 1 point.

現在來展望一下第一季。根據當前匯率，我們預計外匯將使總收入增加 2 個百分點。在這些領域中，我們預期 FX 將使生產力和業務流程領域的營收成長提高約 3 個百分點，使智慧雲端和更多個人運算領域的營收成長提高約 1 個百分點。我們預計外匯將使 COGS 和營運費用增加約 1 個百分點。

In Commercial bookings, we expect healthy growth on a growing expiry base. Bookings growth will again be driven by strong execution across our core annuity sales motions and long-term commitments to our platform. As a reminder, larger long-term Azure contracts, which are more unpredictable in their timing, drive increased quarterly volatility in our bookings growth rate.

在商業預訂方面，我們預計隨著到期基礎的增加，預訂將實現健康成長。預訂量的成長將再次受到我們核心年金銷售計畫的強勁執行和對我們平台的長期承諾的推動。提醒一下，更大的長期 Azure 合約（其時間更難以預測）會導致我們的預訂量成長率的季度波動加劇。

Microsoft Cloud gross margin percentage should be roughly 67%, down year over year, driven by the impact of continuing to scale our AI infrastructure. We expect Q1 capital expenditures to be over $30 billion, driven by the continued strong demand signals we see. As a reminder, there can be quarterly spend variability from cloud infrastructure build-outs and the timing of delivery of finance leases.

微軟雲端的毛利率約為 67%，年減，這受到我們持續擴大人工智慧基礎設施的影響。我們預計第一季的資本支出將超過 300 億美元，這得益於我們看到的持續強勁的需求訊號。提醒一下，雲端基礎設施建設和融資租賃交付時間可能會造成季度支出變化。

Next, to segment guidance. In Productivity and Business Processes, we expect revenue of USD32.2 billion to USD32.5 billion or growth of 14% to 15%, with roughly 3 points of benefit from FX as noted earlier. In M365 Commercial cloud, we expect revenue growth to be between 13% and 14% in constant currency, with business trends that remain relatively stable compared to the prior quarter. ARPU growth will again be driven by E5 and M365 Copilot. M365 Commercial products revenue growth should be in the mid- to high single digits.

接下來，進行分段指導。在生產力和業務流程方面，我們預計收入將達到 322 億美元至 325 億美元，或成長 14% 至 15%，其中如前所述，外匯將帶來約 3 個百分點的收益。在 M365 商業雲端方面，我們預期營收成長率以固定匯率計算將在 13% 至 14% 之間，業務趨勢與上一季相比保持相對穩定。E5 和 M365 Copilot 將再次推動 ARPU 成長。M365 商業產品收入成長應在中高個位數。

As a reminder, M365 Commercial products includes both the Windows Commercial on-premises components of M365 suite and Office transactional purchasing, both of which can be variable due to end-period revenue recognition dynamics. M365 Consumer cloud revenue growth should be in the low 20s, driven by the January price increase. For LinkedIn, we expect revenue growth in the high-single digits. And in Dynamics 365, we expect revenue growth to be in the high teens with continued growth across all workloads.

提醒一下，M365 商業產品包含 M365 套件的 Windows Commercial 內部部署元件和 Office 交易購買，這兩者都可能因為期末收入確認動態而改變。受 1 月價格上漲的推動，M365 消費者雲端收入成長率應該在 20% 出頭。對於 LinkedIn，我們預計其收入將實現高個位數成長。在 Dynamics 365 中，我們預計營收成長將達到百分之十幾，並且所有工作負載都將持續成長。

For Intelligent Cloud, we expect revenue of USD30.1 billion to USD30.4 billion, or growth of 25% to 26%, with roughly 1 point of benefit from FX as noted earlier. Revenue will continue to be driven by Azure, which can have quarterly variability and year-on-year growth rates depending on the timing of capacity delivery and when it comes online, as well as from end-period revenue recognition depending on the mix of contracts.

對於智慧雲，我們預計營收為 301 億美元至 304 億美元，或成長 25% 至 26%，如前所述，外匯將帶來約 1 個點的收益。收入將繼續由 Azure 推動，其季度變化和同比增長率可能取決於容量交付時間和上線時間，以及取決於合約組合的期末收入確認。

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

在 Azure 方面，我們預計第一季營收以固定匯率計算將成長約 37%，這得益於對我們服務組合的強勁需求。即使我們繼續在線上提供更多的資料中心容量，我們目前預計在本財年上半年仍將受到容量限制。

In our on-premises server business, we expect revenue to decline in the low- to mid-single digits with the ongoing customer shift to cloud offerings. In More Personal Computing, we expect revenue to be USD12.4 billion to USD12.9 billion. Windows OEM and Devices revenue should decline in the mid- to high single digits. We expect the elevated inventory levels at the end of Q4 to come down through the quarter in Windows OEM, although the range of potential outcomes remains wider than normal. Devices revenue should decline.

在我們的內部伺服器業務中，隨著客戶不斷轉向雲端產品，我們預計收入將下降低至中等個位數。在「更多個人計算」領域，我們預計收入將達到 124 億美元至 129 億美元。Windows OEM 和裝置收入預計將出現中高個位數的下降。我們預計第四季末 Windows OEM 庫存水準將在本季下降，儘管潛在結果的範圍仍然比正常情況要大。設備收入應該會下降。

Search and news advertising ex TAC revenue growth should be in the low to mid-teens, down sequentially as growth rates normalize following the benefit from third-party partnerships noted earlier. Growth will continue to be driven by volume and revenue per search across Edge and Bing. Overall search and news advertising revenue growth should be in the low-double digits.

搜尋和新聞廣告（扣除 TAC）收入成長應處於低至中等水平，隨著前面提到的第三方合作夥伴關係帶來的收益，成長率將恢復正常，因此環比下降。Edge 和 Bing 的搜尋量和每次搜尋的收入將繼續推動成長。整體搜尋和新聞廣告收入成長率應在兩位數以下。

And in Gaming, we expect revenue to decline in the mid- to high-single digits. Against a strong prior year comparable, we expect Xbox content and services revenue to decline in the mid-single digits.

在遊戲領域，我們預計收入將下降中高個位數。與去年同期的強勁表現相比，我們預期 Xbox 內容和服務收入將下降中等個位數。

Now back to company guidance. We expect COGS of USD24.3 billion to USD24.5 billion or growth of 21% to 22%, and operating expense of USD15.7 billion to USD15.8 billion or growth of 5% to 6%. Other income and expense is estimated to be negative $1.3 billion, primarily due to investments accounted for under the equity method. As a reminder, we do not recognize mark-to-market gains or losses on equity method investments. And lastly, we expect our Q1 effective tax rate to be between 19% and 20%.

現在回到公司指導。我們預計銷貨成本為 243 億美元至 245 億美元，成長 21% 至 22%，營業費用為 157 億美元至 158 億美元，成長 5% 至 6%。其他收入和支出估計為負 13 億美元，主要由於權益法核算的投資。提醒一下，我們不確認權益法投資的以市價計價的收益或損失。最後，我們預計第一季有效稅率將在 19% 至 20% 之間。

In closing, we finished the year with double-digit revenue and operating income growth and exceeded the FY25 operating margin commitment we shared a year ago. Our focus remains on investing in security, quality, and AI platform and product innovation that delivers value and opportunity to our customers. We are excited for FY26.

最後，我們以兩位數的營收和營業收入成長結束了這一財年，並超越了我們一年前做出的 25 財年營業利潤率承諾。我們仍然專注於投資安全性、品質以及為客戶帶來價值和機會的人工智慧平台和產品創新。我們對 26 財年充滿期待。

With that, let's go to Q&A, Jonathan.

下面，我們進入問答環節，喬納森。

Thanks, Amy. We'll now move over to Q&A.

謝謝，艾米。我們現在進入問答環節。

(Operator Instructions)

（操作員指示）

(Operator Instructions)

（操作員指示）

Keith Weiss, Morgan Stanley.

摩根士丹利的基斯‧韋斯。

Congratulations on a fantastic end to FY25. I've been covering Microsoft for a while, I don't think I've ever seen a quarter where like everything came together this well. So congratulations on that execution. Maybe a little bit longer term focus question to start out.

恭喜 2025 財年圓滿結束。我關注微軟已經有一段時間了，我認為我從未見過哪個季度的業績能如此順利。祝賀你成功執行。也許首先要討論的是一些長期關注的問題。

You guys have always had software startups as customers and potentially merging competitors, but the AI Labs now feel different. Investors are ascribing valuations which assume these companies become major players in software. They're underwriting revenue forecasts measured in the tens of billions, if not hundreds of billions. And these startups have also grown to be some of your biggest customers. So they're contributing significantly to Microsoft today.

你們一直都有軟體新創公司作為客戶和潛在的合併競爭對手，但現在人工智慧實驗室的感覺不同了。投資者的估值是假設這些公司將成為軟體領域的主要參與者。他們承保的收入預測數以百億甚至數千億美元計。這些新創公司也已經成長為你們最大的客戶。所以他們今天對微軟做出了重大貢獻。

So it seems like there's a lot of potential opportunity in supporting those businesses, but also it's not certain that they're going to stay your customers as they scale. They could insource some of that that infrastructure, and they very likely emerge as potential competitors. So as managers of Microsoft, as managers of the capital, how do you, guys, manage that risk versus reward with these quickly emerging AI Labs and these AI startups?

因此，支持這些企業似乎有很多潛在機會，但也不確定他們是否會在規模擴大後繼續成為您的客戶。他們可以把部分基礎設施納入其中，而且很有可能成為潛在的競爭對手。那麼，身為微軟的管理者，身為資本的管理者，你們如何管理這些快速崛起的人工智慧實驗室和人工智慧新創公司的風險與回報？

Well thanks, Keith for the question. I don't think it's that different from even sort of the previous era. There's always been, I'll call it, head apps or head company -- new companies that emerge, that in fact are very needed in order to birth a new platform.

好的，謝謝 Keith 提出這個問題。我認為這與之前的時代並沒有什麼不同。我稱之為「頭部應用程式」或「頭部公司」的新公司一直不斷出現，事實上，它們對於新平台的誕生非常必要。

Back in the day when I was getting started on Azure, I used to look over the lake and sort of see Netflix and Amazon, and I say I wish Netflix ran on Azure, and in some sense that's kind of what we now have, which is the largest AI workloads run on Azure. And when that happens, you learn the workload faster, you optimize the entire platform faster, everything from what we're doing with Cosmos DB for a chat interface like ChatGPT or Copilot is, guess, what going to be the most relevant for any AI application going forward.

當我開始使用 Azure 時，我常常看著湖面，看到 Netflix 和 Amazon，我說我希望 Netflix 能夠在 Azure 上運行，從某種意義上說，這就是我們現在所擁有的，即在 Azure 上運行的最大的 AI 工作負載。當這種情況發生時，您可以更快地了解工作負載，更快地優化整個平台，從我們使用 Cosmos DB 為 ChatGPT 或 Copilot 等聊天介面所做的一切，猜猜看，對於未來的任何 AI 應用程式來說，這將是最相關的。

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

我們現在建立的整個數據堆疊將針對人們所描述的任何人工智慧應用程式最困難的挑戰之一進行最佳化，即上下文工程，即如何收集數據，然後確保問題周圍的環境在很長一段時間內保持穩定，以便您獲得真正實現所需結果的智慧。

So these are workload results that are invaluable for us to learn to build both the products as well as the platform. And then broadly, they -- or rather over time, there will be broad diffusion. In fact, one of the things that Amy and I track is not just the head app usage, but also what's the sort of all the Tier 2 applications that are being built.

因此，這些工作量結果對於我們學習建立產品和平台來說非常寶貴。然後從廣義上講，或者更確切地說，隨著時間的推移，它們將會得到廣泛的傳播。事實上，艾米和我追蹤的事情之一不僅是頭部應用程式的使用情況，還有正在建立的所有 Tier 2 應用程式的類型。

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

所以，基思，我認為你的問題是，只要我們有頭部應用程式來塑造平台，然後，我們就會有廣泛的傳播，從某種意義上說，這兩者都是我們所看到的。因此，我對於我們今後的地位保持平等感到非常高興。

Mark Moerdler, Bernstein Research.

伯恩斯坦研究公司 (Bernstein Research) 的馬克‧莫德勒 (Mark Moerdler)。

I'll also give you my congratulations. Amazing. I didn't know how you were going to beat last quarter, and you did it. So congratulations. Satya and Amy, we're now two-plus years into the GenAI revolution and adoption is still early and ramping.

我也要向你表示祝賀。驚人的。我不知道上個季度你會如何獲勝，但你做到了。恭喜你。Satya 和 Amy，我們進入 GenAI 革命已經兩年多了，但其應用仍處於早期階段，並且正在蓬勃發展。

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

您認為軟體公司將 AI 貨幣化用於 SaaS 的最佳方式是什麼？您是否認為橫向更通用的應用程式（如 M365 Copilot 或 Dynamics CRM Copilot）與代理商方面的非常有針對性的容量在貨幣化方面存在差異？此外，您應該如何看待 SaaS AI 利潤率的長期趨勢？

Yes. I'll start and Amy, you should feel free to add. I mean if I just broaden out beyond just SaaS as a category, I think just like the server to cloud transition was an expansion of essentially usage of servers, that is potentially what happened with the cloud, right, which is we did a bunch of servers except that the expertise required, the capital required, the time required to bring up servers, build it out, scale it, was just all hard. And so therefore, the market was a certain size. Whereas with the cloud, you could sort of buy it with flexibility, you could burst and you could spin up and spin down, the expertise required came down. So it was just orders of magnitude.

是的。我先開始，艾米，你可以隨意加入。我的意思是，如果我將範圍擴大到 SaaS 這一類別之外，我認為就像伺服器到雲端的轉變本質上是伺服器使用範圍的擴展一樣，這可能就是雲端所發生的事情，對吧，我們做了一堆伺服器，但所需的專業知識、所需的資金、啟動伺服器、建立伺服器、擴展伺服器所需的時間都很困難。因此，市場具有一定的規模。而使用雲，您可以購買具有靈活性的雲，可以爆發，可以加速或減速，所需的專業知識就減少了。所以這只是數量級而已。

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

這就是正在發生的事情。因此，如果你甚至同意這種觀點，即智能基本上是計算的對數。這意味著運算能力將會成長，你必須盡可能有效率地使用它來不斷創造智慧。

Now how does it manifest beyond just the infrastructure? I kind of, to Keith's earlier question, I talked a little bit about how the infrastructure is getting shaped, data layer is getting shaped, the app server is getting built. These are all classic categories of infrastructure that will continue, but there will be an order or two of magnitude more. So literally, like -- in fact, one of the other things we track is every GPU requires storage and compute. That ratio is another thing that is really exponential for infrastructure growth.

那麼，除了基礎設施之外，它還有哪些表現形式呢？對於 Keith 之前的問題，我稍微談了一下基礎架構是如何形成的，資料層是如何形成的，應用伺服器是如何建構的。這些都是將繼續存在的經典基礎設施類別，但數量將增加一到兩個數量級。所以實際上，我們追蹤的另一件事是每個 GPU 都需要儲存和運算。這個比率對於基礎設施成長而言是另一個真正呈指數級成長的因素。

So when you go to the app layer, the SaaS apps themselves are now building in effectively agentic and chat interfaces with intelligence. And they're also building autonomous agents. Agents are kind of like applications, like a database application perhaps, but they are being used increasingly inside of a user interaction. I think a good example is GitHub Copilot.

因此，當您進入應用程式層時，SaaS 應用程式本身正在建立具有智慧的有效代理和聊天介面。他們還在建構自主代理。代理有點像應用程序，可能像資料庫應用程序，但它們在用戶互動中的使用越來越多。我認為一個很好的例子是 GitHub Copilot。

It got started as a code completions on an IDE. Then we added the chat interface to it. Then we added the agent mode to it. And now we have an autonomous agent, which in fact works completely asynchronously, right? So all those four things are now part of essentially GitHub.

它最初是作為 IDE 上的程式碼完成功能而出現的。然後我們給它添加了聊天介面。然後我們給它添加了代理模式。現在我們有了一個自主代理，它實際上是完全非同步工作的，對嗎？所以這四個東西現在基本上都是 GitHub 的一部分。

And by the way, it also turns out that every other tool that is also doing any form of coding is adding more and more GitHub repos. So if I have to think about GitHub monetization, we have an opportunity around just monetizing GitHub enterprise and then we have the ability to think about GitHub Copilot, and GitHub Copilot as with all these form factors. And so that's exactly the same thing that's happening with Microsoft 365. That's the same thing that's happening with Dynamics 365.

順便說一句，事實證明，所有其他進行任何形式編碼的工具都在添加越來越多的 GitHub 儲存庫。因此，如果我必須考慮 GitHub 貨幣化，我們就有機會將 GitHub 企業貨幣化，然後我們有能力考慮 GitHub Copilot，以及具有所有這些形式因素的 GitHub Copilot。這與 Microsoft 365 發生的事情完全相同。Dynamics 365 也發生過同樣的事情。

So you have to be very open to taking your data tier, your business logic tier, and your UI tier and sort of being more expansive. And as long as you do that, it's just that usage goes up, and that's what I think shows up in the results.

因此，您必須非常開放地採用資料層、業務邏輯層和 UI 層，並且使其更具擴充性。只要你這樣做，使用率就會上升，我認為這就會在結果中反映出來。

And I think, Mark, if you wanted to think about all the things in the layers that you talked about, is really we're seeing very similar monetization tools exist in this transition too, right? There's a per user logic, there's tiers of per user. Sometimes those tiers relate to consumption, sometimes there's pure consumption models.

馬克，我想，如果你想思考一下你談到的各個層面上的所有事情，我們真的會看到在這種轉變中也存在非常相似的貨幣化工具，對嗎？每個使用者都有其邏輯，每個使用者都有其層級。有時這些層級與消費有關，有時則是純粹的消費模式。

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

我認為你會繼續看到這些的融合，特別是隨著人工智慧模型能力的成長，你最終會發現團隊會想要限制這種使用，使用最好的模型來完成最好的工作。我認為，我們在未來仍會看到這些模型的融合。

Thank you. I appreciate it.

謝謝。我很感激。

Karl Keirstead, UBS.

瑞銀的卡爾·基爾斯特德（Karl Keirstead）。

Okay. Satya and Amy, this is the second quarter in a row of pretty material Azure upside from what sounds like an acceleration in on-prem to Azure migration activity. I'm just wondering if you can comment on the plethora of customer conversations you've had, whether there are a couple of two or three specific catalysts that are driving that migration. And how durable a trend do you think that is?

好的。Satya 和 Amy，這是 Azure 連續第二季實現相當可觀的成長，這聽起來像是本地到 Azure 的遷移活動加速了。我只是想知道您是否可以評論一下您與大量客戶進行的對話，是否有兩三個特定的催化劑推動了這種遷移。您認為這種趨勢能持續多久？

Yes. Just three things are really happening. One is the migrations. A good example would be what I referenced in my remarks with Nestle, with the SAP instances, they moved along with a lot of the data that's associated with it in a bunch of servers. So that's kind of a classic example. I think, whether it's VMware migrations or migrations of SAP, or even just our own server migrations, they're pretty healthy. And it turns out that we're still not anywhere close to the finish line, if, at best, maybe in the middle innings of that.

是的。真正發生的只有三件事。一是遷徙。一個很好的例子就是我在與雀巢的評論中提到的，透過 SAP 實例，他們將大量與其相關的資料轉移到了一堆伺服器中。這是一個典型的例子。我認為，無論是 VMware 遷移還是 SAP 遷移，甚至只是我們自己的伺服器遷移，它們都非常健康。但事實證明，我們距離終點線還很遠，或者，充其量，可能只是處於中間階段。

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

正在發生的第二件事是雲端原生應用程式的擴充。這甚至排除了所有的人工智慧內容。就說典型的雲端原生電子商務公司吧。這些都在大規模地擴展。其中一些客戶以前沒有使用過 Azure，但現在他們越來越多地使用 Azure，因為他們可能是為了 AI 而來，但現在他們留下來的原因不僅僅是 AI。所以對我來說，這是你在 Azure 數字中看到的整體情況的另一件事。

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

當然，還有新的人工智慧工作負載。所以從某種意義上來說，這三件事是相互依存的，但這也是推動我們成長的動力。

Got it. Thank you.

知道了。謝謝。

Brent Thill, Jefferies.

布倫特·蒂爾（Brent Thill），傑富瑞集團。

Satya, back to the strength across the board in the quarter, was there anything that jumped out at you or surprised you that you didn't think you were going to see but you did see in the quarter? Just the magnitude of upside, I think, had shocked many here.

Satya，回到本季的全面強勁表現，有什麼事情讓您印象深刻或感到驚訝，您以為您不會在本季度看到但卻看到了嗎？我認為，光是上漲幅度就已讓很多人感到震驚。

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

是的。布倫特，我不知道是否有任何事令我們感到驚訝。但我認為，我們在自己建立這些人工智慧應用程式時注意到，總的來說，平台已經變得不僅僅是一個模型，這是一個 API，可以進行一些調用，對嗎？我的意思是——從某種意義上說，這可能在一年前就達到了最先進的水平。

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

而現在，您基本上已經擁有了這些正在出現的非常有狀態的應用程式模式，這些模式甚至需要對應用程式堆疊進行相當多的重新思考。我的意思是甚至包括儲存層，對嗎？您的複雜程度，嘿，您真正想要透過預處理來建立多少索引，以便您的提示工程或上下文工程（我稱之為）可以更好、品質更高？所以我認為所有這些都正在顯現。

So when I look at a product like Azure Search, Fabric, and Cosmos DB, all of the things, the frameworks around it, are just becoming robust to build serious applications. And so that's what I feel great about, is the learning curve inside the company, outside the company, the diffusion of the stack, the speed with which that's emerging that you can build applications, is much faster.

因此，當我查看 Azure Search、Fabric 和 Cosmos DB 等產品時，所有這些東西以及圍繞它的框架都變得強大，可以建立重要的應用程式。令我感到高興的是，公司內部、公司外部的學習曲線、堆疊的傳播、建立應用程式的速度都快得多。

I always go back and say, hey, when, I don't know, our relational database came out, it took a while for people to build an ERP system, let's say. And this thing, we're kind of building pretty sophisticated applications at a very, very fast clip based on, I think, the degree of maturity that's emerging.

我總是回過頭來說，嘿，當，我不知道，我們的關聯式資料庫問世時，人們花了一段時間才建立一個 ERP 系統。而這件事情，我們正在以非常非常快的速度建立相當複雜的應用程序，我認為，這是基於正在出現的成熟度。

Raimo Lenschow, Barclays.

巴克萊銀行的 Raimo Lenschow。

Congrats from me as well. I had one question on Copilot, and I'm obviously a happy user here at Barclays. If you think about it, the one thing that we're all realizing is that Copilot is the AI part, but data is becoming more and more important. And then from there on, we can start thinking about agents. Where is the -- what are you seeing in your customer conversations, Satya, about like that understanding that Copilot is actually just the starting point, and then from there on it's becoming like much, much broader?

我對此也表示祝賀。我對 Copilot 有一個疑問，顯然我是巴克萊銀行的滿意用戶。如果你仔細想想，我們都會意識到一件事，那就是 Copilot 是人工智慧的一部分，但數據正變得越來越重要。然後從那時起，我們就可以開始考慮代理了。薩蒂亞，您在與客戶的對話中看到了什麼？您認為 Copilot 實際上只是一個起點，從那以後，它會變得越來越廣泛嗎？

Yes. I think that that's right. Even inside of Copilot, I'm sure you're seeing it, right? You now have analysts and researchers, to just talk about two examples, and of course, people, all the third-party agents. So yes, there is a lot more of it's just not request, respond. It's about spawning essentially applications that then go to work and come back.

是的。我認為那是對的。即使在 Copilot 內部，我相信你也看到了，對吧？現在有分析師和研究人員，僅舉兩個例子，當然還有人們，所有的第三方代理。是的，還有很多事情不僅僅是請求，還有回應。它本質上是生成應用程序，然後開始工作並返回。

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

但即使對於非同步工作來說，UI 仍然非常重要。為了指導非同步工作，您需要 UI。要監控非同步工作，您需要 UI。可能不一樣，可能不是一個聊天介面。當然，您需要一種方法來檢查非同步工作是什麼，對嗎？

So even take the example I was giving on GitHub. Even if you're not using GitHub Copilot to create the core check-in or the pool request, interestingly enough, we're seeing massive increase to GitHub Copilot Code Review Agent even if you used maybe Claude Code or whatever else to write the code. So that's, I think, what's happening across all of these systems.

因此，甚至以我在 GitHub 上給出的例子為例。有趣的是，即使您沒有使用 GitHub Copilot 來建立核心簽入或池請求，即使您使用 Claude Code 或其他任何程式碼來編寫程式碼，我們也會看到 GitHub Copilot 程式碼審查代理程式的大幅增加。所以，我認為，這就是所有這些系統中正在發生的事情。

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

所以你說的完全正確——它從某種更注重聊天的用戶介面開始，但很快就會超越它。您可以在 M365 中看到它，在 Dynamics 365 中看到它，在 GitHub 中看到它。

Thank you.

謝謝。

Kash Rangan, Goldman Sachs.

高盛的卡什·蘭根（Kash Rangan）。

Amy, I want to acknowledge that I think a few quarters ago, you said that you reached a point in time where you can accelerate Azure while slowing down CapEx. So you did it. But what is the outlook? When I look at the CapEx guidance for the upcoming quarter, certainly, I would view that as a positive indicator of the book of business you have for your cloud services.

艾米，我想承認，我認為幾個季度前，你說過你已經達到了一個可以加速 Azure 同時減緩資本支出的時間點。所以你做到了。但前景如何？當我查看下一季的資本支出指引時，我當然會將其視為雲端服務業務的正面指標。

But how should we think about the shape of the curve of CapEx vis-a-vis Azure growth rate in the years ahead, particularly as I listen to Satya's comments on the AI stack consuming more and more infrastructure? Are we at a point where we're going to have to continue to do this and we magically wait for inference and applications to kick in and, therefore, create a richer gross margin mix? And congrats on the quarter.

但是，我們應該如何看待未來幾年資本支出與 Azure 成長率曲線的形狀，特別是當我聽到 Satya 關於 AI 堆疊消耗越來越多基礎設施的評論時？我們是否必須繼續這樣做，並神奇地等待推理和應用程式開始發揮作用，從而創造更豐富的毛利率組合？恭喜本季取得佳績。

Thanks, Kash. Let me back up and first say, when you think about the full-year comments I've made on CapEx as well as the Q1 guidance of over $30 billion, you first have to ground yourself in the fact that we have $368 billion of contracted backlog we need to deliver, not just across Azure but across the breadth of the Microsoft Cloud. So in terms of feeling good about the ROI and the growth rates and the correlation, I feel very good that the spend that we're making is correlated to basically contracted on the books business that we need to deliver and we need the teams to execute at their very best to get the capacity in place as quickly and effectively as they can.

謝謝，卡什。讓我回顧一下，首先要說的是，當您考慮我對資本支出所做的全年評論以及超過 300 億美元的第一季度指引時，您首先必須認識到，我們有 3680 億美元的合約積壓需要交付，不僅在 Azure 上，而且在整個 Microsoft Cloud 上。因此，就對投資回報率、成長率和相關性感到滿意而言，我感到非常高興，因為我們的支出與我們需要交付的帳面業務基本相關，我們需要團隊盡最大努力執行，以盡快、有效地實現產能到位。

And so when you look -- and we've talked about the growth rate will decline year over year, but at its core, our investments, particularly in short-lived assets like servers, GPUs, CPUs, networking storage, is just really correlated to the backlog we see and the curve of demand. And I talked about, my gosh, in January and said I thought we'd be in better supply demand shape by June. And now I'm saying, I hope I'm in better shape by December. And that's not because we slowed CapEx even with accelerating the spend and trying to pull leases in and get CPUs and GPUs in the system as quickly as we can, we are still seeing demand improve.

所以當你看的時候——我們已經討論過成長率會逐年下降，但從本質上講，我們的投資，特別是在伺服器、GPU、CPU、網路儲存等短期資產上的投資，實際上與我們看到的積壓和需求曲線相關。天哪，我在一月份就說過，我認為到六月我們的供需狀況會更好。現在我想說，我希望到十二月我的狀態會更好。這並不是因為我們放慢了資本支出，即使我們加快了支出，並試圖盡快獲得租賃並讓 CPU 和 GPU 進入系統，我們仍然看到需求有所改善。

And so I am not as focused, Kash, on trying to pick a date at which revenue growth and CapEx growth will meet and cross. I'm focused on building backlog, building business and delivering capacity, which we are seeing has a good ROI today in terms of our ability to get that done. So I don't want people to get overly focused on a pivot point. Because when you're in sort of these expansive moments, picking a data point usually means you're going to pick to be too conservative in terms of market share gain and in terms of winning. And so I tend to put my energy more there.

因此，Kash，我並沒有那麼專注於嘗試選擇收入成長和資本支出成長相遇和交叉的日期。我專注於建立積壓訂單、建立業務和提供產能，就我們完成這些任務的能力而言，我們今天看到了良好的投資報酬率。所以我不希望人們過度專注於一個關鍵點。因為當你處於這些擴張時刻時，選擇一個數據點通常意味著你會在市佔率成長和獲勝方面做出過於保守的選擇。因此我傾向於把更多的精力投入那裡。

Yes. I think one of the other things, Kash, is that -- I think I said this in the previous earnings as well, which is the difference between a hoster and a hyperscaler is software. And the same is going to be true here. That GP40 example I gave is all software, right? The optimization even in the last year.

是的。卡什，我認為另一件事是——我想我在之前的收益中也說過這一點，託管商和超大規模商之間的區別在於軟體。這裡的情況也是如此。我給的那個 GP40 範例都是軟體，對嗎？甚至在去年也進行了優化。

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

因此，我們知道如何使用軟體技能來使任何硬體變得更好。這就是收益的來源。但正如艾米所說，當你真正去建造工廠時，你並不想對其進行序列化。你只想在所有這些方面努力，隨著時間的推移，這些就會逐漸增加。

And I do think it's important, when Satya talks about the software layer, he is talking about in his comments to connect this back to the compounding S curves. And so I would remind people, that is something that we saw through the prior cloud transition, it's how we operated through that one. And the same sort of skills and logic done at an even faster pace is what will apply the same transition.

我確實認為這很重要，當 Satya 談論軟體層時，他在評論中談到將其與複合 S 曲線聯繫起來。所以我想提醒大家，這是我們在之前的雲端轉型過程中看到的，也是我們當時的運作方式。以更快的速度運用同樣的技能和邏輯將實現同樣的轉變。

Sounds very encouraging. Thank you so much.

聽起來非常令人鼓舞。太感謝了。

Michael Turrin, Wells Fargo.

富國銀行的邁克爾·圖林。

Congrats from me as well on the metrics working in concert here. Amy, maybe on margin, impressive to hear expectations for flat operating margin in the upcoming year as you absorb some of the mix shift towards Azure and some of the more AI-focused offerings. Can you speak in more detail just around your ability to manage those trade-offs and offset some of the mix shift? And I'm wondering specifically just on any productivity gains you're seeing from leveraging AI internally that you'd highlight or anything else you just mention in underpinning the full-year expectation there?

我自己也對這裡的各項指標協同工作表示祝賀。艾米，也許在利潤率方面，聽到對來年持平的營業利潤率的預期令人印象深刻，因為你吸收了一些向 Azure 和一些更注重人工智慧的產品的混合轉變。您能否更詳細地談談您管理這些權衡和抵消部分混合轉變的能力？我特別想知道，您是否看到內部利用人工智慧帶來的生產力提升，或者您剛才提到的其他任何內容是否支援全年預期？

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

謝謝，麥可。我認為真正需要關注的領域是，當你考慮利潤時，我認為有時人們會把大量精力放在成本控制上，將其視為利潤的驅動力。另一個驅動因素是專注於確保你提供具有競爭力和創新性且能夠佔據市場份額的優秀產品，因為這會帶來收入。而收入本身和收入成長，正如大家所了解的，甚至可能比我更了解，是實現利潤率提高的持久方法。它是自我建構的。

That being said, the second thing I would point to is really when I talk to Kash a little bit about before, Satya and I both mentioned it, is applying all of our skill set here to deliver efficiencies, whether that's at whatever layer of the stack that is, the S curves compound, and we are doing that work, and we're focused on it. At the same time, we're doing the build out. So you'll see improvements there even as we continue to invest.

話雖如此，我想指出的第二件事實際上是當我之前與 Kash 交談時，Satya 和我都提到過，就是在這裡運用我們所有的技能來提高效率，無論是在堆疊的任何一層，S 曲線複合，我們正在做這項工作，我們專注於此。同時，我們正在進行擴建。因此，即使我們繼續投資，您也會看到那裡的改善。

And then, of course, it's about continuing to have great talent here, focus on products and opportunities where we have the biggest markets and the most likelihood of success. And so when we have those three things happen and the energy is right and the focus is there, it gives me confidence in terms of margin delivery. But make no mistake, it starts and ends really with product, which is what we're really focused on here and delivering that to customers.

當然，我們的重點是繼續擁有優秀的人才，專注於我們擁有最大市場和最有可能成功的產品和機會。因此，當這三件事發生，並且能量正確且焦點就在那裡時，它就讓我對利潤交付充滿信心。但請不要誤會，一切確實始於產品，終於產品，而這正是我們真正關注的重點，並將產品交付給客戶。

That all sounds pretty good. Thank you so much.

聽起來都很不錯。太感謝了。

Thanks, Michael. 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 you all soon.

謝謝，麥可。今天的收益電話會議的問答部分到此結束。感謝您今天加入我們，我們期待很快與您交談。

Thank you.

謝謝。

Thank you.

謝謝。

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

今天的會議到此結束。現在您可以斷開線路。感謝您的參與。