微軟 (MSFT) 2026 Q4 法說會逐字稿

Greetings, and welcome to the Microsoft fiscal year 2026 fourth-quarter earnings conference call. (Operator Instructions) As a reminder, this conference is being recorded.

各位好，歡迎參加微軟 2026 會計年度第四季財報電話會議。(接線員指示) 提醒您，本次會議將被錄音。

It is now my pleasure to introduce Jonathan Neilson, Vice President of Investor Relations. Please go ahead.

現在我很榮幸為各位介紹投資人關係副總裁 Jonathan Neilson。請開始。

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.

各位下午好，感謝今天加入我們的電話會議。與我一同出席的有：董事長兼執行長 Satya Nadella；財務長 Amy Hood；會計長 Alice Jolla；以及副總法律顧問兼公司秘書 Brian DeFoe。

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 slide will be available on the Microsoft Investor Relations website where we provide outlook commentary on today's call.

在微軟投資人關係網站上，您可以找到我們的財報新聞稿與財務摘要簡報投影片，該投影片旨在補充我們今天電話會議的事先準備講稿，並提供 GAAP 與非 GAAP 財務衡量指標之間差異的調節表。更詳細的展望投影片將會發布於微軟投資人關係網站，我們也會在今天的電話會議中提供展望評論。

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，我們將討論若干非 GAAP 項目。所提供的非 GAAP 財務衡量指標不應被視為依 GAAP 編製之財務績效衡量指標的替代或更優者。納入這些項目是作為額外的釐清資訊，協助投資人進一步理解公司第四季的表現，以及這些項目與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中所做的所有成長比較，皆以去年同期為基準。在可提供的情況下，我們也會提供以固定匯率計算的成長率，作為評估我們核心業務表現的架構，以排除外幣匯率波動的影響。若固定匯率下的成長率相同，我們將僅提及該成長率。

We will post our prepared remarks to our website immediately following the call until the complete transcript is available.

我們將在電話會議結束後立即把事先準備的講稿發布到網站上，並保留至完整逐字稿可供查閱為止。

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.

今天的電話會議將進行即時網路直播並錄音。若您提問，該問題將納入我們的即時傳輸、逐字稿，以及未來任何對錄音的使用。您可以在微軟投資人關係網站上重播本次電話會議並查看逐字稿。

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 statement.

在本次電話會議中，我們將做出前瞻性陳述，亦即對未來事件的預測、推估或其他陳述。這些陳述係基於目前的預期與假設，並可能受到風險與不確定性的影響。實際結果可能因今日財報新聞稿所討論的因素、在本次電話會議中所發表的評論，以及我們 Form 10-K、Form 10-Q 與其他向美國證券交易委員會提交之報告與申報文件中的風險因素章節所述因素，而出現重大差異。我們不承擔更新任何前瞻性陳述的義務。

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

接下來，我把電話會議交給 Satya。

Thank you very much, Jonathan. It was a very strong close to what was a record fiscal year for us. All up, our annual revenue surpassed $331 billion, up 18%; Microsoft Cloud surpassed $214 billion, up 27%; and Azure surpassed $100 billion, up 41%.

非常感謝你，Jonathan。我們以非常強勁的表現為這個創紀錄的會計年度畫下句點。整體而言，我們全年營收突破 3,310 億美元，成長 18%；Microsoft Cloud 營收突破 2,140 億美元，成長 27%；Azure 營收突破 1,000 億美元，成長 41%。

Going forward, we have two goals. First, ensuring AI empowers every person, amplifying their agency and ambition; and second, empowering every organization to build their own continuous learning loop and ensuring that they don't outsource their core IP.

展望未來，我們有兩個目標。第一，確保 AI 能賦能每一個人，放大其自主性與抱負；第二，賦能每一個組織建立自身的持續學習迴圈，並確保他們不會把核心智慧財產權外包出去。

Now let's talk about how we're delivering this across our stacks, starting with our AI platform and infrastructure. We added 31 new data centers across five continents this quarter, bringing the total to 88 this year as we expand our footprint in response to accelerating demand.

現在讓我們談談我們如何在整個技術堆疊中落實這些目標，先從我們的 AI 平台與基礎設施開始。本季我們在五大洲新增了 31 座資料中心；隨著需求加速成長，我們擴大佈局，今年累計新增總數達到 88 座。

We're also bringing capacity online faster than ever. Over the last fiscal year, we have reduced dock-to-live times for new GPUs in our largest regions by nearly 50%. All up, we add in another gigawatt of capacity this quarter and remain on track to roughly double our overall capacity in just two years.

我們也以前所未有的速度讓產能上線。在上一個會計年度，我們在最大型區域將新 GPU 從到港到上線（dock-to-live）的時間縮短了近 50%。整體而言，本季我們再新增 1 吉瓦的產能，並仍按計畫在短短兩年內將整體產能約翻倍。

We're also getting more from the infrastructure we already have by optimizing across silicon systems and software. For example, we increased the throughput for Copilot workloads 4x since the start of the year. AI sovereignty is increasingly top of mind for our customers, and we are expanding our offerings to meet that need. Just last week we announced a partnership with Mistral to bring its models to Microsoft Sovereign Cloud, enabling customers to run them across public, customer-controlled, and fully disconnected environments.

我們也透過在矽晶系統與軟體之間進行最佳化，從既有基礎設施中取得更高效益。例如，自年初以來，我們將 Copilot 工作負載的吞吐量提升了 4 倍。AI 主權日益成為客戶關注的重點，我們正擴大產品供給以滿足此需求。就在上週，我們宣布與 Mistral 建立合作夥伴關係，將其模型帶到 Microsoft Sovereign Cloud，使客戶能在公有環境、客戶自主管控環境，以及完全離線的環境中運行這些模型。

We also continue to modernize our fleet with our own silicon innovation alongside the latest from NVIDIA and AMD. Maia 200 continues to scale. It delivers 30% better performance per dollar than the latest generation hardware in our fleet and is now supporting both OpenAI and MAI models. And we will be among the first cloud providers to deploy next-generation rack scale AI infrastructure based on AMD Helios and NVIDIA Vera Rubin.

我們也持續以自研矽晶創新，並結合 NVIDIA 與 AMD 的最新技術，推進我們的機群現代化。Maia 200 持續擴展規模。相較於我們機群中的最新一代硬體，它每美元可提供高出 30% 的效能，並已開始同時支援 OpenAI 與 MAI 模型。此外，我們將成為首批部署基於 AMD Helios 與 NVIDIA Vera Rubin 的下一代機架級（rack scale）AI 基礎設施的雲端供應商之一。

When it comes to running agents, CPUs are just as important as GPUs. Our Cobalt VMs are powering both our own first-party workloads as well as workloads for customers, including Adobe, Arm, Elastic, OpenAI, Sprinklr, and TomTom. And by the end of this month, we expect to have our Cobalt 200 racks in over 25 data centers around the world as we rapidly expand capacity.

在運行代理（agents）方面，CPU 與 GPU 同樣重要。我們的 Cobalt 虛擬機（VMs）不僅支援我們自家的第一方工作負載，也支援客戶的工作負載，包括 Adobe、Arm、Elastic、OpenAI、Sprinklr 與 TomTom。預計在本月底前，我們的 Cobalt 200 機架將部署至全球超過 25 座資料中心，隨著我們快速擴充產能而持續推進。

Now let me turn to the end-to-end platform we are building on this infrastructure to run, govern, and distribute apps and agents. It starts with model choice. Every customer wants the right model for each task based on quality, latency, cost, and compliance. We offer the broadest model catalog in the cloud with over 11,000 models, including the latest from OpenAI, Anthropic, Mistral, xAI, as well as our own MAI family.

接著我談談我們在此基礎設施之上打造的端到端平台，用於運行、治理並分發應用程式與代理。這一切始於模型選擇。每位客戶都希望針對每項任務，依品質、延遲、成本與合規性選擇最合適的模型。我們在雲端提供最廣泛的模型目錄，超過 11,000 個模型，包括 OpenAI、Anthropic、Mistral、xAI 的最新模型，以及我們自家的 MAI 系列。

Since the start of the year, we have seen 5x increase in the number of customers building with models from multiple providers. Levi Strauss & Co, for example, is using models from OpenAI and Anthropic on foundry as it brings more than 1,000 domain-specific agents into a unified enterprise AI platform.

自年初以來，我們看到使用多家供應商模型進行建置的客戶數量成長了 5 倍。例如，Levi Strauss & Co 正在 Foundry 上同時使用 OpenAI 與 Anthropic 的模型，將超過 1,000 個特定領域代理整合到統一的企業 AI 平台中。

We are also accelerating our own model development. We announced more than a dozen new models across image, voice, transcription, coding, security, including our first reasoning model MAI-Thinking-1, all with cost-efficient inference at the core for the enterprise use cases. We are co-designing these models with our silicon, and we are seeing 40% better performance per watt when running MAI models on Maia 200. But more importantly, we are building a new model system where the harness, context, memory, and action space are separate from any one model family, thereby moving the frontier on the cost to outcome curve.

我們也在加速自家模型的研發。我們宣布推出十多個新模型，涵蓋影像、語音、轉錄、程式碼撰寫與資安等領域，其中包括我們第一個推理模型 MAI-Thinking-1；這些模型皆以具成本效率的推論為核心，以服務企業使用情境。我們正將這些模型與自家矽晶共同設計，並且在 Maia 200 上運行 MAI 模型時，已看到每瓦效能提升 40%。但更重要的是，我們正在打造一個新的模型系統，使編排框架（harness）、上下文（context）、記憶（memory）與行動空間（action space）能與任何單一模型家族分離，從而推進「成本到成果」曲線的前沿。

And it's not just about cost. It also has the added benefit of business continuity and resilience because every model is substitutable. This is the system we are using in our products with great results. For example, millions of developers have used MAI-Code-1-Flash on GitHub Copilot achieving higher core acceptance rates and 10% lower median token usage, while still having access to frontier capabilities from OpenAI and Anthropic.

而且這不僅僅是成本問題。它也帶來業務連續性與韌性的額外好處，因為每個模型都可以相互替換。這正是我們在產品中使用的系統，並取得了很好的成果。例如，數百萬名開發者已在 GitHub Copilot 上使用 MAI-Code-1-Flash，達成更高的核心接受率，且中位數 token 使用量降低 10%，同時仍可存取 OpenAI 與 Anthropic 的前沿能力。

In Excel, MAI-Code-1-Flash is delivering comparable quality to GPT-5.6 for the most common task while operating at significantly lower costs. In security, MAI-Cyber-1-Flash achieves better performance than much larger Mythos model but half the cost when combined with our multi-agent security harness. More broadly, across our model implementations, we are seeing significant efficiency gains, including 89% reduction of GPU costs in Dynamics 365 with MAI-Voice-2 Flash, and up to 84% reduced GPU costs in PowerPoint with MAI-Image-2.5. And this system is available to any company to use as part of foundry.

在 Excel 方面，MAI-Code-1-Flash 以顯著更低的成本，在最常見的任務上提供可與 GPT-5.6 相當的品質。在資安方面，MAI-Cyber-1-Flash 與我們的多代理資安測試框架結合後，以一半的成本達到優於規模大得多的 Mythos 模型的表現。更廣泛地說，在我們的模型落地實作中，我們看到顯著的效率提升，包括在 Dynamics 365 中使用 MAI-Voice-2 Flash 將 GPU 成本降低 89%，以及在 PowerPoint 中使用 MAI-Image-2.5 將 GPU 成本最多降低 84%。而這套系統也可供任何公司作為 foundry 的一部分來使用。

The next layer is the enterprise data in context. The data estate is evolving from primarily supporting apps used by people to supporting agents. Customers are rapidly adopting our AI-optimized databases like Cosmos DB and PostgreSQL to give agents fast, secure access to real-time data and context they need for memory and retrieval. PostgreSQL revenue was up 55%, accelerating for the third consecutive quarter. Also, the number of PostgreSQL customers also using foundry increased 80% as customers increasingly choose it as the database for AI workloads.

下一層是具備情境的企業資料。資料資產正從主要支援人們使用的應用程式，演進為支援代理。客戶正快速採用我們的 AI 最佳化資料庫（如 Cosmos DB 與 PostgreSQL），讓代理能快速且安全地存取即時資料與其所需的情境，用於記憶與檢索。PostgreSQL 營收成長 55%，且已連續第三季加速成長。此外，同時使用 foundry 的 PostgreSQL 客戶數也成長 80%，因為客戶愈來愈多選擇它作為 AI 工作負載的資料庫。

And we are going further with HorizonDB, our new fully managed PostgreSQL service on Azure, which delivers 3 times the throughput of self-managed deployments. When it comes to analytics, we now have over 40,000 paid fabric customers, up more than 60% year over year; and over 17,000 customers now use foundry and fabric, up 60% year over year as enterprises connect agents to real-time operational, analytical, and unstructured data in fabric.

我們也透過 HorizonDB 更進一步；這是我們在 Azure 上全新、完全託管的 PostgreSQL 服務，提供自管部署 3 倍的吞吐量。在分析方面，我們目前有超過 40,000 名付費 fabric 客戶，年增超過 60%；而目前也有超過 17,000 名客戶同時使用 foundry 與 fabric，年增 60%，因為企業正將代理連結到 fabric 中的即時營運、分析與非結構化資料。

This quarter, we also introduced Rayfin, the agent-first SDK that delivers a back end-as-a-service for building apps and fabric. More than 2,500 customers have already used Rayfin and is now powering the back ends for apps created with Replit II.

本季我們也推出 Rayfin，這是一個以代理優先的 SDK，提供用於建置應用程式與 fabric 的後端即服務（back end-as-a-service）。已有超過 2,500 名客戶使用 Rayfin，且它目前正為以 Replit II 建立的應用程式提供後端支援。

On top of this data estate, we are building an IQ layer that combines data with model capabilities to deliver the right context at the right time. Tens of thousands of customers, including nearly 90% of the Fortune 500, are already grounding their agents in enterprise context with foundry, fabric, and work IQ. And this quarter, we introduced Web IQ, which gives agents access to real-world intelligence from across the web. It's already being used by the most popular AI assistants, including ChatGPT.

在這個資料資產之上，我們正在建置一個 IQ 層，結合資料與模型能力，在正確的時間提供正確的情境。已有數以萬計的客戶（包括近 90% 的《財富》500 大企業）透過 foundry、fabric 與 work IQ，將其代理建立在企業情境之上。而本季我們推出 Web IQ，讓代理能存取來自全網的真實世界情報。它已被最受歡迎的 AI 助理使用，包括 ChatGPT。

Beyond model choice, data, and context, we are building foundry as the complete app and agent stack. It gives agents access to the IQ layer, the tools they use, along with durable state and memory, secure sandboxes, rubrics, and evals, and even their own self-improvement loops. We now have 100,000 foundry customers and revenue more than doubled year over year.

除了模型選擇、資料與情境之外，我們正將 foundry 打造成完整的應用程式與代理堆疊。它讓代理可存取 IQ 層、其使用的工具，以及持久狀態與記憶、安全沙箱、規範（rubrics）與評估（evals），甚至還有自我改進迴圈。我們目前有 100,000 名 foundry 客戶，營收年增逾一倍。

Telefonica, for example, adopted foundry as the foundation of its corporate agentic platform with its first wave of agents tackling mission-critical network operations. All up, the number of foundry customers at 1 trillion token annualized run rate increased 4x year over year.

例如，Telefonica 採用 foundry 作為其企業代理平台的基礎，第一波代理正處理關鍵任務的網路營運。整體而言，年化執行率達 1 兆 token 的 foundry 客戶數年增 4 倍。

And finally, with Agent 365, we offer a control plane that extends company's existing governance, identity, security, and management frameworks to agents they build. Just two months in, Agent 365 now has nearly 40 million agents registered across tens of thousands of companies.

最後，透過 Agent 365，我們提供一個控制平面，將企業既有的治理、身分、資安與管理框架延伸到其所建置的代理。僅兩個月，Agent 365 目前已在數以萬計的公司中，登錄近 4,000 萬個代理。

Now let me turn to the apps and agents we are building on top of this platform for individuals and organizations. When it comes to knowledge work, we now have over 30 million paid Microsoft 365 Copilot seats, with net seat adds more than doubling quarter over quarter. Copilot is evolving rapidly from chat to Cowork to Autopilots. Last month, we made Cowork generally available, helping customers complete multi-step tasks grounded in their work data while meeting enterprise security and compliance requirements.

接下來我來談談我們在此平台之上，為個人與組織打造的應用程式與代理。在知識工作方面，我們目前有超過 3,000 萬個付費 Microsoft 365 Copilot 席位，且淨新增席位數較前一季成長超過一倍。Copilot 正快速從聊天演進到 Cowork，再到 Autopilots。上個月，我們正式全面推出 Cowork，協助客戶在符合企業資安與合規要求的前提下，基於其工作資料完成多步驟任務。

This quarter, we also introduced Autopilot's autonomous long-running agents with full enterprise compliance, including always-on personal agent powered by OpenClaw. And this quarter, we are bringing these Copilot experiences together, including code in one super app spanning both consumer and commercial experiences. This is a major step forward, and I look forward to sharing more soon.

本季我們也推出 Autopilot 的自主、長時間運行代理，並具備完整的企業合規能力，其中包括由 OpenClaw 驅動的全天候個人代理。而在本季，我們也將這些 Copilot 體驗整合在一起，包括把程式碼也納入其中，打造一個橫跨消費者與商務體驗的超級應用程式。這是重大的一步，我也期待很快能分享更多。

More broadly, we have steadily been improving the quality and performance of Copilot and have been delighted by the recent customer feedback. Over the last three quarters, user satisfaction scores have doubled and are now at an all-time high. And this quarter alone, we cut latency by 25%. These quality improvements, together with continued product innovation, are driving record usage intensity.

更廣泛地說，我們持續提升 Copilot 的品質與效能，並對近期客戶回饋感到非常振奮。在過去三個季度，使用者滿意度分數翻倍，並創下歷史新高。而僅在本季，我們就將延遲降低了 25%。這些品質提升，加上持續的產品創新，正推動使用強度創下新紀錄。

The number of conversations per user nearly doubled year over year. Average weekly engagement is on par with Outlook and Teams. And the time from deployment to what we think of as high usage, meaning monthly active usage about 80% across a customer's user base, has fallen from months to just days over the past year.

每位使用者的對話次數年增近一倍。平均每週互動程度與 Outlook 和 Teams 相當。而從部署到我們所稱的高使用量（也就是在客戶使用者群中，月活躍使用率約達 80%）的時間，在過去一年已從數月縮短到僅需數天。

The number of customers with more than 50,000 seats increased over 7x year over year. And the number of enterprise customers deploying Copilot to the majority of their information workers grew nearly 75% quarter over quarter, a signal of how central Copilot has become to their operations. NHS England, for example, is rolling out Copilot to 505,000 clinicians and staff, the largest healthcare deployment of its kind after a trial showed it saved employees an average of 43 minutes per day. KPMG is expanding its deployment across its global workforce of more than 276,000 professional, and HSBC committed to 200,000 seats to accelerate its workforce transformation.

席位數超過 50,000 的客戶數年增超過 7 倍。而將 Copilot 部署到其大多數資訊工作者的企業客戶數，較前一季成長近 75%，顯示 Copilot 已成為其營運的核心。例如，英格蘭 NHS 正將 Copilot 推廣至 505,000 名臨床人員與員工；在試點顯示員工平均每天可節省 43 分鐘後，這成為同類型中規模最大的醫療部署。KPMG 正將部署擴展至其全球超過 276,000 名專業人員；而 HSBC 承諾採購 200,000 個席位，以加速其勞動力轉型。

AstraZeneca, Boeing, Infosys, Coke Inc., Procter & Gamble, Stellantis, Tata Consulting Service, University of Pittsburgh Medical Center, Wells Fargo and Wipro, each purchased 60,000 or more. And we have been encouraged by the response to our new E7 suite as customers increasingly go all in on an integrated AI offering that brings together Copilot, E5, Entra, and Agent 365.

AstraZeneca、Boeing、Infosys、Coke Inc.、Procter & Gamble、Stellantis、Tata Consulting Service、University of Pittsburgh Medical Center、Wells Fargo 與 Wipro，皆各自採購 60,000 個或以上。此外，客戶對我們全新的 E7 套件反應令人鼓舞；隨著客戶愈來愈多全面採用整合式 AI 方案，將 Copilot、E5、Entra 與 Agent 365 匯聚在一起。

Just two months after launch, hundreds of enterprise customers have already purchased millions of seats. And this quarter, EY deployed E7 to 400,000 employees in our largest win to date. In addition to this, we are also evolving our business model beyond per-seat to per-seat-plus consumption, further expanding our TAM and delivering more customer value.

上市僅兩個月，已有數百家企業客戶採購了數百萬個席位。而本季，EY 將 E7 部署至 400,000 名員工，成為我們迄今最大的一筆勝出案例。除此之外，我們也正將商業模式從按席位計費，演進為「按席位加上用量」的計費方式，進一步擴大我們的 TAM，並為客戶創造更多價值。

Earlier this month, we added usage-based billing to Cowork with thousands of customers already paying for and actively using it. In biz apps, we have been reinventing Dynamics 365 for an agent-first world. We are exposing over 650,000 MCP actions across sales, finance, supply chain, HR, and customer service, so that agents can now access business context and take action using the same data models, rules, permission, security guardrails, and audit trails as any application user. And we are also moving from seats to seats-plus consumption model.

本月稍早，我們為 Cowork 新增以用量為基礎的計費，已有數千名客戶正在付費並積極使用。在商務應用方面，我們正為代理優先的世界重新打造 Dynamics 365。我們在銷售、財務、供應鏈、人資與客戶服務等領域，開放超過 650,000 個 MCP 動作，讓代理如今可使用與任何應用程式使用者相同的資料模型、規則、權限、資安護欄與稽核軌跡來存取業務情境並採取行動。而我們也正從席位模式轉向席位加上用量的模式。

Customer service is at the forefront of this transformation, with usage-based credit consumption in this category up 4x quarter over quarter with customers like Northern Trust using our tools to drive proactive intelligence.

客戶服務正處於這場轉型的最前線，該類別的按使用量計費之信用額度消耗較上一季成長 4 倍，像 Northern Trust 這樣的客戶正使用我們的工具來推動主動式智慧。

When it comes to developers, GitHub Copilot now has 50 million users. This quarter, we introduced usage-based billing and have continued to see business and enterprise seat growth and also significant consumption revenue after the new model went into effect. Copilot revenue accelerated over 60% quarter over quarter. All up, GitHub now has 225 million users as organizations across every industry, including over 90% of the Fortune 500, choose GitHub for their AI-powered development.

談到開發者，GitHub Copilot 現在已有 5,000 萬名使用者。本季我們導入按使用量計費，且在新模式生效後，持續看到商務與企業席位成長，以及顯著的消耗型營收。Copilot 營收較上一季加速成長超過 60%。整體而言，GitHub 現在已有 2.25 億名使用者，涵蓋各行各業的組織（包括超過 90% 的《財富》500 大企業）選擇 GitHub 作為其 AI 驅動的開發平台。

The agentic era is being built on GitHub. Every major coding agent runs on the platform and one in three pull requests on GitHub now involves an agent.

代理式（agentic）時代正在 GitHub 上打造。每一個主要的程式碼代理都在該平台上運行，而 GitHub 上每三個拉取請求（pull request）就有一個現在會涉及代理。

In security, we are helping customers both secure their AI deployments and use AI to strengthen their security posture. To date, Purview has audited over 15 billion Copilot interactions to meet compliance obligations, up nearly 360% year over year. And earlier this week, we introduced Project Perception, a complete multimodal agentic security system that brings together teams of agents to simulate attacks, investigate threats, and drive remediation. As Perception moves beyond private preview, we expect to bring it to customers through a consumption-based offering.

在資安方面，我們同時協助客戶保護其 AI 部署，並運用 AI 強化其安全態勢。截至目前，Purview 已稽核超過 150 億次 Copilot 互動以滿足合規義務，年增近 360%。而在本週稍早，我們推出了 Project Perception——一套完整的多模態代理式資安系統，將多個代理團隊整合在一起，以模擬攻擊、調查威脅並推動修復。隨著 Perception 走出私人預覽，我們預期將透過消耗型（consumption-based）產品把它帶給客戶。

In healthcare, we are on pace to automate over 100 million patient encounters this calendar year, including 28 million this quarter, up 2x year over year. Mass General Brigham rolled out Dragon Copilot to over 4,000 providers, and after a study, found AmbientAI reduced burnout by 21%. And in Science, Microsoft Discovery, now broadly available, provides a comprehensive platform for building and governing agentic workflows for science and engineering. Early customers include BHP, GSK, Pacific Northwest National Lab.

在醫療保健方面，我們今年曆年有望自動化超過 1 億次病患就診互動，其中本季為 2,800 萬次，年增 2 倍。Mass General Brigham 已將 Dragon Copilot 推廣至超過 4,000 名醫療提供者，並在一項研究後發現 AmbientAI 將倦怠感降低了 21%。而在科學領域，Microsoft Discovery 現已全面可用，提供一個完整的平台，用於建置與治理面向科學與工程的代理式工作流程。早期客戶包括 BHP、GSK、Pacific Northwest National Lab。

Across both our high-value agentic experiences and the AI platform and infrastructure, we are focused on helping customers turn AI into measurable outcomes. The most comprehensive and valuable data in the world is inside each of the customer tenants, and therefore, there is a tremendous opportunity to turn customers' workflows, domain knowledge, and accumulated judgment into AI systems that learn and improve with every usage.

無論是在我們的高價值代理式體驗，或是 AI 平台與基礎設施方面，我們都聚焦於協助客戶將 AI 轉化為可衡量的成果。世界上最全面且最有價值的資料存在於每個客戶的租戶（tenant）之中，因此有巨大的機會把客戶的工作流程、領域知識與累積的判斷，轉化為能在每次使用中學習並持續改進的 AI 系統。

To help customers capture that opportunity, this month, we launched Microsoft Frontier Co., the largest outcome-driven engineering organization in the industry. We will embed 6,000 industry and engineering experts with customers to co-design, co-innovate, and continuously improve AI systems at scale. We've been testing this model over the past year, completing over 330 projects across 164 customers, including many of the world's leading companies across industries.

為協助客戶把握這個機會，本月我們成立了 Microsoft Frontier Co.，這是業界最大的以成果為導向的工程組織。我們將與客戶深度嵌入 6,000 名產業與工程專家，共同設計、共同創新，並以規模化方式持續改進 AI 系統。過去一年我們已在測試此模式，完成了橫跨 164 家客戶的 330 多個專案，其中包括許多跨產業的全球領先企業。

For example, our FDE teams worked with Novo Nordisk to build an agent that helps analyze clinical data while meeting its strict compliance requirements. And we partnered with LSEG to embed AI into LSEG Workspace, helping finance professionals ask complex questions and quickly find answers across structured and unstructured financial content.

例如，我們的 FDE 團隊與 Novo Nordisk 合作打造一個代理，協助分析臨床資料，同時符合其嚴格的合規要求。我們也與 LSEG 合作，將 AI 嵌入 LSEG Workspace，協助金融專業人士提出複雜問題，並在結構化與非結構化的金融內容中快速找到答案。

Finally, let me talk about devices and consumer. When it comes to Xbox, we are making the necessary decisions required across our content portfolio, platform, and operations to reset the business for long-term growth. We have the best IP in the industry and talented studios around the world and believe we can bring these strengths together and expect to return the business to growth in fiscal 2027.

最後，讓我談談裝置與消費者業務。就 Xbox 而言，我們正在針對內容組合、平台與營運做出必要決策，以重整業務、實現長期成長。我們擁有業界最強的 IP，以及遍布全球的優秀工作室，我們相信能把這些優勢整合起來，並預期在 2027 會計年度讓業務重回成長。

In Windows, we are investing to ensure that it has the best quality and fundamentals while also ensuring it's the best place to run secure edge AI. We see significant opportunity for Windows to become the offload for unmuted intelligence, combining powerful on-device compute with enterprise-grade security.

在 Windows 方面，我們持續投資以確保其具備最佳品質與基本面，同時也確保它是執行安全邊緣 AI 的最佳平台。我們看到 Windows 有顯著機會成為「未靜音智慧」（unmuted intelligence）的卸載端，結合強大的裝置端運算能力與企業級安全性。

In search and advertising, Bing and Edge have both taken share for five straight years. And LinkedIn continues to see strong engagement across the platform with double-digit member growth for the fifth consecutive year. Recruiters at over 20,000 companies are now using our AI-powered solutions to reduce time to hire and improve candidate matching. Seats increased to 140% quarter over quarter.

在搜尋與廣告方面，Bing 與 Edge 已連續五年持續提升市占。而 LinkedIn 也持續在整個平台上看到強勁互動，會員數連續第五年維持雙位數成長。目前已有超過 20,000 家公司的招募人員使用我們的 AI 驅動解決方案，以縮短招募時間並改善候選人配對。席位數較上一季增加至 140%。

In closing, I'm energized by the opportunities ahead. I've never been more confident in Microsoft's opportunity to drive durable long-term growth and ensure the benefits of AI flow broadly.

總結來說，我對前方的機會充滿動能。我從未如此有信心，Microsoft 有機會推動可持續的長期成長，並確保 AI 的效益能廣泛流向各方。

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

接下來，讓我把時間交給 Amy，請她說明我們的財務結果與展望。

Thank you, Satya, and good afternoon, everyone. This fiscal year, we delivered over $331 billion in revenue, with growth accelerating to 18%, driven by strong demand across both the Azure platform and our first-party AI applications and services. Operating income growth outpaced revenue growth, increasing 21% to more than $155 billion as we invested in long-term growth while continuing to expand operating leverage.

謝謝你，Satya，各位下午好。本會計年度，我們實現超過 3,310 億美元營收，成長加速至 18%，主要受 Azure 平台以及我們第一方 AI 應用與服務的強勁需求帶動。在我們投資長期成長、同時持續擴大營運槓桿之下，營業利益成長超越營收成長，增加 21% 至超過 1,550 億美元。

This quarter, revenue was $90 billion, up 18% and 17% in constant currency. Gross margin dollars increased 15%, and operating income increased 18%. Earnings per share was $4.74, an increase of 23% when adjusted for the impact from our investment in OpenAI. And FX was roughly in line with guidance.

本季營收為 900 億美元，年增 18%，以固定匯率計年增 17%。毛利金額增加 15%，營業利益增加 18%。每股盈餘為 4.74 美元，若調整我們對 OpenAI 投資的影響後，增加 23%。匯率（FX）大致符合指引。

Several discrete items impact our financial results in the quarter when compared to our forward-looking guidance provided on our April earnings call, resulting in a benefit of $0.27 on diluted earnings per share. These included a $3.2 billion gain from our investment in Anthropic and lower-than-expected expenses related to the voluntary retirement program, which were partially offset by severance expense and impairment charges in Xbox.

與我們在 4 月財報電話會議中提供的前瞻性指引相比，本季有數項個別項目影響了財務結果，使稀釋後每股盈餘增加 0.27 美元。其中包括我們對 Anthropic 的投資帶來 32 億美元收益，以及與自願退休方案相關的費用低於預期；上述部分被 Xbox 的資遣費用與減損費用所抵銷。

When adjusting for these items, we exceeded expectations across revenue, operating income, and earnings per share due to strong demand and execution in the quarter.

若排除這些項目，我們在營收、營業利益與每股盈餘方面皆超出預期，反映本季強勁需求與執行力。

Company gross margin percentage was 67%, down year over year driven by sales mix shift to Azure, as well as continued investments in AI infrastructure and growing product usage, partially offset by ongoing efficiency gains, particularly in Azure and M365 Commercial Cloud.

公司毛利率為 67%，年減主要受銷售組合轉向 Azure 影響，並反映我們持續投資 AI 基礎設施與產品使用量成長；部分則被持續的效率提升所抵銷，尤其是在 Azure 與 M365 商業雲。

Operating expenses increased 10%, driven by continued investment in R&D compute capacity, talent, and data to support product development across the portfolio. G&A growth was impacted by a low prior-year comparable as well as some of the discrete items mentioned earlier. Operating margins increased slightly year over year to 45%. Total company headcount declined 2% year over year.

營業費用增加 10%，主要因持續投資研發運算能力、人才與資料，以支援整體產品組合的產品開發。一般與管理費用（G&A）的成長受到去年同期基期較低以及前述部分個別項目的影響。營業利益率年增小幅上升至 45%。公司總人數年減 2%。

When adjusted for the impact of our investments in OpenAI, other income and expense was $2.8 billion, driven by the gain on investment in Anthropic noted earlier.

若調整我們對 OpenAI 投資的影響，其他收益與費用為 28 億美元，主要來自前述對 Anthropic 投資的收益。

Capital expenditures were $41 billion, including the impact from higher component pricing, as noted in our guide. Roughly two-thirds of our CapEx was for short-lived assets, primarily CPUs and GPUs, as customers increasingly build solutions that leverage both AI and non-AI infrastructure.

資本支出為 410 億美元，包含如我們在指引中所提及、因零組件價格上升帶來的影響。約三分之二的資本支出用於短年期資產，主要是 CPU 與 GPU，因客戶日益建置同時運用 AI 與非 AI 基礎設施的解決方案。

The remaining spend was for long-lived assets. This quarter, total finance leases were $5.6 billion and were primarily for large data center sites. And cash paid for PP&E was $35.8 billion.

其餘支出用於長期資產。本季，融資租賃總額為56億美元，主要用於大型資料中心場址。而用於不動產、廠房及設備（PP&E）的現金支出為358億美元。

Cash flow from operations was $55.4 billion, up 30%, driven by strong cloud billings and collections, partially offset by an increase in operating lease payments. And free cash flow was $19.6 billion, reflecting higher capital expenditures. And finally, we returned $10.2 billion to shareholders through dividends and share repurchases, bringing our total cash return to shareholders to over $43 billion for the full fiscal year.

營運活動現金流為554億美元，年增30%，主要受惠於強勁的雲端開立帳單與收款，部分被營業租賃付款增加所抵銷。自由現金流為196億美元，反映資本支出提高。最後，我們透過股利與股票回購向股東返還102億美元，使本財年全年對股東的現金回饋總額超過430億美元。

Now to our commercial results. Commercial bookings grew 18% when excluding the impact from OpenAI, driven by strong execution in our core annuity sales motions and reflecting broad customer demand across geographies and customer segments. Bookings increased 10% and 11% in constant currency when including Azure commitments from OpenAI.

接著談我們的商業業績。在排除OpenAI影響後，商業訂單（bookings）成長18%，主要來自我們核心年金型銷售動能的強勁執行，並反映跨地區與客戶區隔的廣泛需求。若納入OpenAI的Azure承諾，訂單在固定匯率下分別成長10%與11%。

Commercial remaining performance obligation grew 84% to $678 billion. All sequential commercial RPO growth was driven by commitments from customers outside of Frontier model companies. And RPO increased 25% when excluding OpenAI.

商業剩餘履約義務（RPO）成長84%至6,780億美元。所有商業RPO的季增，皆由非Frontier模型公司客戶的承諾所帶動。而在排除OpenAI後，RPO成長25%。

RPO, including OpenAI, has a weighted average duration of 2.3 years, and roughly 30% will be recognized in revenue in the next 12 months, up 37% year over year. The remaining portion recognized beyond the next 12 months increased 112%.

包含OpenAI在內的RPO加權平均期間為2.3年，約30%將於未來12個月內認列為營收，年增37%。在未來12個月之後認列的其餘部分增加112%。

Microsoft Cloud revenue was $59.3 billion and grew 27%, reflecting strong demand across Azure and our first-party AI applications and services. And for the full year, our Cloud revenue surpassed $214 billion, with nearly 90% from customers outside of Frontier model companies.

Microsoft Cloud營收為593億美元，成長27%，反映Azure以及我們第一方AI應用與服務的強勁需求。而就全年而言，我們的雲端營收超過2,140億美元，其中近90%來自Frontier模型公司以外的客戶。

Microsoft Cloud gross margin percentage was better than expected at 65% and down year over year, driven by sales mix shift to Azure as well as continued investments in AI infrastructure and increased product usage, partially offset by ongoing efficiency gains noted earlier.

Microsoft Cloud毛利率優於預期，為65%，且較去年同期下降，主要因銷售組合轉向Azure，以及持續投資AI基礎設施與產品使用量增加；部分被前述持續的效率提升所抵銷。

Now to our segment results. Revenue from Productivity and Business Processes was $37.8 billion and grew 14%. M365 commercial cloud revenue increased 16% on an adjusted basis when normalized for the prior-year comparable that benefited from 2 points of in-period revenue recognition. And on a reported basis, revenue growth was 14%.

接著看各事業群表現。生產力與商務流程（Productivity and Business Processes）營收為378億美元，成長14%。M365商業雲端營收在調整後基礎上成長16%，係將去年同期可比基期中受益於當期2個百分點營收認列的影響予以常態化。而按報導口徑，營收成長為14%。

Building on our Copilot momentum from Q3, net paid seat adds more than doubled sequentially, with paid seats now over 30 million. Premium offerings, including Copilot, E5, and early traction in E7, drove ARPU growth this quarter. And 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.

延續第三季Copilot的動能，付費席次淨新增較前一季增加逾一倍，付費席次目前已超過3,000萬。包含Copilot、E5以及E7初期進展在內的高階方案，帶動本季ARPU成長。而M365商業付費席次年增6%，各客戶區隔的裝機基礎均有擴張，但主要來自中小企業與第一線員工方案。

M365 commercial products revenue increased 19% ahead of expectations, driven by large, long-duration M365 contracts that resulted in higher end-period revenue recognition from the Windows Commercial on-premises component. M365 consumer cloud revenue increased 24% and 22% in constant currency, again driven by ARPU growth. And M365 consumer subscriptions grew 7%.

M365商業產品營收成長19%，高於預期，主要受大型、長期間的M365合約帶動，使Windows Commercial內部部署（on-premises）組件在期末的營收認列更高。M365消費者雲端營收成長24%，固定匯率下成長22%，同樣由ARPU成長所驅動。而M365消費者訂閱數成長7%。

LinkedIn revenue increased 12% and 10% in constant currency, primarily driven by Marketing Solutions. Dynamics 365 revenue increased 13% and 12% in constant currency against a strong prior-year comparable. Bookings growth in ERP remains healthy, while CRM continued to moderate with longer sales cycles.

LinkedIn營收成長12%，固定匯率下成長10%，主要由行銷解決方案（Marketing Solutions）帶動。Dynamics 365營收成長13%，固定匯率下成長12%，係在去年同期強勁可比基期下達成。ERP的訂單成長仍然健康，而CRM因銷售週期拉長而持續趨緩。

Segment gross margin dollars increased 14% and 13% in constant currency, and gross margin percentage decreased slightly with increased M365 Copilot usage as we continue to invest in product quality and drive further efficiency gains.

該事業群毛利金額成長14%，固定匯率下成長13%；毛利率因M365 Copilot使用量增加而小幅下降，我們持續投資產品品質並推動進一步的效率提升。

Operating expenses increased 11%, primarily driven by the shared R&D investments mentioned earlier. Operating income increased 15% and 14% in constant currency, and operating margins increased year over year to 58%.

營業費用成長11%，主要由前述共享的研發投資所驅動。營業利益成長15%，固定匯率下成長14%，營業利益率年增至58%。

Next, the Intelligent Cloud segment. Revenue was $39.3 billion and grew 32% and 31% in constant currency. In Azure and other Cloud Services, revenue grew 43% against the prior year that included accelerating growth. Customer demand continues to exceed available capacity.

接著是智慧雲端（Intelligent Cloud）事業群。營收為393億美元，成長32%，固定匯率下成長31%。在Azure及其他雲端服務方面，營收成長43%，對比去年同期包含加速成長的基期。客戶需求仍持續超過可用產能。

Revenue growth was ahead of expectations, driven by efficiency gains across our CPU and GPU fleet as well as process improvements to enable earlier delivery of new capacity. That additional in-quarter capacity for Azure was quickly monetized. Results also benefited from stronger-than-expected GitHub Copilot consumption following the June business model change to align pricing with usage and value.

營收成長高於預期，主要受惠於我們CPU與GPU機群的效率提升，以及流程改善以更早交付新增產能。Azure於本季新增的產能很快即被變現。在6月商業模式調整、使定價與使用量及價值更一致之後，GitHub Copilot的使用量高於預期，也帶動了本季表現。

In our on-premises server business, revenue was relatively unchanged year over year and was down 1% in constant currency. Results were ahead of expectations, primarily driven by renewals with higher in-period revenue recognition from the mix of contracts. Segment gross margin dollars increased 24%. And gross margin percentage decreased year over year, primarily driven by sales mix shift to Azure as well as the continued scaling of our AI infrastructure ahead of growing demand, partially offset by ongoing efficiency gains in Azure.

在內部部署伺服器業務方面，營收年比大致持平，固定匯率下下降1%。表現高於預期，主要由續約帶動，且因合約組合使當期營收認列更高。該事業群毛利金額成長24%。而毛利率年比下降，主要因銷售組合轉向Azure，以及在需求成長前持續擴大AI基礎設施規模；部分被Azure持續的效率提升所抵銷。

Segment gross margins were also impacted by growing GitHub Copilot usage, though margins improved through the quarter with the June business model change to usage-based pricing.

該事業群毛利亦受到GitHub Copilot使用量成長的影響，不過隨著6月商業模式改為按使用量計價，毛利率在本季內有所改善。

Operating expenses increased 10%, driven by shared R&D investments noted earlier. Operating income grew 31%, and operating margins, with a strong focus on efficiencies and investment returns, were relatively unchanged year over year at 41%.

營業費用成長10%，由前述共享的研發投資所帶動。營業利益成長31%；在高度聚焦效率與投資報酬之下，營業利益率年比大致持平，為41%。

Now to more Personal Computing. Revenue was $12.9 billion and (technical difficulty) and Windows OEM decreased 5%, driven by lower PC market demand and a high prior-year comparable that benefited from Windows 10 end of support. Results were ahead of expectations as OEM and channel partners continue to build inventory given increasing component prices.

接著是更多個人運算（More Personal Computing）。營收為129億美元，且（技術困難）Windows OEM下降5%，主要因PC市場需求較低，以及去年同期受惠於Windows 10終止支援而形成較高的可比基期。表現高於預期，因OEM與通路夥伴在零組件價格上漲的情況下持續建立庫存。

Search advertising revenue ex-TAC increased 10% and 9% in constant currency, with growth driven by higher revenue per search across Edge and Bing as well as higher volume. The growth was impacted by third-party partnerships.

搜尋廣告營收（扣除TAC）成長10%，固定匯率下成長9%，成長動能來自Edge與Bing每次搜尋的收入提高以及搜尋量增加。成長亦受到第三方合作夥伴關係的影響。

And at Xbox. Revenue decreased 10% and 11% in constant currency. Xbox content and services revenue decreased 10% against the prior-year comparable that benefited from strong first-party content performance.

再來是Xbox。營收下降10%，固定匯率下下降11%。Xbox內容與服務營收下降10%，對比去年同期受惠於強勁第一方內容表現的基期。

Segment gross margin dollars decreased 2%, and gross margin percentage increased year over year, driven by lower amortization from the Activision acquisition. Operating expenses increased 8% and 7% in constant currency, driven by the continued investments in shared R&D noted earlier as well as impairment charges in Xbox.

該事業群毛利金額下降2%，毛利率年比上升，主要因收購Activision後的攤銷費用降低。營業費用成長8%，固定匯率下成長7%，主要由前述持續投入共享研發，以及Xbox的減損費用所驅動。

Operating income decreased 14% and 15% in constant currency, and operating margins decreased year over year to 21%.

營業利益下降14%，固定匯率下下降15%，營業利益率年比下降至21%。

Now, before I move to outlook, effective at the start of FY27, we are extending the estimated useful life of our data centers and office buildings from 15 to 25 years, reflecting our operating history and expected use of these assets. The impact of this update is reflected in today's guidance.

現在，在我談到展望之前，自 FY27 年初起，我們將資料中心與辦公大樓的估計耐用年限由 15 年延長至 25 年，以反映我們的營運歷史以及對這些資產的預期使用情況。此項更新的影響已反映在今天的指引中。

This change affects only the timing of future depreciation and is expected to have a minimal benefit to FY27 operating income. The greater impact is on capital expenditures as more of our future data center leases will shift from finance leases to operating leases as a result of this update. Finance leases are included in capital expenditures while operating leases are not.

此變更僅影響未來折舊的認列時點，預期對 FY27 營業利益的助益極小。更大的影響在於資本支出，因為由於此項更新，我們未來更多的資料中心租賃將由融資租賃轉為營業租賃。融資租賃計入資本支出，而營業租賃則不計入。

Outside of this useful life impact, our calendar year 2026 CapEx investment expectations remain unchanged. However, the shift from finance to operating leases adjust our expectation to approximately $175 billion.

除上述耐用年限影響之外，我們對 2026 曆年 CapEx 投資的預期維持不變。然而，從融資租賃轉為營業租賃的變化，將我們的預期調整為約 1,750 億美元。

Now moving to our outlook. Let me start with some full-year commentary for FY27. First, some reminders. In both M365 commercial products and server products KPIs, we are lapping higher transactional purchasing from the timing of product launches and expect revenue from both to decline in the mid-single digits for the full fiscal year.

接下來談我們的展望。我先就 FY27 全年做一些說明。首先，提醒幾點。在 M365 商用產品與伺服器產品的 KPI 方面，我們正面臨去年因產品發表時點帶來較高交易型採購的高基期，預期兩者全年營收都將出現中個位數百分比的下滑。

Growth in Windows OEM and Devices will be impacted by lower PC market demand as higher component cost increased device pricing, a prior-year comparable that benefited from Windows 10 end of support and elevated inventory levels. As a result, we expect revenue to decline in the high-teens for the fiscal year.

Windows OEM 與裝置的成長將受到 PC 市場需求走弱的影響，因為較高的零組件成本推升裝置定價；此外，去年同期亦受惠於 Windows 10 終止支援以及較高的庫存水位。因此，我們預期本會計年度營收將下滑高十位數百分比。

Moving to FX. Assuming current rates remain stable, we now expect FX to decrease full year fiscal revenue growth by less than 1 point with no meaningful impact to COGS and operating expense growth. At the company level, with strong commercial momentum, we continue to expect another fiscal year of double-digit revenue and operating income growth.

接著談外匯。假設目前匯率維持穩定，我們現在預期外匯將使全年會計年度營收成長率減少不到 1 個百分點，對銷貨成本（COGS）與營業費用成長沒有顯著影響。在公司層級，憑藉強勁的商用動能，我們仍預期下一個會計年度營收與營業利益將維持雙位數成長。

Operating expenses should grow in the mid- to high single digits, reflecting continued investment in R&D compute capacity, talent, and data. And we expect FY27 capital expenditures will grow year over year given demand signals across our portfolio.

營業費用預計將以中到高個位數百分比成長，反映我們持續投資於研發運算能力、人才與資料。我們也預期 FY27 資本支出將因應我們產品組合各項需求訊號而較去年成長。

Even as we invest to meet growing demand, full fiscal year operating margins should be down less than 1 point. In addition, we expect to remain free cash flow positive in FY27. And finally, we expect our FY27 effective tax rate to be approximately 20%.

即使我們投資以滿足持續成長的需求，全年營業利益率預期下滑不到 1 個百分點。此外，我們預期 FY27 仍將維持自由現金流為正。最後，我們預期 FY27 的有效稅率約為 20%。

Now to the outlook for our first quarter, which unless specifically noted otherwise, is on a US dollar basis. Based on current rates, we expect FX to decrease total revenue growth by less than 1 point with no meaningful impact to COGS or operating expense growth. Within the segments, we expect FX to decrease revenue growth in productivity and business processes by roughly 1 point and Intelligent Cloud by less than 1 point. There is no meaningful impact in more personal computing.

接下來是第一季展望；除非另有特別說明，皆以美元為基礎。依目前匯率，我們預期外匯將使總營收成長率降低不到 1 個百分點，對銷貨成本或營業費用成長沒有顯著影響。在各事業群中，我們預期外匯將使生產力與商務流程的營收成長率降低約 1 個百分點，智慧雲端則降低不到 1 個百分點。更多個人運算則沒有顯著影響。

Starting with our commercial business. In commercial bookings, when adjusted for the impact from OpenAI, we expect healthy growth on a growing expiry base driven by strong execution across our core annuity sales motions. As a reminder, the significant OpenAI contracts signed in the prior year will result in some quarterly volatility in both bookings and RPO growth rates.

先從我們的商用業務開始。在商用訂單（bookings）方面，若調整 OpenAI 的影響，我們預期在到期基礎持續擴大的情況下，將維持健康成長，主要由我們核心年金型銷售動能的強勁執行所帶動。提醒一下，前一年簽署的重大 OpenAI 合約，將使訂單與 RPO 成長率在季度間出現一定波動。

Microsoft Cloud gross margin percentage should be relatively stable quarter over quarter.

Microsoft Cloud 毛利率百分比預期將較上一季大致持平。

Now to segment guidance. In Productivity and Business Processes, we expect revenue of USD36.7 billion to USD37 billion, a growth of 11% to 12%. In M365 Commercial Cloud, we expect growth of approximately 16% in constant currency on an adjusted basis, which normalizes for the prior-year comparable that benefited from 1 point of in-period revenue recognition, or 15% on a reported basis.

接著是各事業群指引。在生產力與商務流程方面，我們預期營收為 367 億至 370 億美元，成長 11% 至 12%。在 M365 商用雲端方面，按固定匯率並以調整後口徑（將去年同期受惠於 1 個百分點的當期營收認列影響予以正常化）計算，我們預期成長約 16%；按報導口徑則為 15%。

Sequential growth from our momentum in Copilot, E5, and E7 is mitigated a bit by the lower ARPU, new seat adds in frontline worker, and small and medium business SKUs. With the premium SKU momentum and the increased monetization opportunity from adding usage-based billing products alongside per seat licensing in July, we expect to see acceleration in M365 Commercial Cloud revenue growth through this fiscal year.

我們在 Copilot、E5 與 E7 的動能帶來的序列成長，部分被較低的 ARPU、第一線員工與中小企業 SKU 的新增席次所抵銷。隨著高階 SKU 動能，以及 7 月起在按席次授權之外加入按使用量計費產品所帶來的變現機會提升，我們預期本會計年度 M365 商用雲端營收成長將加速。

M365 Commercial products revenue should grow in the mid-single digits, driven by the timing of long-duration M365 contracts, partially offset by the impact from the prior-year comparable noted earlier. M365 consumer cloud revenue should grow in the mid-teens, down sequentially as we lapped the benefit from last year's price increase. Growth will again be driven by ARPU and an increase in subscription volume.

M365 商用產品營收預期將以中個位數百分比成長，主要受長期 M365 合約認列時點帶動，部分被前述去年同期比較基期影響所抵銷。M365 消費者雲端營收預期將以中十位數百分比成長，但因去年價格上調帶來的效益已過基期，序列成長將放緩。成長仍將由 ARPU 與訂閱量增加所帶動。

For LinkedIn, we expect revenue growth in the high single digits. And in Dynamics 365, we expect revenue growth to be in the low-teens, relatively stable quarter over quarter, driven by continued growth in ERP, although impacted by the bookings trends noted earlier.

LinkedIn 方面，我們預期營收成長為高個位數百分比。Dynamics 365 方面，我們預期營收成長為低十位數百分比，季度間相對穩定，主要由 ERP 持續成長帶動，但會受到前述訂單趨勢的影響。

For Intelligent Cloud, we expect revenue of USD40.95 billion to USD41.25 billion, or growth of 33% to 34%. In Azure, we expect revenue growth of approximately 45% in constant currency, and we remain focused on delivering efficiencies that help us bridge the gaps we see as customer demand continues to exceed supply.

智慧雲端方面，我們預期營收為 409.5 億至 412.5 億美元，成長 33% 至 34%。在 Azure 方面，按固定匯率我們預期營收成長約 45%；同時我們仍專注於提升效率，以協助縮小我們所見的缺口，因為客戶需求仍持續超過供給。

Even with the strong close to Q4, we continue to expect H1 growth to accelerate. And as a reminder, year-over-year Azure growth rates can vary quarter to quarter based on capacity, timing, and contract mix.

即使第四季收官強勁，我們仍預期上半年成長將加速。並提醒一下，Azure 的年增率可能因產能、時點與合約組合而在季度間有所波動。

In our on-premises server business, we expect revenue to decline in the low- to mid-single digits with ongoing customer shift to cloud offerings and the prior-year comparable noted earlier. In more Personal Computing, we expect revenue to be USD12.2 billion to USD12.7 billion as we continue to lap strong prior-year comparables noted earlier and navigate complex PC market dynamics impacted by component prices and inventory levels.

在我們的地端伺服器業務方面，隨著客戶持續轉向雲端產品，以及前述去年同期比較基期影響，我們預期營收將以低到中個位數百分比下滑。在更多個人運算方面，隨著我們持續面對前述強勁的去年同期比較基期，並因零組件價格與庫存水位影響而處於複雜的 PC 市場動態中，我們預期營收為 122 億至 127 億美元。

Windows OEM and Devices revenue should decline in the low-20s, driven by the market dynamics noted earlier. As in prior quarters, the range of potential outcomes remains wider than normal. Search advertising revenue ex-TAC growth should be in the mid-single digits, down sequentially due to the impact of third-party partnerships. Growth will continue to be driven by consistent trends in revenue per search and volume.

Windows OEM 與裝置營收預期將下滑約 20% 出頭，主要由前述市場動態所致。如同前幾季，可能結果的區間仍比正常情況更寬。搜尋廣告營收（不含 TAC）的成長預期為中個位數百分比，因第三方合作夥伴的影響而較上一季放緩。成長仍將由每次搜尋收入與搜尋量的穩定趨勢所帶動。

And in Xbox content and services, we expect revenue to decline in the mid-single digits. Hardware revenue should decline year over year. Therefore, at the total company level, revenue should be between USD89.85 billion and USD90.95 billion, or growth of 16% to 17%, with accelerating commercial growth partially offset by the impact from the PC market dynamics noted earlier.

Xbox 內容與服務方面，我們預期營收將以中個位數百分比下滑。硬體營收預期將年減。因此，在公司整體層級，營收預期介於 898.5 億至 909.5 億美元之間，成長 16% 至 17%；商用成長加速將部分抵銷前述 PC 市場動態的影響。

We expect COGS of USD29.6 billion to USD29.8 billion, or growth of 23% to 24%. And operating expense of USD16.8 billion to USD16.9 billion, a growth of 7% to 8%, driven by continued investment in R&D compute capacity and talent. Operating margins should be relatively flat year over year. Excluding any impact from our investments in OpenAI, other income and expense is expected to be roughly negative $100 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 Q1 effective tax rate to be approximately 20%.

我們預期銷貨成本（COGS）為 296 億至 298 億美元，成長 23% 至 24%。營業費用預期為 168 億至 169 億美元，成長 7% 至 8%，主要由持續投資於研發運算能力與人才所帶動。營業利益率預期將較去年大致持平。若不計我們對 OpenAI 投資的任何影響，其他收益與費用預期約為負 1 億美元，因利息收入將被利息費用（包含與資料中心融資租賃相關的利息支付）所抵銷並超過。我們預期第一季有效稅率約為 20%。

Next, capital expenditures. We expect CapEx spend will be over $50 billion, including the lease reclassification impact from the useful life update.

接下來是資本支出。我們預期資本支出（CapEx）將超過500億美元，其中包含因使用年限更新而產生的租賃重分類影響。

In closing, in FY26, we delivered accelerating revenue and operating income growth while expanding operating margins. Our execution across sales and product engineering strengthened through the second half of the year. As we begin FY27, we remain focused on delivering products that create meaningful return on investment for our customers, which will result in durable long-term growth for Microsoft and our shareholders.

總結來說，在FY26，我們在擴大營業利益率的同時，實現了營收與營業利益加速成長。我們在銷售與產品工程方面的執行力於下半年進一步強化。在開始FY27之際，我們仍專注於提供能為客戶創造具意義投資報酬率的產品，這將為微軟及我們的股東帶來穩健且長期的成長。

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

接下來我們進入問答環節，Jonathan。

Thanks, Amy. We'll now move over to Q&A. Out of respect for others on the call, we request that participants please only ask one question. Operator, can you please repeat your instructions?

謝謝，Amy。我們現在進入問答環節。為尊重其他與會者，我們請參與者每次僅提一個問題。接線員，請您重複說明指示。

(Operator Instructions) Karl Keirstead, UBS.

(接線員指示) Karl Keirstead，瑞銀（UBS）。

Satya, maybe I'll start away from the numbers and ask if you could spend a minute and elaborate on your opening comments about model choice and the protection of corporate IP. Maybe I could ask this in two parts.

Satya，也許我先不從數字切入，想請你花一點時間延伸說明你在開場談到的模型選擇以及企業智慧財產（IP）保護。我想把這個問題分成兩個部分。

First, how material do you think traction could be for open and custom models over the next year or two, knowing that many enterprises might be initially reticent to use open models? And secondly, how exactly does Microsoft benefit from this shift knowing that you've also got fairly large Frontier Lab exposure? Thanks so much.

第一，在未來一到兩年內，你認為開放模型與客製模型的採用動能會有多大？考量到許多企業一開始可能會對使用開放模型有所顧慮。第二，鑑於你們也相當程度地曝險於Frontier Lab，你們如何從這樣的轉變中受益？非常感謝。

Thank you, Karl. So the way we are coming at this is, at the end of the day, the goal is to have the firm be in control of their own destiny in terms of what I describe as building their human capital and their token capital, right? So at the end of the day, if a firm is a learning machine, they need their own learning machine. And that's sort of really the goal.

謝謝你，Karl。我們的切入方式是：歸根結底，目標是讓企業能掌控自己的命運，我所說的是在打造其人力資本與其「token資本」方面的掌控權，對吧？所以到最後，如果一家企業是一部學習機器，它就需要自己的學習機器。而那正是我們真正的目標。

And the models are an input, not some extraction of the knowledge of the enterprise. But in some sense, you have to really -- at the end of the day, every firm is going to evaluate who are the providers who are helping them with their outcomes and their knowledge creation. I think that that is now fairly clear, and it's going to become clearer by the day. This is not going to be about come in and take all my knowledge and benefit yourself, whereas I am not getting any output.

模型是一種輸入，而不是把企業知識抽取走的工具。但某種意義上，你必須真正——到最後，每一家企業都會評估：哪些供應商在協助他們達成成果與創造知識。我認為這點現在已相當清楚，而且會一天比一天更清楚。這不會是「我進來把你的知識全拿走、自己受益，而你卻得不到任何產出」的模式。

So given that direction of travel, we are very, very clear about the architectural sort of design of the platform, which is you've got to keep your harness separate from the model. When the harness will ensure that your memory, your context, all of that is external. That means any given model at any given time is swappable. You should and you can use Frontier models. There's no reason not to.

因此，基於這樣的趨勢方向，我們對平台的架構設計非常、非常明確：你必須讓你的harness與模型分離。harness將確保你的記憶、你的脈絡（context）等都在外部。這表示在任何時間點，任何模型都可以被替換。你應該、也可以使用Frontier模型。沒有理由不使用。

But you also can use multiple of them, right? So if you look at some of the stats I gave, it's a great example of how to use the Frontier models for what they deliver, how to use low-cost models for what they deliver, and in fact, train your own model when you don't want to use any external model itself. Because after all, you have all the output, you have all the traces, you have all the context.

但你也可以同時使用多個模型，對吧？如果你看我提供的一些數據，那就是一個很好的例子：如何針對Frontier模型的強項使用它、如何針對低成本模型的強項使用它，甚至在你不想使用任何外部模型時訓練自己的模型。因為畢竟，你擁有所有輸出、所有軌跡（traces）、以及所有脈絡。

That's really the enterprise design architecture that we are going to evangelize. We ourselves using it. Copilot is built that way. GitHub Copilot is built that way. Our security Copilot is built that way. And we want to democratize that design pattern so that every enterprise can use it.

這就是我們要大力推廣的企業設計架構。我們自己也在使用。Copilot就是以這種方式建構的。GitHub Copilot也是以這種方式建構的。我們的Security Copilot也是以這種方式建構的。我們希望把這種設計模式普及化，讓每一家企業都能使用。

And within that, there will be a mix of open weights, closed weights. And by the way, one of the things that we talked about is, remember, right, if you look even at the Hugging Face incident, the biggest thing that we should take away from that is you can't sort of depend on any one model. You will maybe need multiple models to even remediate some challenges that get caused by one model, right? That's the way to think about it, which is you can't be subject to the refusal of one model.

而在這之中，會同時存在開放權重與封閉權重的組合。順帶一提，我們談到的一點是：記得，如果你甚至回頭看Hugging Face事件，我們應該得到的最大教訓是，你不能只依賴單一模型。你可能需要多個模型，甚至用來修復（remediate）某個模型所造成的一些挑戰，對吧？思考方式就是如此：你不能受制於某一個模型的拒絕（refusal）。

So there's a lot more design space here. We talk about the Frontier as if it's one thing. The Frontier is about every firm having a Frontier and the choice, the cost control, and the capability that they need in order to be able to control the destiny.

所以這裡的設計空間大得多。我們談Frontier時，好像它是一個單一事物。Frontier的核心在於：每一家企業都擁有自己的Frontier，以及他們為了掌控自身命運所需要的選擇權、成本控管與能力。

And I think maybe, Karl, just to add a little bit to the end of your question, which is that it's why it's important that the platform is built. And I think Satya mentioned this in his comments. To be able to deliver the right model for the right job on the architecture called Azure. And so, given that we continue to see growing demand. No matter what model is chosen or what model family or whether it's run a model of your own, the Azure platform is quite efficient at delivering that. So think about that infrastructure as being pretty fungible.

我想，Karl，也許再補充你問題的最後一部分：這也是為什麼建構平台很重要。我想Satya在他的評論中也提到這點。要能在名為Azure的架構上，為正確的工作提供正確的模型。因此，鑑於我們持續看到需求成長，無論選擇哪一種模型、哪一個模型家族，或是是否運行自有模型，Azure平台都能相當有效率地交付。所以把那個基礎設施視為相當可互換（fungible）的。

Thanks, Karl. Operator, next question, please.

謝謝你，Karl。接線員，請下一題。

Brent Thill, Jefferies.

Brent Thill，Jefferies。

Amy, impressive acceleration in Azure, up to 43% going to mid-40s. I guess the questions around the underlying drivers, what you and Satya are seeing in terms of just what's driving this and many of the questions around capacity constraints. Are we just still in the same environment? Or is this Microsoft just executing better given the constraints we're all seeing? Thanks.

Amy，Azure成長加速令人印象深刻，達到43%，並且指引到40%中段。我想問題在於背後的驅動因素：你和Satya觀察到究竟是什麼在推動這個表現，以及大家也很關注的產能限制問題。我們是否仍處於相同的環境？還是說在我們都看到的限制之下，微軟只是執行得更好？謝謝。

Thanks, Brent. First, there are still constraints in the system. I think we've continued to say, I think, now for a number of quarters that demand continues to exceed available supply. And that certainly remains true. You can even see it, I think, in some of the pricing that's occurring in the spot market for assets.

謝謝，Brent。首先，系統中仍然存在限制。我想我們已經持續說了好幾個季度：需求仍然超過可用供給。而這點確實依然如此。你甚至可以從某些資產在現貨市場的定價中看出來。

So when you think about being able to deliver better, the first thing we focus on, and I tried to talk a little bit about it in my prepared remarks, is efficiency. Being able to get more out of everything that we've got in the fleet. That applies to efficiency gains in the CPU fleet. It's going to be efficiency gains in the GPU fleet.

因此，談到如何交付得更好，我們首先聚焦的——我也在事先準備的講稿中稍微提到——是效率。也就是能從我們現有的整個機群（fleet）中榨取更多產出。這適用於CPU機群的效率提升。也會是GPU機群的效率提升。

We saw a good work this quarter in particular from our engineering teams to make as much of that available as we could. And because of the supply-demand imbalance we've been talking about, when we can make efficiency gains, they are quickly monetized in quarter. And I think that dynamic certainly impacted the quarter positively.

本季度我們看到工程團隊做了很好的工作，特別是在盡可能把這些資源釋出可用性方面。而由於我們一直在談的供需失衡，當我們能取得效率提升時，往往會在當季迅速變現。我認為這種動態確實對本季度帶來了正面影響。

I would also say some of the process improvements we've made to make sure both CPUs and GPUs just the lead time from how quickly we can get things to simplify it tremendously plugged in was also improved over the past 90 days. And so, those improvements, again, are very quickly monetized and we're able to do that. And at the scale that we're operating in terms of across the entire hyperscale fleet, making efficiency improvements that can be quickly monetized as a result and acceleration in the quarter, it's part of also what we expect to see and talk about with Q1.

我也想說，我們在流程上的一些改進——確保 CPU 與 GPU 的交期，以及從我們能多快把東西接上線、並大幅簡化的角度——在過去 90 天也有所提升。因此，這些改進同樣能非常快速地變現，我們也做得到。而以我們目前在整個超大規模機群的營運規模來看，能做出可快速變現的效率提升，並在本季帶來加速，這也是我們預期在 Q1 會看到並會談到的一部分。

Thanks, Brent. Operator, next question, please.

謝謝你，Brent。接線員，請下一題。

Mark Moerdler, Bernstein Research.

Bernstein Research 的 Mark Moerdler。

Congratulations on the solid, really great quarter. Satya, Amy, sentiment around AI remains incredibly volatile, with concerns about oversupply coming as well as concerns about component pricing increasing impacting margins.

恭喜本季表現穩健、非常出色。Satya、Amy，市場對 AI 的情緒仍然極度波動，一方面擔心供給過剩，另一方面也擔心零組件價格上漲會影響毛利率。

Amy, two related questions. How does Microsoft protect itself if there really is overcapacity and overbuilding of data centers or overbuilding of chips, et cetera? And on the flip side of that, how do you manage through the hardware price increases that we're seeing, the component prices, and that it doesn't just drive you to either massively drive up the price of your offerings or negatively impact your margins? Thank you.

Amy，兩個相關問題。如果資料中心過度擴建、或晶片等出現過度供給與過度建置，微軟如何保護自己？反過來說，面對我們看到的硬體價格上漲、零組件價格上漲，你們如何管理，讓它不至於迫使你們要大幅提高產品報價，或對毛利率造成負面影響？謝謝。

Thanks, Mark. The questions are a little bit related, but I'll start with maybe the first. Currently, the situation is obviously, that demand exceeds available supply in a sort of relatively extreme moment. But when you start to think about over the duration, I try to remind people, a lot of the expense, especially you see it in CapEx, you've seen our CapEx really pivot toward what I would call and do call short-lived assets, which really, right, that CPUs and GPUs that have relatively shorter lead times. And so, if the demand environment changes, you just slow down what is, in fact, the largest component and the driver of COGS.

謝謝你，Mark。這兩個問題有點相關，但我先從第一個開始。目前的情況顯然是，在一個相對極端的時點，需求超過可用供給。但當你開始從較長期間來思考時，我會提醒大家，很多支出——尤其你在資本支出（CapEx）上看到的——我們的 CapEx 已經明顯轉向我所稱、也一直稱為「短壽命資產」，也就是交期相對較短的 CPU 與 GPU。因此，如果需求環境改變，你只要放慢實際上最大、也是成本（COGS）驅動因素的那一部分。

The investment into land and data center builds is actually quite flexible, right? It's a smaller percentage of the overall cost structure. And it can be -- timing can be changed on much of that, especially on the build, or you can stagger the timing of the build-out of, as I was saying, some of the GPUs and CPUs that you plan to put in. And so, when you think about being able to manage through that, hyperscalers have been doing that for quite a long time in terms of having the flexibility and the understanding of manage those changes in demand.

對土地與資料中心建置的投資其實相當有彈性，對吧？它在整體成本結構中占比更小。而且其中很多項目的時程都可以調整，尤其是建置本身；或者你也可以錯開建置時程——就像我說的——把你計畫要放進去的一些 GPU 與 CPU 的導入時點分批安排。因此，談到如何管理這些情況，超大規模雲端業者在面對需求變化時，長期以來一直都在這樣做，也具備相應的彈性與理解。

And the other thing that's important, Mark, is you just have an incredibly diverse book of business by geo, by segment, by industry. And I feel like when you look even at our backlog or what we added in RPO this quarter, it is from the breadth of really the Microsoft product portfolio as well as our customer portfolio.

另外一個很重要的點，Mark，是你擁有非常多元的業務組合：按地理區域、按客群區隔、按產業別都很分散。而且我覺得，即使你看我們的待履約訂單（backlog）或本季新增的 RPO，也都來自微軟產品組合的廣度，以及我們客戶組合的廣度。

So when you have the ability to late bind some of the more expensive components in the short term, you have a big book of business that's flexible, you have a big first-party app business that also uses the capacity that you're building out in addition to your Azure platform, it does allow us to have a lot more flexibility to manage through those.

所以，當你能在短期內對一些較昂貴的零組件採取「延後綁定」（late bind），同時又有一個具彈性的龐大業務組合，還有一個大型的第一方應用業務，除了 Azure 平台之外也會使用你正在擴建的產能，這確實讓我們在管理這些情況時有更大的彈性。

When it comes to the pricing question, I think that's really impacting everybody equivalently in so many ways. What we've been trying to do, of course, at this point is to just make sure that we're doing the best efficiency work we can so we can continue to give customers great value. We're reminding people that, frankly, the cloud offers tremendous benefits versus having to make these purchases as servers on-prem yourself where the price increases are even more hard for customers. So the cloud still provides a great ROI in those types of situations.

至於定價問題，我認為在很多方面這對所有人造成的影響其實都差不多。我們目前當然努力要做的，是確保把效率工作做到最好，讓我們能持續為客戶提供很高的價值。我們也提醒大家，坦白說，相較於客戶自己在本地端購買伺服器（on-prem）——而那種情況下價格上漲對客戶更難承受——雲端提供了巨大的好處。因此，在這類情境下，雲端仍然能提供很好的投資報酬率（ROI）。

And we're adding this capacity, to your point, but a lot of this, obviously, is also being sold in newer contracts, and we're able to have the pricing reflected the keep value where we -- listen, for the long term, you want to have pricing work for customers and for you. And so, we're trying to stay focused on that as well.

而且如你所說，我們正在增加這些產能，但其中很大一部分顯然也會透過較新的合約售出，我們也能在定價上反映、並維持價值——聽著，長期來看，你希望定價對客戶與對你自己都能行得通。所以我們也努力把焦點放在這一點上。

And if I just add to Amy's comments. I thought, and we captured it well. All of us are reading this 1873 as the book to be read. And so, in my mind, I think you've got to get the product shape right. That's sort of a lot of what we are focused on.

我再補充 Amy 的評論。我覺得我們已經把它掌握得很好。我們大家都在讀《1873》，把它當作必讀的一本書。所以在我看來，你必須把產品形態（product shape）做對。這也是我們專注的很大一部分。

You have to get the portfolio right. Amy talked about how -- what we're doing, whether it's in Copilot or the super app, bringing all the form factors or all the way to Azure and the agent-first sort of primitives in Azure, you kind of have to really get that portfolio to all come together.

你也必須把產品組合（portfolio）做對。Amy 談到我們正在做的事情——不論是在 Copilot 或超級應用（super app）上，把所有的裝置形態整合起來，或一路延伸到 Azure，以及 Azure 中以代理（agent-first）為先的各種基礎元件（primitives）——你必須讓整個產品組合真正整合到位。

The mix of customers is super important. You have to recognize the breadth, the geo mix, the segment mix, the workload mix, and you got to really think about all of those when you're even building capacity. And then you've got to run an efficient railroad.

客戶組合的混合（mix）非常重要。你必須認知到其廣度：地理分布的 mix、區隔的 mix、工作負載的 mix；甚至在建置產能時，你也必須把這些都納入考量。然後你必須把營運做得像高效率的鐵路系統一樣。

At the end of the day, you do need to -- Amy talked a little bit about even in the last quarter, how we've improved on the efficiency front. It's not something that will just show up at the end. You have to sort of monotonically work at it. And so, we are very focused on all of those.

歸根結底，你確實需要——Amy 也稍微提到，即使在上一季，我們在效率面已經有所改善。這不是那種最後才會突然顯現的事情。你必須以單調遞進的方式持續投入改善。因此，我們非常專注在所有這些面向。

And then we know that there will be ups and downs of what is the cycle here. But the secular shift is clear, and we're very bullish about us coming with the right sort of mix of business and the right margin structure, and most importantly, with the right value for our customers.

而且我們也知道，這個循環一定會有起起落落。但長期結構性的轉變（secular shift）很清楚，我們對於以正確的業務組合、正確的毛利結構來推進非常樂觀；最重要的是，為客戶提供正確的價值。

Thanks, Mark. Operator, next question, please.

謝謝你，Mark。接線員，請下一題。

Adam Wood, Morgan Stanley.

Morgan Stanley 的 Adam Wood。

Congrats on a very strong end of the year. I wanted to maybe just ask about M365 Copilot. Obviously, very strong quarter there with over 30 million paid seats and a strong acceleration. Could you just talk a little bit about how you're seeing customers move from pilots to broader deployments there? Is this still a pilot-driven motion or are we seeing a lot more broader deployments?

恭喜在年底交出非常強勁的成績。我想問一下 M365 Copilot。顯然本季表現非常強，付費席次超過 3,000 萬，而且加速成長很明顯。你能否談談你們如何看到客戶從試點（pilot）走向更大範圍的部署？這仍然主要是由試點驅動的推進方式，還是我們看到更多更廣泛的部署？

And then when we think about the monetization of the product in terms of additional seats migration to higher-value SKUs like E7 and then consumption, what do you see as the main monetization or the main driver of monetization from here, please? Thank you.

另外，當我們思考產品變現時——包括新增席次、升級到像 E7 這類更高價值的 SKU，以及用量（consumption）——你認為接下來最主要的變現來源或變現驅動因素是什麼？謝謝。

No, thank you, Adam, for that question. So let me start, and then Amy can add. I think, yeah, it starts with, again, that product shape. As you can see, even within the quarter, the product shape has changed pretty dramatically, right? So we now have chat, Cowork, Autopilot code all coming to essentially what is going to become this flagship super app that various roles can use it.

不，謝謝你，Adam，這個問題。我先回答，然後 Amy 可以補充。我想，是的，還是從產品形態（product shape）開始。如你所見，即使在本季之內，產品形態也有相當劇烈的變化，對吧？所以我們現在把聊天（chat）、Cowork、Autopilot code 都整合進來，基本上會成為這個旗艦級的超級應用（super app），讓不同角色都能使用。

And if you think about even the usage side, that's a place where, again, lots of interesting data there, right, which is time to usage has drastically come [down]. What used to be months is days, right? So when a license is bought to usage. The usage intensity itself has gone up significantly. I mean, we are talking about usage intensity that's sort of at the same level of what is an everyday communication tool like Outlook or Teams.

而且如果你連使用端也一起思考，那也是一個同樣有很多有趣數據的地方，對吧，也就是從購買到開始使用的時間已經大幅[縮短]。以前要好幾個月，現在是幾天，對吧？也就是從買了授權到開始使用。使用強度本身也顯著提升。我的意思是，我們談的是使用強度大致已經到達像 Outlook 或 Teams 這種日常溝通工具的同一個等級。

The second thing I would say is the overall enterprise wiring of this, right? So it's not like a tool that's isolated somewhere, but it's wired in, whether it is you brought up E7, right? So it's wired into the governance thesis with Agent 365, so then you have your ITOps, SecOps, FinOps, all wired in as well as it's all the business processes.

第二點我想說的是整體企業層面的佈線與整合，對吧？所以它不是某個地方孤立存在的工具，而是被整合進來的；不管是你提到的 E7，對吧？因此它被接到 Agent 365 的治理主張裡，接著你的 ITOps、SecOps、FinOps 也都一起接入，並且也涵蓋所有的業務流程。

So for example, your CRM system, your ERP system, all of them are just skills and plug-ins that go into Cowork. So you're able to take that enterprise-wide work workflow and wire it into the super app, right? That increases usage. So it all compounds.

例如，你的 CRM 系統、你的 ERP 系統，它們全都只是技能與外掛，接到 Cowork 裡。所以你能把企業範圍的工作流程接到這個超級 App 裡，對吧？那會提高使用量。所以一切都會疊加放大。

And then the other one is the business model. So we now have this per seat business model, and so we also now have the usage business model, so it's seat-plus usage. So we're already seeing the ARPU growth that comes from things like E7. But really, as we deliver more value to customer and customer outcomes at the enterprise level. In fact, if I think about historically Office compared to what Copilot is, is much more narrow. This is the first time where you really have an enterprise-wide tool which has a both per seat and usage-based pricing.

然後另一個是商業模式。所以我們現在有這種按席位（per seat）的商業模式，同時我們也有使用量（usage）的商業模式，所以是席位加使用量。因此我們已經看到像 E7 這類產品帶來的 ARPU 成長。但真正關鍵在於，當我們在企業層級為客戶交付更多價值與成果時。事實上，如果我回頭看歷史上 Office 相較於 Copilot，是更狹窄的。這是第一次你真正擁有一個企業範圍的工具，同時具備按席位與按使用量計價。

So the TAM is much more expansive. We're going to be very, very focused on driving customer value and then expanding with it.

所以 TAM 會大得多。我們會非常、非常專注於推動客戶價值，並隨之擴張。

Yeah, Adam. And I think I talked a little bit about it in my prepared remarks. But I do think what we've been seeing is, over the course of this year, some of the growth in ARPU was from E5 plus the Copilot license that Satya is talking about. We'll see a little bit more from E7 really has a lot of interesting value in the Agent 365 component, in particular.

是的，Adam。我想我在事先準備的發言裡也稍微提到過。但我確實認為，我們今年看到的 ARPU 成長，有一部分來自 E5 加上 Satya 所談到的 Copilot 授權。我們也會從 E7 看到更多一些，因為它在 Agent 365 的組件上有很多有趣的價值，尤其是。

Where Satya is talking about, I mean, having SecOps and FinOps think about, in general, everyone is going to need both observability of token spend and the manageability of token spend for all business processes. And that is what E7 brings. And so, I think that is -- it was only in market for a part of the quarter, and I think we were quite encouraged by the value customers saw in that SKU. I think we'll continue to focus on that through the year.

就像 Satya 在說的，我的意思是，讓 SecOps 和 FinOps 去思考，一般而言，每個人都會需要對所有業務流程的 token 支出具備可觀測性，以及 token 支出的可管理性。而這正是 E7 帶來的。所以，我認為那就是——它只在本季的一部分時間上市，而我們對客戶在那個 SKU 上看到的價值感到相當鼓舞。我想我們會在今年持續聚焦於此。

And then finally, what Satya is talking about is this building TAM that grows through the year. And as I think about that expensive spending TAM, that's really where we're talking about this usage and consumption growth. And so, as more of those experiences get wired in and as IT gets more involved in that process, it will be quite, I think, changing in terms of what people think of the M365 capabilities.

最後，Satya 談到的是這個在一年中持續成長的 TAM。而當我想到那個龐大的支出 TAM，那其實就是我們在談的使用量與消耗的成長。因此，隨著更多這些體驗被接入，以及 IT 更深入參與這個流程，我認為這將會相當改變人們對 M365 能力的看法。

And it would be fun for you, Adam. I think one of your colleagues put out an ROIC document. So I took that document to Copilot, which is a PDF. And I said, build me a new sort of PowerBI dashboard essentially. But here is the thing. It built a rich semantic model that went into my fabric with one lake that brought all the data in from the external sources, in fact, was current with all the SEC filings of all the MAG7. And then on top of that, the repo itself is in GitHub.

而且這對你來說會很有趣，Adam。我想你的一位同事發了一份 ROIC 文件。所以我把那份文件（PDF）丟給 Copilot。我說，基本上幫我建立一個新的 PowerBI 儀表板。但重點是：它建立了一個豐富的語意模型，進到我的 Fabric，透過 OneLake 把所有外部來源的資料都匯入；事實上，它還與所有 MAG7 的 SEC 申報保持同步更新。然後在那之上，repo 本身在 GitHub。

But the artifact is sitting in my Copilot as a site. That, to me, is a classic example of an enterprise-wide workflow (inaudible) a knowledge worker could go create a dashboard. The data engineer can go to fabric and find the artifact. The professional developer can go to the repo and find it in GitHub. And by the way, it's all registered with Agent 365, right? That's a little bit of what Amy is describing as they're coming together of a new way to work even while at the same time, bringing IT, security and manageability of it.

但這個成品（artifact）是以一個站點的形式放在我的 Copilot 裡。對我來說，這就是一個典型例子：企業範圍的工作流程（聽不清）讓知識工作者可以去建立一個儀表板。資料工程師可以到 Fabric 去找到這個成品。專業開發者可以到 repo，在 GitHub 裡找到它。而且順帶一提，它全部都已在 Agent 365 註冊，對吧？這有點像 Amy 所描述的：它們正在匯聚成一種新的工作方式，同時也把 IT、安全性與可管理性帶進來。

Thanks, Adam. Operator, next question, please.

謝謝你，Adam。接線員，請下一題。

Brad Zelnick, Deutsche Bank.

Brad Zelnick，德意志銀行。

Satya, appreciating cybersecurity is so core to everything Microsoft does. The playing field shifted recently with the latest Frontier model releases. And this week, you introduced Project Perception. Can you expand on what this moment means for your cyber business explicitly and also what it means for trust in Microsoft more broadly? Thanks.

Satya，鑑於資安是微軟所做一切的核心。隨著最新 Frontier 模型的發布，競爭格局最近出現了變化。而本週你們推出了 Project Perception。你能否更明確地談談這個時刻對你們資安業務的意義，以及更廣泛而言對外界信任微軟意味著什麼？謝謝。

Yeah. Thank you for that question. I think you're right about saying that the entire, I would say, the overall physics of how both what is needed in terms of the cyber product and even the cyber operations, because at the end of the day, you kind of have to sort of transform yourself on both the products, but also how you operate as a company to protect yourself have changed pretty dramatically.

是的。謝謝你的問題。我想你說得對：整體而言，我會說，不論是在資安產品需要什麼、甚至資安營運本身的「物理法則」都變了；因為歸根結底，你必須在產品上轉型，同時也要在公司如何運作以保護自己這件事上轉型，而這些都已經相當劇烈地改變了。

So what we are focused on is, first, again, take the same approach we have taken for knowledge work or coding, which is you've got to start with an intelligence-first, model-forward approach. And so, what we launched with Perception is essentially saying, let's sort of really make sure that you have the red team agents that know how to find -- constantly are red teaming and finding the vulnerabilities.

所以我們聚焦的是，第一，仍然採取我們在知識工作或寫程式上採取的同樣方法：你必須從 intelligence-first、model-forward 的方法開始。因此，我們在 Perception 推出的本質上是在說：我們要真正確保你擁有紅隊代理（red team agents），他們知道如何找出——持續進行紅隊演練並找出弱點。

Then you have the blue team agent that is constantly going and making sure that you're triaging, and the green team that fix this. So you kind of create your own agentic system that's continuously operating to create the cyber defense unique.

接著你有藍隊代理（blue team agent），持續確保你在做分流與處置（triaging），以及綠隊來修復這些問題。所以你等於建立了一套你自己的代理式系統（agentic system），持續運作，打造獨特的資安防禦。

It does definitely feeds off of all the signals, right? Whether it's the defenders, it's identity and trust signal, the defender signal, the network signal, the app security signal, all that's sort of helping really do the context so that you can then truly create the protection.

它確實會利用所有的訊號，對吧？不論是 Defender、身分與信任訊號、Defender 訊號、網路訊號、應用程式安全訊號，所有這些都在幫助建立情境脈絡，讓你能真正形成防護。

The other thing they also said is, especially in cyber, it becomes critical to have that multi-model approach to sort of the first question that was asked. Not just for cost. In fact, we proved with the MDASH data in CyberGym that essentially, you can have Mythos level performance with 50% less cost because of this MAI Cyber-Flash-1 (sic - "MAI-Cyber-1-Flash").

他們另外也提到的是，特別是在資安領域，採用多模型（multi-model）的方法會變得至關重要，回到第一個被問到的問題。不只是為了成本。事實上，我們用 CyberGym 裡的 MDASH 數據證明了：基本上，因為這個 MAI Cyber-Flash-1（原文如此——「MAI-Cyber-1-Flash」），你可以用少 50% 的成本達到 Mythos 等級的效能。

And the reason is because 90% of the tasks are done by the Cyber-Flash-1 (sic - "Cyber-1-Flash") model, and 10% of the tasks, you still go to the Frontier, right? So this is sort of that mixing of the right model for the right task in what is essentially a pipeline job is a super important characteristic. And so to us, I think this is an important piece.

原因在於，90%的任務由 Cyber-Flash-1（原文如此—「Cyber-1-Flash」）模型完成，而剩下10%的任務，你仍然會交給 Frontier，對吧？因此，這種在本質上屬於管線式作業（pipeline job）的流程中，為正確的任務搭配正確的模型的混用方式，是一個極其重要的特性。所以對我們而言，我認為這是一個重要的部分。

And the other thing I'd say is from a resilience perspective. For whatever reason, if a given model goes away, then you kind of can't be left high and dry. You need to be able to still continue your cyber operations. And that's the other piece.

另外我想說的是，從韌性（resilience）的角度來看。無論出於什麼原因，如果某個特定模型不可用了，那你就不能陷入束手無策的狀態。你仍需要能夠持續進行你的資安作業。這也是另一個重點。

So it's cost and resilience is both an important criteria. And that's what we are trying to build in, whether it's in code, whether it's in cyber, whether it is in knowledge work. And we're very excited about Perception and what it means, quite frankly, for our security business going forward.

所以成本與韌性都是重要的評估標準。而這正是我們試圖內建進去的，不論是在程式碼、在資安，或是在知識型工作中。坦白說，我們對 Perception 以及它對我們未來資安業務的意義感到非常興奮。

Thanks, Brent. Operator, we have time for one last question.

謝謝你，Brent。接線員，我們還有時間再問最後一個問題。

Gabriela Borges, Goldman Sachs.

Gabriela Borges，高盛。

Amy, I'd like to ask you about ROI. And you've given us color on the CapEx side of the equation. You've given us color on the monetization side of the equation. Maybe put those two pieces together for us. When you look at and track ROI on the CapEx decisions you're making today, how does that compare to a year ago? And what are some of the levers that you can still pull perhaps on the internal silicon side, for example, as a driver of incremental monetization going forward? Thank you.

Amy，我想問你關於投資報酬率（ROI）。你已經就資本支出（CapEx）這一端提供了一些說明。你也就變現（monetization）這一端提供了一些說明。或許可以幫我們把這兩部分串起來。當你回頭看並追蹤你今天所做的資本支出決策的ROI時，和一年前相比如何？另外，未來作為增量變現的驅動因素，例如在內部自研晶片（internal silicon）方面，還有哪些槓桿可以運用？謝謝。

Thanks, Gabriela. I don't know that -- quite frankly, my math has changed in terms of how I do it over the past year. I would say the way to think about it for me is more the confidence in the TAM expansion, the margin levers that we have in terms of both product improvements than the infrastructure improvements. And we talked about some already on the call today in terms of the levers we have to continue to get efficiencies across both the application part of the stack and then the infra part of the stack.

謝謝你，Gabriela。坦白說，在過去一年裡，我計算的方式在數學上已經有所改變。對我而言，思考方式更偏向於：我們對TAM（可服務市場總量）擴張的信心、以及我們在毛利方面可運用的槓桿——既包括產品改進，也包括基礎設施改進。而我們今天在電話會議中也已談到其中一些槓桿，關於我們如何持續在技術堆疊中，從應用層到基礎設施層（infra）兩端提升效率。

But you're right, we didn't touch on all of the pieces. I think Satya actually commented on a number of them. We still have opportunities, obviously, as we continue to look for the best price performance on silicon, including our investments in first party.

但你說得對，我們沒有涵蓋所有面向。我想 Satya 其實評論了其中不少項。顯然，我們仍有機會，尤其是在持續尋求晶片（silicon）的最佳性價比（price performance）方面，包括我們對第一方（1P）自研的投資。

The work, frankly, on model diversification also is a margin improvement opportunity being able to serve the best possible outcome with a more efficient or both efficient in terms of token usage and efficient in terms of cost structure are also margin levers. All of these things contribute, obviously, to your point, of increased confidence in ROIC, frankly, of the dollars that we're investing and continue to invest going forward.

坦白說，模型多元化（model diversification）的工作也是一個提升毛利的機會：能以更有效率的方式提供最佳可能的結果——不論是以token使用效率來看，或是以成本結構效率來看——這些也都是毛利槓桿。顯然，所有這些都會促成——正如你所說——我們對投入資金的投資資本報酬率（ROIC）的信心提升，且我們未來仍將持續投資。

And as we think about the mix of the portfolio, being able to have a pretty broad pool across knowledge work, coding, security, then basically the agent layer, I'll call that Agent 365, it's kind of a cheap, but all of that also is an opportunity. And then, of course, what we talked about on the Azure side between model efficiency, silicon, and component efficiency, including our investments in 1P solutions there and just the overall efficiency of running it at a hyperscale. So we have quite a few levers to continue to see improvement that we're focused on.

此外，當我們思考產品組合（portfolio）的配置時，能夠在知識型工作、程式開發、資安，然後基本上是代理（agent）層——我稱之為 Agent 365，這名字有點俗，但——這些也都是機會。當然，還有我們在 Azure 端所談到的：模型效率、晶片，以及元件效率，包括我們在那裡對第一方（1P）解決方案的投資，以及在超大規模（hyperscale）環境下運行的整體效率。因此，我們有相當多的槓桿可以持續看到改善，而這也是我們專注的方向。

But as Satya mentioned, this is the grind work. This is like every day. You just get a little better, get a little better. And we actually are quite good at that grind and making sure that we can deliver that for customers.

但正如 Satya 提到的，這是苦功。這就像每天一樣。你只是不斷變得更好、更好。而我們其實很擅長做這種苦功，並確保我們能為客戶交付這些成果。

Thanks, Gabriela. 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.

謝謝你，Gabriela。以上是今天財報電話會議的問答（Q&A）部分。感謝各位今天的參與，我們期待很快再與各位交流。

Thank you very much.

非常感謝。

Thank you.

謝謝。

Ladies and gentlemen, this does conclude today's conference. You may disconnect your lines at this time and enjoy the rest of your day.

各位女士先生，今天的會議到此結束。您現在可以掛斷電話線，祝您今天剩餘時間愉快。