微軟 (MSFT) 2027 Q1 法說會逐字稿

Greetings, and welcome to the Microsoft fiscal year 2027 first-quarter earnings conference call. (Operator Instructions) As a reminder, this conference is being recorded.

各位好，歡迎參加微軟 2027 會計年度第一季財報電話會議。(接線員指示) 提醒各位，本次會議將被錄音。

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

現在我很榮幸介紹投資人關係副總裁 Jonathan Neilson。

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

各位下午好，感謝今天加入我們。與我一同出席電話會議的有：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 provide the reconciliation of differences between GAAP and non-GAAP financial measures. More detailed outlook slides will be available on the Microsoft Investor Relations website when we provide outlook commentary on today's call.

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，該資料旨在補充我們今天電話會議中的事先準備發言，並提供 GAAP 與非 GAAP 財務衡量指標之間差異的調節表。當我們在今天電話會議中提供展望評論時，更詳細的展望投影片將會在微軟投資人關係網站上提供。

On this call, we will discuss certain non-GAAP items. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the measures of financial performance prepared in accordance with GAAP. They are included as additional clarifying items to aid investors in further understanding the company's first-quarter performance in addition to the impact these items and events have on the financial results.

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。這些指標作為額外的釐清項目納入，旨在協助投資人除了解第一季表現外，也能進一步理解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 business performed, excluding the effect of foreign currency rate fluctuations. Where growth rates are the same in constant currency, we will refer to the growth rate only.

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，作為評估我們基礎業務表現的架構，排除外幣匯率波動的影響。若以固定匯率計算的成長率相同，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發言稿張貼到網站上，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 Factor section of our Form 10-K, Forms 10-Q, and other reports and filings with the Securities and Exchange Commission. We do not undertake any duty to update any forward-looking statements.

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，我把電話交給 Satya。

Thank you very much, Jonathan. It was a fast start to our fiscal year. Microsoft Cloud revenue surpassed $63 billion with growth accelerating to 30% year over year. We are focused on three things: designing AI to empower people, ensuring every organization has sovereignty over its own learning, and building trust with controls that ensure agent safety and security. Now, let's talk about how we are making progress on those goals as we build the new tech stack, starting with Copilot.

非常感謝你，Jonathan。我們的會計年度開局迅速。Microsoft Cloud 營收突破 630 億美元，年增率加速至 30%。我們聚焦三件事：設計能賦能人們的 AI、確保每個組織對自身學習擁有主權，以及透過能確保代理安全與資安的控制機制來建立信任。現在，讓我們從 Copilot 開始，談談在打造新技術堆疊的同時，我們如何在這些目標上取得進展。

We announced our biggest update to Copilot today this quarter, bringing together Chat, Cowork, Autopilot and Code into one unified experience. It's one product experience across commercial and consumer and comes with all of Office built-in. We think of Copilot as the new OS for work. Customers are increasingly turning to Copilot to get real work done.

本季我們在今天宣布了 Copilot 迄今最大更新，將 Chat、Cowork、Autopilot 與 Code 整合為單一的統一體驗。它在商用與消費端提供一致的產品體驗，並內建完整的 Office。我們把 Copilot 視為工作的全新作業系統。客戶正日益轉向使用 Copilot 來完成真正的工作。

Automated tasks has nearly doubled since July. Daily users are up nearly 50% quarter over quarter and over 5x year over year. User satisfaction improved nearly 20% quarter over quarter to another all-time high. And 90% of Copilot queries use auto mode, which dynamically routes tasks across models optimizing for quality, speed, and cost. These improvements are translating into larger purchases.

自 7 月以來，自動化任務量幾乎翻倍。每日使用者數季增近 50%，年增超過 5 倍。使用者滿意度季增近 20%，再創歷史新高。此外，90% 的 Copilot 查詢使用自動模式，該模式會在不同模型之間動態分派任務，以在品質、速度與成本之間達到最佳化。這些改善正轉化為更大規模的採購。

The number of customers with more than 50,000 Copilot seats increased over 8x year over year, including Capgemini, HCL Tech, Hitachi Group, Truist Financial, and UK Revenue and Customs Department. And just last week, Volkswagen announced plans to deploy Copilot to more than 330,000 employees, one of the largest deployments to date in Europe.

擁有超過 50,000 個 Copilot 席次的客戶數年增超過 8 倍，其中包括 Capgemini、HCL Tech、日立集團、Truist Financial，以及英國稅務海關總署。就在上週，Volkswagen 宣布計畫將 Copilot 部署給超過 330,000 名員工，這是迄今歐洲規模最大的部署之一。

We're also seeing strong momentum with E7, which brings together Copilot, E5, Entra, and Agent 365. Thousands of customers in every industry have purchased the suite to date, including Amadeus, BlackRock, Fiserv, and New South Wales Health Department, and ZEISS.

我們也看到 E7 的強勁動能；E7 將 Copilot、E5、Entra 與 Agent 365 整合在一起。迄今為止，各行各業已有數千家客戶購買該套件，包括 Amadeus、BlackRock、Fiserv、新南威爾斯州衛生部，以及 ZEISS。

Our business model is expanding from per-seat subscriptions to include consumption, expanding our TAM and ARPU. The subscription brings increasingly capable everyday intelligence to every user. Typically, IT funds this, consolidating frontier advances for everyone across the organization. And as agents take on higher value work, consumption opens up business-funded demand with spending tied directly to the value these agents deliver. The number of Copilot customers actively consuming credits through usage-based billing grew over 75% over the quarter.

我們的商業模式正從按席次訂閱擴展到包含用量計費，進而擴大我們的 TAM 與 ARPU。訂閱為每位使用者帶來日益強大的日常智慧能力。通常由 IT 部門出資，將前沿進展整合，讓整個組織中的每個人都能受益。而當代理承擔更高價值的工作時，用量計費將開啟由業務部門出資的需求，支出將直接與這些代理所交付的價值掛鉤。本季透過按用量計費、以使用量主動消耗點數的 Copilot 客戶數成長超過 75%。

When it comes to software development, all major coding agents have shown up to work on GitHub. Agent-generated PRs have increased 6x over the past six months, and agents now open more than a third of all PRs on the platform. We are very hard at work on reliability as agentic activity on GitHub soars.

在軟體開發方面，所有主要的程式碼代理都已在 GitHub 上投入工作。過去六個月，代理生成的 PR 數量增加了 6 倍，而代理目前開啟的平台 PR 已超過三分之一。隨著 GitHub 上的代理式活動激增，我們正全力投入提升可靠性。

At GitHub Universe this morning, we shared how we are expanding capacity and rebuilding the core Git architecture for the agentic wave. Also at Universe, we announced broad availability of Copilot Fusion, which is all about bringing multi-model orchestration to software development. It delivers frontier level quality up to 40% faster and at up to 77% lower cost. Credit consumption from agentic features on GitHub has more than doubled since usage-based billing went into effect, and we're also helping developers secure their code and turn AI-generated code into high-quality software.

今天上午在 GitHub Universe 大會上，我們分享了如何擴充容量並重建 Git 核心架構，以迎接代理浪潮。同樣在 Universe，我們宣布 Copilot Fusion 正式全面可用，其核心在於將多模型協同編排帶入軟體開發。它可在速度提升最高達 40% 的同時，提供前沿等級的品質，並將成本降低最高達 77%。自按用量計費生效以來，GitHub 上代理式功能的點數消耗已超過翻倍；我們也在協助開發者保護其程式碼，並將 AI 生成的程式碼轉化為高品質軟體。

GitHub Advanced Security revenue increased over 50% year over year as customers use its AI capabilities to scan entire repos and fix vulnerabilities in real time.

GitHub Advanced Security 營收年增超過 50%，因客戶使用其 AI 能力掃描整個儲存庫（repo），並即時修補弱點。

In the business application space, we are extending this vision of Copilot as the new OS for work, bringing the business logic and capabilities of Dynamics 365 directly into Copilot and helping every organization stand up their own infinite SaaS factory. This quarter, we introduced 30 new Copilot skills across Dynamics 365, which enables customers to access CRM and ERP capabilities directly in the flow of work.

在商業應用領域，我們正延伸將 Copilot 視為工作新作業系統的願景，把 Dynamics 365 的商業邏輯與能力直接帶入 Copilot，並協助每個組織建立自己的「無限 SaaS 工廠」。本季我們在 Dynamics 365 中推出 30 項新的 Copilot 技能，使客戶能在工作流程中直接存取 CRM 與 ERP 能力。

In recruiting, more than 10 million LinkedIn members use our LinkedIn AI-powered job search daily, and 25,000 customers are using our agentic hiring solutions. Recruiters using Hiring Assistant are finding interview-quality applicants 33% faster while reviewing 83% fewer profiles to find qualified match.

在招募方面，每天有超過 1,000 萬名 LinkedIn 會員使用我們由 AI 驅動的 LinkedIn 求職搜尋，而有 25,000 家客戶正在使用我們的代理式招募解決方案。使用 Hiring Assistant 的招募人員，能以快 33% 的速度找到具備面試水準的應徵者，同時為找到合格匹配而需檢視的個人檔案數量減少 83%。

In healthcare, we automated 30 million patient encounters this quarter, up 70% year over year, helping clinicians spend less time on administrative work and more time with patients. 10 providers, including Advocate Health, Mass General Brigham, Mercy, Intermountain Health, and others have used our solutions to document over 1 million encounters, each since the beginning of the calendar year.

在醫療照護方面，本季我們自動化了 3,000 萬次病患就診紀錄，年增 70%，協助臨床人員減少行政作業時間、把更多時間留給病患。自本曆年開始以來，包括 Advocate Health、Mass General Brigham、Mercy、Intermountain Health 等在內的 10 家醫療服務提供者，已各自使用我們的解決方案記錄超過 100 萬次就診。

And in science, our FDE teams are working with customers to use discovery to accelerate scientific progress. A great example is Saint-Gobain, which used discovery to accelerate the development of low-carbon construction materials.

在科學領域，我們的 FDE 團隊正與客戶合作，運用 discovery 來加速科學進展。一個很好的例子是 Saint-Gobain，其使用 discovery 加速低碳建築材料的研發。

Underneath our first-party agentic experience is a common platform. It starts with Foundry, which is becoming an increasingly important driver of our growth. Foundry helps organizations build learning loops grounded in their business context and deploy agents safely at scale. We now have over 120,000 Foundry customers, with revenue more than tripling year over year. Foundry's model choice and feature set, coupled with its deep integration across our stack, is driving differentiation.

在我們第一方代理式體驗之下，是一個共通的平台。它從 Foundry 開始，而 Foundry 正日益成為我們成長的重要驅動力。Foundry 協助組織在其業務情境中建立學習迴圈，並以安全的方式大規模部署代理。我們目前已有超過 120,000 名 Foundry 客戶，營收年增逾三倍。Foundry 的模型選擇與功能組合，加上其在我們整個技術堆疊中的深度整合，正在推動差異化。

Azure OpenAI directly benefited in the last quarter with big advances in OpenAI models, and when you couple this with our model choice built into Foundry, customers are able to build solutions optimizing across quality, cost, and performance. In fact, the number of customers building agentic solutions with multiple models increased 5x year over year, and revenue from open source models on Foundry increased 10x.

在上一季，Azure OpenAI 直接受惠於 OpenAI 模型的重大進展；再結合我們在 Foundry 內建的模型選擇能力，客戶便能打造在品質、成本與效能之間最佳化的解決方案。事實上，使用多模型建置代理式解決方案的客戶數年增 5 倍，而 Foundry 上開源模型的營收年增 10 倍。

We also continue to make rapid progress with our first-party models. Our goal is to advance the cost-to-outcome frontier, which means delivering capabilities comparable to leading models within three to six months of their release at a fraction of the training cost, thereby allowing us to transfer those cost benefits to customers. And you see this in our products today.

我們在第一方模型方面也持續快速推進。我們的目標是推進「成本對成果」的前沿，這意味著在領先模型發布後三到六個月內，以遠低於其訓練成本的一小部分，交付可比擬的能力，並因此將成本效益轉移給客戶。而你今天就能在我們的產品中看到這一點。

MAI Cyber now powers over 40% of the scans in our agentic MDASH code scanner at 18% lower cost per scan. MAI Transcribe is the most accurate and cheapest transcription model in the world, supporting Dragon Copilot's multilingual workflow. MAI Code Flash has 3 million users in GitHub Copilot last month alone, helping developers get more out of their AI credits.

MAI Cyber 現在為我們代理式 MDASH 程式碼掃描器中超過 40% 的掃描提供支援，且每次掃描成本降低 18%。MAI Transcribe 是全球最準確且最便宜的轉錄模型，支援 Dragon Copilot 的多語工作流程。僅上個月，MAI Code Flash 就在 GitHub Copilot 中擁有 300 萬名使用者，協助開發者更充分運用其 AI 點數。

Microsoft-Decision-1 is our new model for structured decision-making, outperforming both LLMs and other decision models in latency and quality. Over 4,000 customers, including Atos Group, Equinor, and RBI, have already used it in the first month since its release.

Microsoft-Decision-1 是我們用於結構化決策的新模型，在延遲與品質方面都優於 LLM 以及其他決策模型。自發布以來的第一個月內，已有超過 4,000 家客戶（包括 Atos Group、Equinor 與 RBI）使用。

And we recently completed pre-training MAI-Base-2, which outperforms other open weight models we tested with 4 to 12 times greater training compute efficiency. This base model will be used in the upcoming MAI models across thinking, code, and cyber.

我們最近也完成了 MAI-Base-2 的預訓練；在我們測試的其他開放權重模型中，它以 4 到 12 倍更高的訓練算力效率表現勝出。這個基礎模型將用於即將推出、涵蓋推理、程式碼與資安的 MAI 模型。

Beyond models, we are making the harness behind our own Copilot experience available to customers in Foundry. It gives customers a Microsoft-managed way to build agents that reason, use tools, complete complex long-running work while preserving their choice of model.

除了模型之外，我們也將支撐自家 Copilot 體驗的「編排框架（harness）」提供給 Foundry 的客戶使用。它為客戶提供一種由 Microsoft 管理的方式來建置代理，使其能推理、使用工具、完成複雜且長時間執行的工作，同時保留其模型選擇權。

Another critical layer is data. We now have 44,000 paid Fabric customers, up more than 50% year over year. We are bringing Foundry and Fabric closer together so you can build your own agents right next to data. Over 19,000 customers now use Foundry and Fabric as enterprises connect and operate agents over real-time operational, analytical, and unstructured data.

另一個關鍵層是資料。我們目前有 44,000 名付費 Fabric 客戶，年增超過 50%。我們正讓 Foundry 與 Fabric 更緊密結合，讓你能在資料旁邊直接建置自己的代理。目前已有超過 19,000 名客戶同時使用 Foundry 與 Fabric，企業得以在即時營運、分析與非結構化資料上連結並運行代理。

Customers are also rapidly deploying our AI-optimized databases, including PostgreSQL, SQL DB Hyperscale, and Cosmos DB, to give agents fast, secure access to the data and context they need. PostgreSQL growth accelerated for the fourth consecutive quarter, and the number of PostgreSQL customers also using Foundry accelerated to 90% year over year.

客戶也在快速部署我們針對 AI 最佳化的資料庫，包括 PostgreSQL、SQL DB Hyperscale 與 Cosmos DB，讓代理能快速且安全地存取所需的資料與情境。PostgreSQL 的成長已連續第四季加速，而同時使用 Foundry 的 PostgreSQL 客戶數也加速至年增 90%。

We also have one of the most important databases for any enterprise, which is the knowledge underneath Microsoft 365, spanning people, their relationships, documents, emails, meetings, chats, projects, and other artifacts.

我們也擁有任何企業最重要的資料庫之一，也就是 Microsoft 365 底層的知識，涵蓋人員、其關係、文件、電子郵件、會議、聊天、專案與其他各類成品（artifacts）。

Work IQ makes this context available to every agentic workload. And with Microsoft IQ, we are bringing together Work IQ, Fabric IQ, and Foundry IQ as a unified context for agentic systems. Nearly 60,000 customers are accessing context across Microsoft IQ, up 25% quarter over quarter.

Work IQ 讓每一個代理式工作負載都能使用這些情境。而透過 Microsoft IQ，我們正將 Work IQ、Fabric IQ 與 Foundry IQ 整合為代理式系統的統一情境。目前將近 60,000 名客戶正在透過 Microsoft IQ 存取跨域情境，季增 25%。

As enterprises deploy more agents, they also need to govern them at scale. With Agent 365, we provide a platform for AI observability, enabling customers to manage, secure, and optimize the performance and cost of their agents. Over 50 million agents are now in the registry, up over 30% quarter over quarter.

隨著企業部署更多代理，也需要能以規模化方式進行治理。透過 Agent 365，我們提供 AI 可觀測性平台，使客戶能管理、保護並最佳化其代理的效能與成本。目前登錄庫中已有超過 5,000 萬個代理，季增超過 30%。

And finally, as agents gain greater access to enterprise data and systems, security becomes even more critical. Our approach is to separate intelligence from authority, enforcing identity, permissions, monitoring, and containment outside the model itself.

最後，隨著代理對企業資料與系統的存取權限提高，安全性就變得更加關鍵。我們的方法是將「智慧」與「權限」分離，在模型本身之外強制執行身分識別、權限控管、監控與隔離（containment）。

Last week, we expanded Perception with new capabilities to help customers secure and contain agentic insiders, including expanded agent discovery across local and cloud environments, dynamic permissions that enforce least privileged access for each task, and continuous risk assessment.

上週，我們透過新增功能擴充了 Perception，協助客戶保護並隔離代理式內部威脅（agentic insiders），包括擴大在本地與雲端環境中的代理探索能力、可針對每項任務強制最小權限存取的動態權限，以及持續性的風險評估。

We also introduced teams of guardian agents that continuously monitor agent activity to help prevent unsafe actions before they occur. And we are seeing encouraging feedback on Perception overall from preview customers, including KPMG, Nationwide Building Society, Northern Trust, Stellantis. More broadly, we are helping customers secure and govern AI use across the enterprise. Customers have used Microsoft Purview to audit over 7.6 billion agent activities to date, up 5x quarter over quarter.

我們也推出了由多個守護者代理（guardian agents）組成的團隊，持續監控代理活動，以在不安全行為發生前加以預防。整體而言，我們從預覽客戶（包括 KPMG、Nationwide Building Society、Northern Trust、Stellantis）對 Perception 收到令人鼓舞的回饋。更廣泛地說，我們正在協助客戶在全企業範圍內保護並治理 AI 的使用。截至目前，客戶已使用 Microsoft Purview 稽核超過 76 億次代理活動，季增 5 倍。

Underlying everything I've talked about so far is our infrastructure. We are building against a growing book of business with a fungible fleet that allows us to dynamically allocate capacity to the highest value opportunities across compute, data, Foundry, and Copilot.

支撐我目前所談一切的是我們的基礎設施。我們正面向不斷成長的業務訂單（book of business）進行建置，並以可互換的機群（fungible fleet）讓我們能在算力、資料、Foundry 與 Copilot 之間，動態將容量配置到最高價值的機會上。

Accelerating demand led to us adding 24 new data centers across five continents this quarter. And we are bringing capacity online faster, reducing [doctor] lifetimes by about 20% quarter over quarter for new GB300s in our biggest regions, which make up the majority of the GPU deployments.

需求加速促使我們本季在五大洲新增 24 座資料中心。我們也更快讓產能上線，針對我們最大區域中新部署的 GB300（占 GPU 部署的大多數），將 [doctor] 生命週期（lifetimes）季減約 20%。

At the same time, we continue to get more from the infrastructure we already have by optimizing across the data center designs, silicon systems, software, and models. For example, we increased the throughput for Copilot workloads by over 50% quarter over quarter.

同時，我們也持續透過在資料中心設計、矽晶系統、軟體與模型上的最佳化，從既有基礎設施中榨取更多效益。例如，我們將 Copilot 工作負載的吞吐量季增超過 50%。

We continue to scale our fleet with the latest innovations from NVIDIA and AMD alongside our own Maia systems. We have docked our first NVIDIA Vera Rubin GPUs and are very excited about it.

我們持續結合 NVIDIA 與 AMD 的最新創新，以及我們自家的 Maia 系統，擴大機群規模。我們已完成首批 NVIDIA Vera Rubin GPU 的上架（docked），對此感到非常振奮。

Maia 200 is already delivering up to 1.7 times more tokens per watt across the AI experiences in Teams and Copilot, and Maia 300 will drive further gains, delivering 40% more tokens per watt compared to the leading GPU-based systems.

Maia 200 已在 Teams 與 Copilot 的 AI 體驗中，提供每瓦最多 1.7 倍的 token 產出；而 Maia 300 將帶來進一步提升，相較於領先的 GPU 型系統，每瓦可多提供 40% 的 token。

Our growth extends beyond GPUs. We continue to see strong adoption of our cloud-native Cobalt CPUs, improving price performance for general-purpose cloud workloads. All up, Azure growth was broad-based across both enterprises and small and medium business segments and spanning both core cloud services and AI infrastructure.

我們的成長不僅限於 GPU。我們持續看到雲端原生 Cobalt CPU 的強勁採用，提升一般用途雲端工作負載的性價比（price performance）。整體而言，Azure 的成長在企業與中小企業客群中皆呈現廣泛動能，並同時涵蓋核心雲端服務與 AI 基礎設施。

Finally, let me turn to devices and consumer. In Windows, we are executing on our vision to bring hybrid intelligence to every desk and every home, making every PC a secure agent box. As more capable models run locally, we see an opportunity to make more intelligence effectively unmetered.

最後，讓我談談裝置與消費者業務。在 Windows 方面，我們正落實將混合智慧帶到每一張辦公桌與每一個家庭的願景，讓每台 PC 都成為安全的代理盒（agent box）。隨著更強大的模型可在本地端執行，我們看見一個機會，讓更多智慧在實質上可視為不計量（unmetered）。

We are working with a broader hardware ecosystem to bring these capabilities to a new generation of PCs across AMD's Ryzen AI 400 series, Intel Core Ultra Series 3, Qualcomm Snapdragon X2 series. And earlier this month, we also announced new PCs powered by NVIDIA's RTX Spark and DGX Station for Windows. With these new devices, you can run last year's frontier models on your laptop and last quarter's model at your desk.

我們正與更廣泛的硬體生態系合作，將這些能力帶到新一代 PC，涵蓋 AMD 的 Ryzen AI 400 系列、Intel Core Ultra Series 3，以及 Qualcomm Snapdragon X2 系列。而在本月稍早，我們也宣布推出搭載 NVIDIA RTX Spark 與 DGX Station（適用於 Windows）的新款 PC。透過這些新裝置，你可以在筆電上執行去年的前沿模型，並在桌機上執行上一季的模型。

We are bringing together Windows and Agent 365 so agents can work with secure boundaries on device. We introduced Microsoft Execution Containers, a policy-driven execution layer that governs and contains agents across Windows and other platforms, integrated with Agent 365 for governance and observability. Agents like OpenAI Codex, Anthropic Claude Code, Meta Muse are adopting MXC, and customers like Meta are starting to deploy it across their enterprise environments.

我們正將 Windows 與 Agent 365 整合在一起，讓代理能在裝置端於安全邊界內運作。我們推出了 Microsoft Execution Containers（MXC），這是一個以政策驅動的執行層，用於在 Windows 與其他平台上治理並隔離代理，並與 Agent 365 整合以提供治理與可觀測性。像 OpenAI Codex、Anthropic Claude Code、Meta Muse 等代理正在採用 MXC，而像 Meta 這樣的客戶也開始在其企業環境中部署。

In search and advertising, Bing and Edge once again took share. In LinkedIn, engagement continues to deepen across our more than 1.4 billion members, with time spent viewing content in the feed up 15% year over year.

在搜尋與廣告方面，Bing 與 Edge 再次提升市占。在 LinkedIn 方面，我們超過 14 億名會員的互動持續加深，動態消息中內容瀏覽時間年增 15%。

And finally, in gaming, we remain focused on building great games and reaching players wherever they choose to play across console, PC, mobile, and cloud.

最後，在遊戲方面，我們仍專注於打造優秀的遊戲，並在玩家選擇的任何平台上觸及他們，包括主機、PC、行動裝置與雲端。

Minecraft delivered a record quarter, reaching all-time highs in both engagement and revenue, while World of Warcraft had its largest beta in franchise history.

Minecraft 創下創紀錄的一季，互動與營收皆達歷史新高；同時，《魔獸世界》也迎來該系列史上規模最大的 Beta 測試。

We enter the holiday season with one of our strongest first- and third-party lineups in years, including Modern Warfare 4, which launched last week to the best reviews for a Call of Duty game in more than a decade and Grand Theft Auto 6, which is coming to XBOX next month.

我們以多年來最強的第一方與第三方作品陣容之一迎接假期旺季，其中包括《現代戰爭 4》，上週推出後獲得十多年來《決勝時刻》系列最佳評價；以及《俠盜獵車手 6》，將於下個月登陸 XBOX。

In closing, based on the demand we see, the strength of our products, and the efficiency we are driving across the stack, I've never been more confident in the long-term returns for our investments.

總結來說，基於我們所看到的需求、產品的強勁實力，以及我們在整個技術堆疊上推動的效率提升，我從未像現在這樣對我們投資的長期報酬更有信心。

With that, let me turn it over to Amy.

接下來，我把時間交給 Amy。

Thank you, Satya, and good afternoon, everyone. Our results exceeded expectations across revenue, operating income, and earnings per share, driven by strong demand across the Microsoft Cloud.

謝謝你，Satya，各位下午好。在 Microsoft Cloud 的強勁需求帶動下，我們在營收、營業利益與每股盈餘方面的表現均超出預期。

This quarter, revenue was $92.3 billion, up 19%. Gross margin dollars increased 17%, and gross margin percentage was 68%. Operating income increased 21% and 22% in constant currency. Earnings per share was $4.89, an increase of 18% and 19% in constant currency when adjusted for the impact for our investment in OpenAI, and FX was roughly in line with guidance.

本季營收為 923 億美元，年增 19%。毛利金額增加 17%，毛利率為 68%。營業利益增加 21%，以固定匯率計增加 22%。每股盈餘為 4.89 美元，增加 18%；若調整我們對 OpenAI 投資的影響，以固定匯率計增加 19%，而外匯影響大致符合指引。

Operating expenses increased 6%, driven by continued investments in R&D compute capacity and talent. Operating margins increased slightly year over year to 50%, driven by strong revenue growth, platform efficiency gains, and focused on investments across our portfolio, partially offset by sales mix shift to Azure.

營業費用增加 6%，主要來自持續投資於研發運算能力與人才。營業利益率年增小幅上升至 50%，受惠於強勁的營收成長、平台效率提升，以及我們在投資組合上的聚焦投資；但部分被銷售組合轉向 Azure 所抵銷。

When adjusted for the impact for our investments in OpenAI, other income and expense was negative $234 million, slightly lower than expected. Capital expenditures were $45.2 billion as some third-party capacity deliveries we expected in Q1 were delayed.

若調整我們對 OpenAI 投資的影響，其他收益與費用為負 2.34 億美元，略低於預期。資本支出為 452 億美元，原因是我們原預期在第一季交付的部分第三方產能有所延遲。

Roughly three quarters of our CapEx was for short-lived assets, primarily CPUs and GPUs, including higher memory and storage costs, as we continue to invest in the infrastructure required for our customers to build and scale AI applications.

我們的資本支出約有四分之三用於短年限資產，主要是 CPU 與 GPU，並包含較高的記憶體與儲存成本；因為我們持續投資於客戶建置並擴展 AI 應用所需的基礎設施。

The remaining spend was for long-lived assets. This quarter, finance leases were $7.4 billion. As a reminder, we recognize the full principal value of finance leases and CapEx at the time of lease commencement. And cash paid for PP&E was $39.4 billion.

其餘支出用於長年限資產。本季融資租賃為 74 億美元。提醒一下，我們在租賃開始時即認列融資租賃與資本支出的全部本金價值。而用於不動產、廠房及設備（PP&E）的現金支付為 394 億美元。

Cash flow from operations was $58 billion, up 29%, driven by strong cloud billings and collections. And free cash flow was $18.6 billion, reflecting higher capital expenditures. And finally, we returned $10.2 billion to the shareholders through dividends and share repurchases.

營運活動現金流為 580 億美元，年增 29%，主要由強勁的雲端帳單與收款所帶動。自由現金流為 186 億美元，反映較高的資本支出。最後，我們透過股利與庫藏股回購向股東返還 102 億美元。

Now, to our segment results reported under the updated segment structure announced in September. Revenue from Agents and Infra was $76.8 billion and grew 25%, reflecting strength across the connected layers of our platform.

接著說明我們在 9 月宣布更新後的部門架構下所揭露的分部業績。Agents and Infra 的營收為 768 億美元，成長 25%，反映我們平台各相連層面的強勁表現。

Commercial bookings decreased 12% and 11% in constant currency, driven by the impact from large Azure commitments in the prior year, partially offset by healthy growth in our commercial sales motions, including a large Azure commitment this quarter.

商業訂單（commercial bookings）下降 12%，以固定匯率計下降 11%，主要受前一年大型 Azure 承諾案影響；部分被我們商業銷售動能的健康成長所抵銷，其中包括本季一筆大型 Azure 承諾案。

Commercial remaining performance obligation grew 73% to $677 billion with a smaller sequential decline relative to historical seasonality due to the large Azure commitment this quarter.

商業剩餘履約義務（RPO）成長 73% 至 6,770 億美元；由於本季大型 Azure 承諾案，使得相較於歷史季節性，季對季下降幅度較小。

Our RPO has a weighted average duration of 2.3 years and roughly 30% will be recognized in revenue in the next 12, up 29% year over year. The remaining portion recognized beyond the next 12 months increased 98%.

我們的 RPO 加權平均期間為 2.3 年，約 30% 將在未來 12 個月內認列為營收，年增 29%。在未來 12 個月之後才認列的其餘部分增加 98%。

Now to Microsoft Cloud. Revenue was $63.9 billion and growth accelerated to 30% and 31% in constant currency with sequential dollars added nearly doubling year over year, reflecting strong demand across Azure and M365 commercial cloud.

接著談 Microsoft Cloud。營收為 639 億美元，成長加速至 30%；以固定匯率計為 31%，且本季新增的連續季度增量金額較去年同期幾乎翻倍，反映 Azure 與 M365 商用雲端的強勁需求。

Azure revenue was ahead of expectations and increased 48% even with the 3P capacity delays noted earlier, driven by Foundry and improved CPU monetization.

Azure 營收優於預期，即使受到前述第三方（3P）產能延遲影響，仍成長 48%，主要由 Foundry 以及 CPU 變現能力改善所帶動。

Foundry revenue more than tripled year over year with upside driven by efficiency gains across our GPU fleet that allowed us to allocate additional capacity to customers, as well as higher revenue per token that we benefited from in the quarter.

Foundry 營收年增超過三倍，超預期主要來自我們 GPU 機群的效率提升，使我們能將額外產能分配給客戶，以及本季我們受惠於每 token 較高的營收。

Across our CPU fleet, engineering work enabled us to identify and monetize underutilized capacity this quarter, helping us serve more of the growing demand with our existing capacity. The timing of engineering efficiencies like these, as well as 3P GPU lease deliveries, our own capacity build-outs, and ARPU changes from model mix can create quarterly variability in the year-over-year growth rate.

在我們的 CPU 機群方面，工程工作讓我們得以在本季辨識並將未充分利用的產能變現，協助我們以既有產能滿足更多成長中的需求。像這類工程效率提升的時點、以及第三方 GPU 租賃交付、我們自建產能的擴建進度、與模型組合造成的 ARPU 變動，都可能使年對年成長率在季度間出現波動。

M365 Commercial cloud revenue increased 18% and 19% in constant currency when adjusted for the prior year comparable that benefited from one point of in-period revenue recognition.

M365 商用雲端營收增加 18%；若調整前一年可比基期中受惠於當期營收認列增加 1 個百分點的影響，以固定匯率計增加 19%。

On a reported basis, revenue growth was 17% and 18% in constant currency. Results were ahead of expectations, driven by stronger GitHub Copilot adoption and usage, partially offset by weaker sales execution in our M365 E3 and standalone SKUs.

以報告基礎計算，營收成長為 17%；以固定匯率計為 18%。結果優於預期，主要由 GitHub Copilot 更強勁的採用與使用所帶動；但部分被我們在 M365 E3 與獨立 SKU 的銷售執行較弱所抵銷。

We continue to evolve our sales motions to balance those more traditional SKU per-seat rhythms with the newer premium E7, M365 Copilot, and usage-based productivity offerings. Year-over-year growth was driven by both ARPU and seats. ARPU growth was led by our premium seat-based offerings, including M365 Copilot, E5, and E7, which has already reached millions of paid seats, with additional contribution from usage-based offerings, primarily GitHub Copilot. And Copilot revenue growth accelerated quarter over quarter with continued adoption across M365, GitHub, and security.

我們持續演進銷售模式，以在較傳統的按席位 SKU 節奏與較新的高階 E7、M365 Copilot，以及按使用量計費的生產力產品之間取得平衡。年對年成長同時由 ARPU 與席位數帶動。ARPU 成長主要由我們的高階按席位產品帶動，包括 M365 Copilot、E5 與 E7；這些產品已達數百萬個付費席位，另有按使用量計費產品的額外貢獻，主要是 GitHub Copilot。而 Copilot 營收成長在季度間持續加速，並在 M365、GitHub 與資安領域持續擴大採用。

Paid M365 commercial seats grew 5% with some impact from the weaker sales execution noted earlier. Growth was driven by installed base expansion across all customer segments, though primarily in our SMB and frontline worker offerings.

付費的 M365 商用席位數成長 5%，其中受到前述銷售執行較弱的部分影響。成長來自各客戶區隔的既有安裝基礎擴張，但主要集中在我們的中小企業（SMB）與第一線員工產品。

M365 consumer cloud revenue increased 17% and 16% in constant currency, down sequentially as we begin to lap the benefit from the price increase in the prior year.

M365 消費者雲端營收增加 17%；以固定匯率計增加 16%，由於我們開始進入前一年漲價效益的比較基期，季對季有所放緩。

Productivity and server licensing revenue decreased 3% and 2% in constant currency, primarily driven by a decrease in transactional purchasing as we lap the benefit from product launches in the prior year, partially offset by a greater mix of contracts that carry higher in-period revenue recognition.

生產力與伺服器授權營收下降 3%；以固定匯率計下降 2%，主要因為在前一年產品推出帶來的效益進入比較基期後，交易型採購減少；但部分被合約組合中當期營收認列較高的比重提升所抵銷。

Industry solutions cloud revenue increased 10% with growth in Dynamics 365 and LinkedIn Talent Solutions, though booking trends continued to moderate. And in frontier and support services, revenue increased 4% and 5% in constant currency, driven by support.

產業解決方案雲端營收增加 10%，受 Dynamics 365 與 LinkedIn Talent Solutions 成長帶動，但訂單趨勢仍持續趨緩。而在前線與支援服務方面，營收增加 4%；以固定匯率計增加 5%，主要由支援服務帶動。

Microsoft Cloud gross margin percentage declined year over year to 66%, driven by sales mix shift to Azure, partially offset by product level margin improvements primarily in Azure. And for this segment, gross margin dollars increased 20% and 21% in constant currency, operating expenses increased 10%, driven by the R&D investments noted earlier.

Microsoft Cloud 毛利率年對年下降至 66%，主要因銷售組合轉向 Azure；但部分被產品層級的毛利改善（主要在 Azure）所抵銷。就此分部而言，毛利金額增加 20%；以固定匯率計增加 21%，營業費用增加 10%，主要由前述研發投資所帶動。

Operating income grew 24% and 25% in constant currency, and operating margins decreased slightly year over year to 53% as strong revenue growth, platform efficiency gains, and focused investments across our portfolio were more than offset by sales mix shift to Azure.

營業利益成長24%，以固定匯率計成長25%；由於銷售組合轉向Azure，營業利益率較去年同期小幅下降至53%，儘管強勁的營收成長、平台效率提升，以及我們投資組合中聚焦的投資，仍不足以完全抵銷該影響。

Now to Devices and Consumer. Revenue was $15.5 billion and declined 3%. Search and advertising revenue ex TAC increased 12% and was ahead of expectations, driven by higher volume and rate across LinkedIn, Edge, and Bing.

接下來談裝置與消費者。營收為155億美元，下降3%。搜尋與廣告營收（扣除TAC）成長12%，優於預期，主要受LinkedIn、Edge與Bing的量與價提升所帶動。

XBOX revenue decreased 2%, and XBOX content and services revenue decreased 2% and 1% in constant currency, driven by declines in third-party content and XBOX Game Pass, partially offset by growth in first-party content.

XBOX營收下降2%；XBOX內容與服務營收下降2%，以固定匯率計下降1%，主要因第三方內容與XBOX Game Pass下滑，部分被第一方內容成長所抵銷。

And Windows OEM and devices revenue decreased 22%. Windows OEM revenue was below expectations and decreased 27% and 28% in constant currency, driven by the Windows 10 end of support demand in the prior year, inventory drawdowns by OEM and channel partners, and weaker PC market demand. Inventory levels remain elevated.

Windows OEM與裝置營收下降22%。Windows OEM營收低於預期，下降27%，以固定匯率計下降28%，主要受前一年Windows 10終止支援帶來的需求、OEM與通路夥伴去化庫存，以及PC市場需求疲弱所影響。庫存水位仍然偏高。

Segment gross margin dollars were relatively unchanged year over year, and operating expenses decreased 3% driven by XBOX, partially offset by the continued investments in R&D noted earlier.

部門毛利金額與去年同期大致持平；營業費用下降3%，主要由XBOX帶動，但部分被前述持續的研發投資所抵銷。

Operating income increased 2% and 3% in constant currency and operating margins increased year over year to 35%, driven by lower amortization of intangible assets from the Activision acquisition, partially offset by the impact from a lower mix of Windows OEM revenue.

營業利益成長2%，以固定匯率計成長3%；營業利益率較去年同期提升至35%，主要受Activision併購帶來的無形資產攤銷降低所推動，但部分被Windows OEM營收占比下降的影響所抵銷。

Now, moving to the outlook for our second quarter, which unless specifically noted otherwise is on a US dollar basis. Based on current rates, we expect FX to have no meaningful impact on total revenue, COGS, or operating expense growth or on revenue growth in either segment.

接著談第二季展望；除非另有特別說明，以下皆以美元為基礎。依目前匯率，我們預期匯率對總營收、銷貨成本（COGS）或營業費用成長，以及兩個部門的營收成長，均不會造成顯著影響。

Starting with segment guidance. We expect revenue from Agents and Infra of $80.1 billion to $80.7 billion or growth of 24% to 25%. In Commercial bookings, we expect healthy growth in our commercial sales motions, though results will be impacted by the significant Azure commitments signed in the prior year. Timing related to significant Azure commitments like these will result in material volatility in bookings, making quarterly growth rates less indicative of underlying sales execution.

先從部門指引開始。我們預期Agents and Infra營收為801億至807億美元，成長24%至25%。在商業訂單（Commercial bookings）方面，我們預期商業銷售動能將維持健康成長，但結果將受到前一年簽署的大額Azure承諾合約影響。此類重大Azure承諾的時點因素將使訂單出現顯著波動，使得單季成長率較難反映底層銷售執行狀況。

In Azure, we expect revenue growth of 49% to 50% in constant currency with continued efficiency gains across our CPU and GPU fleet, helping to offset some 3P GPU-as-a-service contracts that have been delayed to H2.

在Azure方面，我們預期以固定匯率計營收成長49%至50%；CPU與GPU機群持續的效率提升，將有助於抵銷部分延後至下半年（H2）的第三方GPU即服務（GPU-as-a-service）合約。

Customer demand continues to exceed available supply. And looking beyond Q2, year-over-year growth will continue to reflect the timing and scale of engineering efficiencies delivered in the quarter and new capacity adds, as well as a strong prior-year comparable that included accelerating growth in the second half.

客戶需求仍持續高於可用供給。展望第二季之後，年對年成長仍將反映本季交付的工程效率提升之時點與規模，以及新增產能，同時也受到去年同期基期偏強（包含下半年成長加速）的影響。

In M365 Commercial cloud, we expect growth of approximately 19% in constant currency, with FX expected to reduce reported growth by less than a point.

在M365商業雲方面，我們預期以固定匯率計成長約19%，匯率預期將使報表成長率降低不到1個百分點。

We expect continued momentum across our premium per-seat offerings and usage-based offerings, along with some improvement in execution across E3 and our standalone SKUs. Growth will be driven primarily by ARPU, with additional contribution from seats. And we continue to expect revenue growth to accelerate through the year. M365 consumer cloud revenue should grow in the low-teens, down sequentially as we lap the price impact noted earlier.

我們預期每席位高階方案與按使用量計費方案將持續保持動能，同時E3與獨立SKU的執行也會有所改善。成長主要由ARPU帶動，席位數亦將提供額外貢獻。我們仍預期營收成長將在全年逐步加速。M365消費者雲營收應可成長至低十位數百分比區間，但因前述價格影響進入比較基期，將較前一季放緩。

Productivity and Server Licensing revenue should decline in the mid- to high-single digits, down sequentially due to a lower expected mix of contracts that carry higher in-period revenue recognition. Quarterly growth can vary materially based on contract mix, product launch timing, and other transactional purchasing trends.

生產力與伺服器授權（Productivity and Server Licensing）營收應在中到高個位數百分比下滑，且因預期合約組合中可在當期認列較高營收的合約占比降低，將較前一季走弱。單季成長可能因合約組合、產品上市時點及其他交易型採購趨勢而出現顯著波動。

In Industry Solutions Cloud, we expect revenue growth to be in the mid- to high-single digits with continued impact from the bookings trends noted earlier.

在產業解決方案雲（Industry Solutions Cloud）方面，我們預期營收成長為中到高個位數百分比，並持續受到前述訂單趨勢的影響。

And in Frontier and Support Services, we expect revenue to grow in the low- to mid-single digits.

在Frontier與支援服務方面，我們預期營收成長為低到中個位數百分比。

Microsoft Cloud gross margin percentage should be roughly 65% down year over year as continued improvement in product level margins is more than offset by sales mix shift to Azure.

Microsoft Cloud毛利率預期約為65%，較去年同期下降；雖然產品層級毛利率持續改善，但銷售組合轉向Azure的影響更大。

In Devices and Consumer, we expect revenue to be $15.9 billion to $16.4 billion. Search and Advertising revenue ex tech growth should be in the low-double digits, driven by consistent trends in rate and volume, with overall Search and Advertising revenue expected to grow at a similar rate.

在裝置與消費者方面，我們預期營收為159億至164億美元。搜尋與廣告營收（扣除TAC）成長預期為低雙位數百分比，主要由費率與量的穩健趨勢帶動；整體搜尋與廣告營收預期也將以相近速度成長。

And in XBOX content and services, we expect revenue growth to be in the mid- to high-single digits up sequentially, driven by the timing of content launches across both third and first party.

在XBOX內容與服務方面，我們預期營收成長為中到高個位數百分比，較前一季上升，主要受第三方與第一方內容上市時點所帶動。

With content launch patterns through the year, we expect growth to be the strongest in the second quarter with some deceleration in Q3 and further moderation in Q4. Hardware revenue in Q2 should decline year over year.

隨著全年內容上市節奏，我們預期第二季成長最強，第三季將略為放緩，第四季進一步趨於溫和。第二季硬體營收預期將較去年同期下滑。

Windows OEM and devices revenue should decline in the mid-30s. Growth will continue to be impacted by elevated inventory levels, PC market demand, and a prior-year comparable that benefited from Windows 10 end of support. As in prior quarters, the range of potential outcomes remains wider than normal. We expect these trends to continue through the rest of the fiscal year.

Windows OEM與裝置營收應在約30%中段下滑。成長仍將受到偏高庫存水位、PC市場需求，以及去年同期受Windows 10終止支援帶動而受惠的比較基期影響。如同前幾季，可能結果的區間仍較正常更寬。我們預期這些趨勢將延續至本會計年度剩餘期間。

Therefore, at a total company level, revenue should be between USD96 billion and USD97.1 billion or growth of 18% to 19%. We expect COGS at USD32.7 billion to USD32.9 billion or growth of 26% to 27% and operating expense of USD18.5 billion to USD18.6 billion or growth of 9% driven by continued investment in R&D compute capacity and talent.

因此，以公司整體而言，營收應介於960億至971億美元之間，成長18%至19%。我們預期銷貨成本（COGS）為327億至329億美元，成長26%至27%；營業費用為185億至186億美元，成長9%，主要由持續投資研發運算產能與人才所帶動。

Our cost guidance across both COGS and OpEx includes an estimate for the recently announced employee voluntary exit offer. Operating margins should be down slightly year over year.

我們在銷貨成本與營業費用的成本指引中，已納入近期宣布的員工自願離職方案之估計影響。營業利益率預期將較去年同期小幅下降。

Excluding any impact from our investments in OpenAI, other income and expense is expected to be roughly negative $300 million as interest income will be more than offset by interest expense, which includes the interest payments related to data center finance leases. And we expect our Q2 effective tax rate to be approximately 20%.

不含我們對OpenAI投資的任何影響，其他收益與費用預期約為負3億美元，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）所超過。我們預期第二季有效稅率約為20%。

Next, capital expenditures. We expect CapEx spend will be over $50 billion. Therefore, for the calendar year, spend should be approximately $170 billion due to the 3P capacity delays noted earlier.

接下來是資本支出。我們預期資本支出（CapEx）將超過500億美元。因此，就曆年而言，支出應約為1,700億美元，原因是前述第三方（3P）產能延遲。

In the second half of the fiscal year, we currently expect CapEx spend to accelerate primarily from CPUs, inclusive of higher memory and storage costs and GPUs, as well as the 3P capacity deliveries that shifted to H2. And as we continue to improve the efficiencies of our infrastructure, each dollar of CapEx has the potential to support more revenue and higher returns over time.

在本會計年度下半年，我們目前預期資本支出將加速，主要來自CPU（包含較高的記憶體與儲存成本）與GPU，以及延後至下半年交付的第三方（3P）產能。隨著我們持續提升基礎設施效率，每一美元的資本支出都有機會在時間推移下支撐更多營收並帶來更高報酬。

Given our strong business performance, we expect to continue to remain free cash flow positive in FY27. To complement cash generated by the business and preserve financial flexibility, we will access additional sources of funding when we believe it is attractive to do so.

鑑於我們強勁的業務表現，我們預期在FY27將持續維持自由現金流為正。為了搭配業務所產生的現金並維持財務彈性，我們將在認為具吸引力時，取得額外資金來源。

In closing, we are off to a strong start to FY27 with accelerated growth across the Microsoft Cloud. Product improvements along with efficiency gains across our data center infrastructure and our first-party apps and agents are increasing the value and improving the outcomes we deliver to our customers. Delivering that value to our customers positions us for durable long-term growth.

最後，我們在FY27開局強勁，Microsoft Cloud各項業務成長加速。產品改進，以及我們資料中心基礎設施與第一方應用程式與代理（agents）的效率提升，正在提高我們為客戶創造的價值並改善交付成果。為客戶交付這些價值，使我們具備可持續的長期成長動能。

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

接下來進入問答，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.

謝謝你，Amy。現在我們進入問答。為了尊重其他與會者，我們請參與者每次僅提一個問題。

Operator, can you please repeat your instructions?

接線員，請你重複一次你的指示，好嗎？

(Operator Instructions) Adam Wood, Morgan Stanley.

(接線員指示) Adam Wood，摩根士丹利。

Hi. Thanks so much. (inaudible) alongside lower than expected CapEx and those better cloud gross margins sequentially. Can I ask, as incremental AI capacity comes online, what do you see is likely to be the more important driver of returns over the next few years, improving utilization and unit costs within Azure or your ability to monetize more layers of each workload across Fabric, Foundry, and Copilot?

嗨。非常感謝。(聽不清) 再加上低於預期的資本支出（CapEx），以及雲端毛利率較佳且呈現季增。我想請問，隨著新增的 AI 產能陸續上線，未來幾年您認為回報更重要的驅動因素會是什麼：是提升 Azure 內部的使用率與單位成本，還是您能夠在 Fabric、Foundry 與 Copilot 上，針對每個工作負載的更多層級進行變現的能力？

Thanks for the question, Adam. I would say all of the above. But I think the way we're coming at this is we have one pool and we want to get the pool to be as efficient and fungible. That's sort of the place where if I sort of think about all of the physics of how we're building out the data centers, all of the operational rigor with which we can bring up the capacity. And then, of course, how do we run the workloads that are optimized on our infrastructure.

謝謝你的問題，Adam。我會說以上皆是。但我認為我們的切入方式是：我們有一個資源池，我們希望讓這個資源池盡可能高效率且可互換（fungible）。如果我從我們如何擴建資料中心的各種「物理限制」來看，以及我們能以多嚴謹的營運方式把產能拉起來。然後，當然還有：我們如何在自家基礎設施上執行並最佳化工作負載。

And once you do that, then it's just a function of how we allocate it by looking at the demand signal. And even there, even in our new segment reporting, I think you kind of see it, which is Copilot. Copilot stateful database underneath it is WorkIQ. That gets used in Foundry, which is where people will build their multi-agent system for supply chain that spans both unstructured and structured. Of course, it uses a Postgres database in Azure. And then by the way, all the agentic work is registered in the Agent 365 and Perception manages the security of it.

而一旦做到這些，接下來就只是看需求訊號來決定如何分配。即便在我們新的分部揭露中，我想你也能看到這一點，也就是 Copilot。Copilot 底層的有狀態資料庫是 WorkIQ。它會在 Foundry 中被使用，人們會在那裡建置跨越非結構化與結構化資料的供應鏈多代理系統。當然，它也會使用 Azure 裡的 Postgres 資料庫。另外，所有代理式（agentic）工作都會登錄在 Agent 365，而 Perception 會管理其安全性。

So to us, at least, we look at all of this as the same infrastructure. Of course, we report to you in a variety of different products. But your core question of where is the margin going to come from? Where is the leverage going to come from? It's not going to come from anyone. It's going to come from every one of them, and it compounds when we work them across.

所以對我們而言，至少我們把這一切都視為同一套基礎設施。當然，我們會以各種不同產品的方式向各位揭露。但你核心的問題是：利潤率會從哪裡來？槓桿效益會從哪裡來？它不會只來自其中任何一個。它會來自每一個，而且當我們把它們串在一起運作時，效益會複利式累積。

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

我想——Adam，很抱歉如果我們漏聽了你問題的前半段。我想我們至少有聽到後半段。

Great. Yeah, it's very helpful. Thank you.

很好。是的，非常有幫助。謝謝。

Operator, next question, please.

接線員，請下一題。

Karl Keirstead, UBS.

Karl Keirstead，瑞銀（UBS）。

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

好的，謝謝。Amy 和 Satya，我想請你們拆解一下我認為本次電話會議中最關鍵的指標之一，也就是 12 月 Azure 以固定匯率計算的成長指引為 49% 到 50%。我可以想像其中有很多變數：你們正在上線的產能、分配給第三方客戶的比例、可能還有 OpenAI 的強勁表現；但也許你們可以稍微談談，在這個數字看起來（至少對我而言）相當亮眼的情況下，主要驅動因素有哪些。謝謝。

Thanks, Karl, for the question. Maybe I'll start by talking a little bit about Q1, and I think that will help to think through Q2 and even going forward. And it's not unrelated really to Adam's question at some level as well.

謝謝你的問題，Karl。也許我先談談第一季（Q1），我想這會有助於理解第二季（Q2）以及往後的情況。而且在某種程度上，這也與 Adam 的問題不無關聯。

In Q1, I would say the engineering teams have really delivered very, very good work in terms of improving efficiency at the platform layer. That is not just a statement around the efficiency of GPUs. It's a statement around the efficiency of every layer, how the app utilizes the platform and how Foundry utilizes the platform as well as the Azure platform itself.

在 Q1，我會說工程團隊在提升平台層效率方面，確實交出了非常、非常好的成果。這不只是關於 GPU 效率的說法；而是涵蓋每一層的效率：應用程式如何使用平台、Foundry 如何使用平台，以及 Azure 平台本身的效率。

Those efficiencies, they're sort of ground out every week. And you have good ideas, a lot work, some don't, and you stay at it. So they're not maybe as predictable in terms of how much impact we'll get in quarter. Q1, they did a very good job, and you saw some of that result in us being able to put more allocation into Foundry in the quarter.

這些效率提升，是每週一點一滴磨出來的。你會有好點子，也會做很多工作，有些有效、有些無效，但你會持續投入。因此，就每一季能帶來多大影響而言，可能不那麼可預測。Q1 他們做得非常好，你也看到其中一些成果，讓我們在該季能把更多資源分配到 Foundry。

That's a great thing because we're, as I said in the call, we still have demand that exceeds supply. So where we can have our engineering teams deliver those efficiencies, we do really try to put it into Foundry when we can because it's so important, as Satya talked about, into how customers broadly are building what I would call against a new stack.

這是很棒的事情，因為如我在電話會議中所說，我們仍然是需求大於供給。所以只要工程團隊能交付這些效率提升，我們就會在可行時盡量把它投入 Foundry，因為正如 Satya 所談到的，這對客戶廣泛地在我所稱的「新技術堆疊」上進行建置非常重要。

Secondly, and you mentioned it, token pricing will create a little bit of variability. We had higher token pricing than we expected in the quarter with some high-quality models that we're able to take advantage of and see good margins on do benefit us in the quarter, that did happen in Q1.

第二點，你也提到了，token 定價會帶來一些波動。本季我們的 token 定價高於預期；我們能運用一些高品質模型，並在其上取得良好毛利，這確實在 Q1 對我們有利。

And I think -- also in that number in Q1 was the efficiency that I talked about applied not just to our GPU fleet, but I think people sort of underestimated when the example Satya gave for Adam's question, that's the GPU/CPU storage memory workload. I mean, it takes all of the pieces. And so our ability to also create additional capacity within our existing fleet. It gave us some room to be able to convert that actually pretty quickly as well in Q1.

另外，我想——Q1 的那個數字也包含我剛提到的效率提升，這些提升不只應用在我們的 GPU 機群；我認為人們可能低估了 Satya 在回答 Adam 問題時舉的例子，那其實是 GPU/CPU、儲存、記憶體等工作負載的組合。我的意思是，它需要所有組件一起配合。因此，我們也能在既有機群中創造額外產能。這讓我們在 Q1 也有一些空間，能夠相當快速地把這些轉換出來。

So in Q2, we've got those efficiency gains, which is great, and those will continue into Q2. We need to find some more, which we're counting on, enable to get to that guidance that I gave because I have faith in the team's work in Q1 continuing into Q2. But we also need that work to be able to help us a little bit because we had some supply we were counting on Q2 move out into H2.

所以在 Q2，我們有這些效率增益，這很好，而且會延續到 Q2。我們還需要再找到一些（效率），我們也把這點納入我所給出的指引之中，因為我相信團隊在 Q1 的工作會延續到 Q2。只是我們也需要這些工作在某種程度上幫我們一把，因為我們原本預期在 Q2 會到位的一些供給，已經延後到下半年（H2）。

And so I think and to your point, there's also some unknown on some token pricing through the quarter that stuff can change. So I think I feel good in terms of the efficiency gains that we saw, when we're able and when I'm able to see those and put them in, I feel good about guiding to that. But as other things are less predictable, I hope that's helpful on the levers, Karl.

所以我想，回到你提到的點，本季 token 定價也仍有一些不確定性，這些事情可能會變動。因此，就我們看到的效率增益而言，我感覺良好；當我能看到這些增益並把它們納入規劃時，我對給出那樣的指引是有信心的。但其他因素較難預測；希望這能幫助你理解這些槓桿，Karl。

Yeah, it is. Thanks, Amy.

是的，確實有幫助。謝謝，Amy。

Thanks, Karl. Operator, next question, please.

謝謝，Karl。接線員，請下一題。

Mark Moerdler, Bernstein Research.

Mark Moerdler，Bernstein Research。

Thank you very much for taking my question. Congratulations on the solid quarter and the solid guidance. It's really nice to see how well you guys are executing.

非常感謝讓我提問。恭喜本季表現穩健，指引也很扎實。很高興看到你們的執行力如此出色。

I'd like to get a sense on the drivers of the AI strength in Azure being from enterprise versus digitally native in general or AI native. With inferencing starting to ramp and Microsoft the go-to for enterprises, how should we think, Amy, about the mix of enterprise customer workloads within overall workloads at this point?

我想了解一下，Azure 的 AI 強勁成長，其驅動力主要來自企業客戶，還是整體而言更多來自數位原生（digitally native）或 AI 原生（AI native）客戶。隨著推論（inferencing）開始加速成長，且微軟成為企業客戶的首選，Amy，我們現在應該如何看待企業客戶工作負載在整體工作負載中的占比？

And Satya, with the strong growth of the Azure AI platform offering, can you give us color on what's driving that? Is it, again, enterprise, is it digitally native? Obviously, it's a mix of both, but any color that shows the ramp of that enterprise I think would be valuable.

另外，Satya，隨著 Azure AI 平台產品的強勁成長，你能否提供一些背景說明其驅動因素？是否同樣是企業客戶？還是數位原生客戶？顯然兩者都有，但若能提供一些能反映企業端加速導入的資訊，我想會很有價值。

Yeah, thanks for the question, Mark. Maybe I'll start, and Amy, you can add to it. I was even in Europe just last week, and it was great to see the quality of the agentic systems that are just broadly getting deployed. When Unilever deploys what is their automated order taking and trade coupon dispute management stuff, all as a fully agentic touchless system.

是的，Mark，謝謝你的提問。也許我先開始，Amy 你可以再補充。我上週甚至還在歐洲，看到各種代理式（agentic）系統正在被廣泛部署，品質非常好。像是聯合利華（Unilever）部署了自動化接單與通路折價券爭議管理等功能，全部都是完整的代理式免接觸（touchless）系統。

Rolls-Royce deploys the system to really manage all of their maintenance of whatever their jet engines with 30,000 parts are pretty complex supply chain, both planning, execution, inventory management system, all built on Foundry agentic systems.

勞斯萊斯（Rolls-Royce）部署了系統，真正用來管理其噴射引擎維修相關的一切；噴射引擎有 30,000 個零件，供應鏈相當複雜，涵蓋規劃、執行、庫存管理系統，全部建立在 Foundry 的代理式系統之上。

RBI, which is an Austrian bank, showed me 20-plus business processes end-to-end. And they were talking about like whether it's in for credit or what have you -- how they are able to now do that so much more optimally, right?

RBI（奧地利的一家銀行）向我展示了 20 多個端到端的業務流程。他們談到例如授信或其他事項——他們現在如何能以更優化的方式來完成，對吧？

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

所以在廣度、品質、以及他們的能力——喔，順帶一提，還有它的多模型特性（multi-model nature），對吧？他們先從前沿模型（frontier model）開始。其中很多案例，事實上像聯合利華那個，他們剛剛下線了一個使用我們的 traces 訓練的 MAI 模型。所以就連我所認為的模型最佳化、工作負載最佳化、token 最佳化的成熟度，都非常令人驚艷。所以這個廣度正在開始展開。

Finally, it does feel like the enterprise workloads that feel like to me, like the database applications enterprises built in the past that I grew up with happening now when it comes to AI.

最後，確實讓人感覺企業工作負載正在發生——對我而言，就像我成長過程中企業過去建立的資料庫應用那樣——現在在 AI 上也正在發生同樣的事。

And in fact, if anything, some of the shiny object stuff is waning, which is not about the next big thing, they're really more about, wow, can I build a system, can I own the weights, can I manage my costs, can I have reliability, what about security.

而且如果要說的話，一些追逐「亮點」的東西正在退燒；大家不再只是談下一個大事件，而是更關注：哇，我能不能建一個系統、能不能擁有權重（weights）、能不能管理成本、能不能有可靠性、安全性怎麼辦。

And so in that sense, the enterprise breadth motion is starting. But like everything else, the enterprise stuff is not like a quarter over quarter, it's a decade long thing and that's what I've been waiting for as opposed to like four customers who buy a lot of capacity from you and you can show a few quarters of growth and that's not a business as far as I'm concerned.

因此從這個意義上說，企業端「廣度擴張」的動能正在啟動。但就像其他事情一樣，企業端不是那種季對季的事情，而是長達十年的事情；這正是我一直在等待的，而不是像只有四個客戶向你買很多算力，你就能展示幾季成長——在我看來那不算是一門生意。

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

所以我想要的是廣度；我們在廣度上具備很好的定位，而且也有大型客戶想向我們採購，我們也已經準備好以此開展業務。只要定價合適，我們就可能賣給他們一些。如果不合適，我們會有耐心去建立這個（聽不清）之廣度。

Thanks, Mark. Operator, next question, please.

謝謝你，Mark。接線員，請下一題。

Gabriela Borges, Goldman Sachs.

Gabriela Borges，高盛（Goldman Sachs）。

Hi, good evening. Thank you. Satya, I want to stay on the topic of breadth because you had a comment in the prepared remarks talking about how MAI can now be comparable to leading models within three to six months of their release.

嗨，晚安。謝謝。Satya，我想延續「廣度」這個主題，因為你在事先準備的講稿中提到，MAI 現在可以在領先模型發布後三到六個月內達到可比水準。

At the same time, you have OpenAI at 11% of revenue in the quarter. So maybe just take a step back and give us your latest thinking on how you think token mix and token value is going to evolve between the frontier MAI and maybe what some of your more sophisticated enterprise customers are doing from a proprietary AI strategy standpoint? Thank you.

同時，你們本季 OpenAI 相關收入占比為 11%。所以也許請你退一步，談談你最新的看法：你認為 token 組合（token mix）與 token 價值（token value）將如何在前沿 MAI 與一些更成熟的企業客戶（從專有 AI 策略角度）之間演進？謝謝。

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

是的，所以我認為——事實上我會說，你應該把任何工作負載可用的工具箱想成三件事。第一是有新模型發布，它在某些性能上表現很棒；你可以在你在意的指標上把評估（eval）拉到最大，也就是用它來達成你在意的結果。大家就應該使用它。我們在上一季的一些 OpenAI 模型上就看到了這點。它們是非常出色的模型。而且我們當然也非常振奮於 OpenAI 在 Astra 上取得的進展，以及接下來將推出的內容。我認為我們也看到那方面有不錯的需求。

Then the next thing people do is, hey, can I actually put multiple of the frontier models because these are very different prices. In fact, this morning, artificial analysis had what I think is the real benchmark, which is the coding agents using our Fusion. And I think we were number two or number three there, which is awesome to see, which is you can now get frontier performance 45% faster, 75% cheaper. Like, who would want to not take that, right?

接著人們會做的下一件事是：嘿，我能不能把多個前沿模型放進來，因為它們的價格差異很大。事實上，今天早上 Artificial Analysis 發布了我認為真正的基準測試：使用我們 Fusion 的程式碼代理（coding agents）。我記得我們在那裡是第二或第三名，看到這點很棒；這表示你現在可以用快 45%、便宜 75% 的方式取得前沿等級的表現。這種情況下，誰會不想採用呢，對吧？

If you're a coding agent user, you want, in fact, Anthropic and OpenAI, by the way, to compete for your workload, not like once a quarter, but for every task. And that to me is what the value of these routers and auto Fusion stuff routing does, and we are very excited about it.

如果你是程式碼代理的使用者，你其實希望 Anthropic 和 OpenAI——順帶一提——為了你的工作負載競爭，不是每季一次，而是每一個任務都在競爭。而對我來說，這就是這些路由器（routers）以及自動 Fusion 路由所帶來的價值，我們對此非常興奮。

And then the last thing is another important one. A lot of customers are saying, hey, look, take the Unilever one, right? It's their system. They will ultimately take even the traces after having done even a bunch with frontier models, and they just want to train their own model. So it can be open weights, or in this case, it was MAI model.

最後一點也同樣重要。很多客戶在說：嘿，你看，以聯合利華那個案例來說，對吧？那是他們的系統。他們最終甚至會在用前沿模型做了很多事情之後，把 traces 拿來，然後他們就是想訓練自己的模型。所以可以是開放權重（open weights），或者像這個案例一樣，是 MAI 模型。

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

所以我認為以上所有都需要作為可用選項提供。然後依據定價、依據客戶需求，他們會去採用。而且這裡有時間性。它從來不是「喔，我從某個地方開始就停在那裡」，對吧？而是：我可能從前沿開始，我可能轉到開放權重，我可能轉到 MAI 模型，我也可能在下一次新模型發布時回到前沿用幾個月，然後再退出。這就是我認為這些工作負載的動態性。因此當我們思考 Foundry、或思考 Fabric、或思考 Copilot 時，我們真正想打造的是一個模型系統，能持續為客戶交付價值，而不是讓他們被卡在任何單一選項上。

Operator, next question please.

接線員，請下一題。

Brent Thill, Jefferies.

Brent Thill，Jefferies。

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

謝謝。Amy，很高興見到你——當你們接近 50% 時，你們還有另一個科目也接近 50%，那就是營業利益率。我想很多人會問：在營收端接近 50%、獲利端也接近 50% 的情況下，你們如何維持這樣的成長水準？也許你可以談談你們持續推動哪些營運改善，以維持如此高的獲利水準。

Thanks, Brent. Let me first say the best solution here is revenue growth. And so I would say I tend to start and focus there even though I think many people seem to think I start at the bottom of the P&L and work up. The right answer is you always start at the top of the P&L and work down.

謝謝，Brent。我先說，這裡最好的解法是營收成長。所以我會說，我傾向從那裡開始並聚焦，即使我認為很多人似乎覺得我是從損益表（P&L）底部往上推。正確答案是：你永遠要從損益表的最上方開始，然後往下推。

And so what we've been focused on and I think really it's almost inherent in all of the commentary is we change segments because we're changing how we deliver products and services to customers. We're changing it because we're delivering new and different products with a lot of value in them, and those products are far more integrated than they were before.

因此我們一直聚焦的事情——我認為其實幾乎也內含在所有評論之中——是我們在調整分部（segments），因為我們正在改變向客戶交付產品與服務的方式。我們之所以改變，是因為我們正在交付全新且不同、且內含大量價值的產品，而這些產品的整合度遠比以前更高。

I think when you see that revenue accelerate at the top line, of course, it does in a pretty healthy way contribute to positive margin and part of the positive margin is dollars, which I think I need people to also focus on.

我認為，當你看到營收在頂線加速成長時，當然，這會以相當健康的方式促進正向的利潤率；而正向利潤率的一部分是以美元計的貢獻，我認為大家也需要把焦點放在這一點上。

The second piece is there's real focus on efficiency because efficiency, when we say the word, I think people believe it's cost-related. The outcome is cost-related, but the real benefit of efficiency is stability, it's security, it's reliability, is that it delivers the highest-quality unit at the lowest possible cost. And so it's operational excellence.

第二點是，我們確實非常專注於效率，因為當我們說到「效率」這個詞時，我想大家會以為它與成本有關。結果確實與成本相關，但效率真正的好處是穩定性、安全性與可靠性——也就是以最低可能的成本交付最高品質的單位產出。因此，這是營運卓越。

And so I think when you think about you can deliver product excellence, which is what we're really focused on, I think we did a very good job on product quality in the past quarter, which I think teams should be proud of in lots of places. I think then you have this sort of operational focus on improvement.

因此我認為，當你想到你能交付產品卓越——這正是我們真正專注的——我認為我們在上一季的產品品質上做得非常好，我想各團隊在很多方面都應該為此感到自豪。接著，你會有這種在營運面聚焦於改善的作法。

And then it is a real focus in terms of operating expense to make sure it's going toward building the new thing or providing security and quality. And I think that we've made, I think, a very active choice to be really focused on those two things, especially in this environment and how important it is.

然後，在營運費用方面也會有真正的聚焦，以確保支出是用在打造新事物，或提供安全性與品質上。我認為我們做出了一個非常積極的選擇，把焦點牢牢放在這兩件事上，尤其是在這樣的環境下，以及它的重要性。

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

我認為，當你做到這些事，而你又剛好處在一個市場狀況良好、客戶覆蓋面廣、且業務全球化的情境下，我們就看到了不錯的成果。尤其是本季，當你在一季之內交付大量效率提升，同時又能在不增加額外成本的情況下實現營收成長，你當然會看到效益——我們確實看到了。但我對這個數字背後的因素感到很有信心，也就是我認為我們把焦點放在正確的槓桿上。

Thanks, Brent. Operator, next question, please.

謝謝，Brent。接線員，請下一題。

Brad Reback, Stifel.

Brad Reback，Stifel。

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

好的。抱歉剛剛那樣。我沒有聽到叫到我的名字。關於 M365 的用量（consumption），當你們把 GitHub 從按席位（per seat）模式轉為用量計費模式時，為你們解鎖了大量的營收成長。當你們思考現在用量端的工具，對於核心 M365 客戶而言要如何解鎖——你認為這個解鎖會很快、且不需要銷售投入，還是需要相當多的努力才能讓那些計量表開始轉動？謝謝。

Yeah, thanks for the question. I think on the coding side, it will be faster just because I think people are used to paying on this pay-go as the sort of the general market and how it works. And if anything, hopefully, some of the things that we announced even at GitHub Universe today with Fusion are a more attractive way. Because if you think about it, you buy a bunch of credits and you want to use those credits most efficiently, that's the promise of GitHub Copilot Fusion. So we are very optimistic about making progress on that.

是的，謝謝你的問題。我認為在程式開發（coding）這一側會更快，因為我想大家已經習慣以這種隨用隨付（pay-go）的方式付費，這也是一般市場的運作方式。而且如果有什麼的話，希望我們今天在 GitHub Universe 上宣布的一些內容（包含 Fusion）會是更具吸引力的方式。因為你想想看，你買了一堆點數（credits），你希望最有效率地使用這些點數——這就是 GitHub Copilot Fusion 的承諾。所以我們對在這方面取得進展非常樂觀。

And then when it comes to Copilot itself, we are trying to make sure that we in some sense are driving more and more value into the subscription with every model drop and essentially consolidating the frontier gains for broad deployment. And in many instances, as my remarks said, IT funds this, that's the thing that you want to have standard issue across the board.

接著談到 Copilot 本身，我們正努力確保在某種意義上，隨著每一次模型更新（model drop），我們都把更多價值注入訂閱中，並且基本上把前沿能力的提升整合起來，以利於廣泛部署。而在很多情況下，正如我剛才的發言所說，這是由 IT 來出資；你會希望它成為全公司標配的那種東西。

And at the same time, you have your pay-as-you-go or consumption meters for places where you need it. And so both of those options are open. And I think that's why the Copilot referenced, which is we are trying to make sure that customers understand both options, they're able to use the two options in the optimal way that benefits them.

同時，你也會有隨用隨付或用量計費的計量表，適用於你需要它的地方。因此，這兩種選項都存在。我想這也是我提到 Copilot 的原因：我們正努力確保客戶理解這兩種選項，並能以對他們最有利的最佳方式使用這兩種選項。

We don't want them to overbuy one thing and then feel like they're token maxing because that doesn't serve anybody's purpose. We want to make sure that they understand the value of the subscription and how it's a continually improving value. It's not even static. And at the same time, you can exercise this consumption meter.

我們不希望他們在某一項上買太多，然後覺得自己在把 token 用到上限，因為那對任何人都沒有幫助。我們希望確保他們理解訂閱的價值，以及它是一個持續提升的價值。它甚至不是靜態不變的。同時，你也可以使用這個用量計費的計量表。

And so that's a little bit of the degree of sophistication in both in our sales motions, even a customer's understanding that's, I think, coming together. We feel very good about the progress, but a lot more to do.

因此，這在我們的銷售推進方式上，以及客戶的理解上，都需要一定程度的成熟度；我認為這些正在逐步到位。我們對進展感到非常滿意，但仍有很多工作要做。

And I think I would say it's also why we've made the investment into the frontier company here, coupled with changes in our sales motion, which I talked a little bit about. We need both of those things to make sure customers are -- because what I think we want them to utilize both the Copilot license to its fullest and understand when the consumption meter is delivering value to them.

我想我也會說，這也是為什麼我們在這裡對前沿公司（frontier company）進行投資，同時搭配我稍早提到的銷售推進方式的改變。我們需要這兩者，才能確保客戶——因為我認為我們希望他們能把 Copilot 授權用到極致，同時也理解在什麼時候用量計費的計量表能為他們帶來價值。

The investment in the FDE organization or the Frontier core, as well as new motions within our modern work in Microsoft 365 sales teams are both meant to do that. And I think to Satya's point, it will be a slower move outside of coding. But I also still think we're still seeing encouraging signs, and I feel positive about that.

對 FDE 組織或 Frontier core 的投資，以及我們在現代工作（modern work）的 Microsoft 365 銷售團隊內導入的新推進方式，目的都是為了做到這一點。而且我認為就像 Satya 所說，離開 coding 場景之後，推進會比較慢。但我也仍然認為我們看到令人鼓舞的跡象，我對此感到正向。

Thank you.

謝謝。

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

謝謝，Brad。接線員，我們還有時間再問最後一題。

Tal Liani, Bank of America.

Tal Liani，美國銀行（Bank of America）。

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

我想釐清你剛才說的一件事。你們這一季有揭露 Copilot 的數字嗎？不過我的問題更多是關於資本承諾或資本策略。你在事先準備的講稿中提到，若未來有需要，你們會考慮籌資。你能談談你們在債務、股權以及其他來源之間的策略嗎？如果有需要，你們打算如何籌資？謝謝。

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

好的。我來回答。我想我說的是：如果它具有吸引力而且合理的話。我們很幸運，在籌措資金的能力方面有很大的彈性。我以前談過這點。有一種融資形式叫做租賃（leasing），我們一直把它當作一種工具在使用。另外——我們也很幸運，基於我們的信用評等等因素，我們能進入債券市場；而且我會說，我們還沒有、也尚未真正去動用那一塊。當然，還有其他選項。

But I think the way I see it is we're feeling good that we're free cash flow positive. We feel good that the return on every dollar of CapEx we're spending, we're confident in that. And therefore, we feel like we have lots of options to be able to tap the financing markets when they make sense and they're attractive.

但我認為我的看法是：我們對自由現金流為正感到很有信心。我們也對每一美元資本支出（CapEx）所帶來的回報感到很有把握。因此，我們覺得自己有很多選項，可以在合理且具吸引力時進入融資市場。

And we did not disclose, to answer your direct question, update on the Copilot number this quarter. We talked about momentum in revenue and usage.

另外，直接回答你的問題：我們本季沒有揭露 Copilot 數字的更新。我們談的是營收與使用量的動能。

Thank you.

謝謝。

Thanks, Tal. That wraps up the Q&A portion of today's earnings call.

謝謝，Tal。以上是今天財報電話會議的問答環節。

Thank you for joining us today, and we look forward to speaking with all of you soon.

感謝各位今天加入，我們期待很快再與各位交流。

Thank you.

謝謝。

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

謝謝。今天的會議到此結束。您現在可以掛斷電話線，並感謝您的參與。