甲骨文 (ORCL) 2026 Q3 法說會逐字稿

Hello, and thank you for standing by. My name is Regina, and I will be your conference operator today. At this time, I would like to welcome everyone to the Oracle Corporation third-quarter fiscal year 2026 earnings conference call. (Operator Instructions)

您好，感謝您的耐心等待。我叫雷吉娜，今天我將擔任你們的會議接線生。在此，我謹代表甲骨文公司歡迎各位參加2026財年第三季財報電話會議。（操作說明）

I would now like to turn the conference over to Ken Bond, Head of Investor Relations. Please go ahead.

現在我將把會議交給投資者關係主管肯·邦德。請繼續。

Thank you, Regina, and good afternoon, everyone. Welcome to Oracle's third-quarter fiscal year 2026 earnings conference call.

謝謝你，雷吉娜，大家午安。歡迎參加甲骨文公司2026財年第三季財報電話會議。

On the call today, our Chairman and Chief Technology Officer, Larry Ellison; Chief Executive Officer, Clay Magouyrk; Chief Executive Officer, Mike Sicilia; and Principal Financial Officer, Doug Kehring.

今天參加電話會議的有：董事長兼技術長 Larry Ellison；執行長 Clay Magouyrk；執行長 Mike Sicilia；以及財務長 Doug Kehring。

A copy of the press release and financial tables, which includes supplemental financial details on our most recent quarter, guidance for our future results, a GAAP to non-GAAP reconciliation, and a selected list of customers who purchased Oracle Cloud services or went live on Oracle Cloud recently, will be available from our Investor Relations website.

新聞稿和財務報表的副本（其中包括我們最近一個季度的補充財務詳情、未來業績指引、GAAP 與非 GAAP 調整表以及最近購買 Oracle 雲端服務或上線 Oracle 雲端服務的部分客戶名單）將在我們的投資者關係網站上提供。

As a reminder, today's discussion will include forward-looking statements, and we will discuss some important factors relating to our business. These forward-looking statements are also subject to risks and uncertainties that may cause actual results to differ materially from the statements being made today. As a result, we caution you from placing undue reliance on these forward-looking statements, and we encourage you to review our most recent reports, including our 10-K and 10-Q, and any applicable amendments.

提醒各位，今天的討論將包含前瞻性陳述，我們將討論一些與我們業務相關的重要因素。這些前瞻性陳述也存在風險和不確定性，可能導致實際結果與今天所作的陳述有重大差異。因此，我們提醒您不要過度依賴這些前瞻性聲明，並鼓勵您查看我們最新的報告，包括我們的 10-K 和 10-Q 報告以及任何適用的修訂。

Finally, we are not obligating ourselves to revise our results or these forward-looking statements in light of new information or future events. Before we go to the Q&A portion of the call, we'll begin with a few prepared remarks.

最後，我們不承擔因新資訊或未來事件而修改業績或這些前瞻性聲明的義務。在進入問答環節之前，我們先來做一些事先準備好的發言。

And with that, I'll turn it over to Doug.

那麼，接下來就交給道格了。

Thanks, Ken. Let me start by highlighting the changes we're making to our earnings press release and this call.

謝謝你，肯。首先，我想重點介紹一下我們對獲利新聞稿和本次電話會議所做的更改。

In the press release, we have laid out clearly and explicitly the supplemental financial metrics that we otherwise would have provided on the earnings call so that each of you has the information in writing and in advance. Then as it relates to our approach to the earnings call itself, I will be very brief and then turn it over to Mike and Clay to provide more substantial thoughts on our business. After which all of us, including Larry, will be available to take questions.

在新聞稿中，我們清楚明確地列出了原本會在財報電話會議上提供的補充財務指標，以便各位都能提前獲得書面資訊。至於我們對財報電話會議本身的處理方式，我將簡要說明，然後交給 Mike 和 Clay，讓他們就我們的業務提供更實質的想法。之後，包括拉里在內的我們所有人都會回答問題。

In terms of the results for Q3, we had a tremendous quarter that exceeded expectations across the board. Our momentum continues to accelerate with Q3 being the first quarter in over 15 years where both organic total revenue and organic non-GAAP EPS grew at 20% or better in USD, as we highlighted in the press release.

就第三季業績而言，我們取得了巨大的成功，各項指標都超乎預期。正如我們在新聞稿中所強調的那樣，我們的成長勢頭持續加速，第三季是 15 年多來第一個有機總收入和有機非 GAAP 每股收益均以美元計價增長 20% 或以上的季度。

I'll quickly mention a couple of things and then hand the call over to our CEOs. First, in January, TikTok US completed the separation of its US data operations from ByteDance into an independent company in which Oracle now holds a 15% equity stake along with a seat on the Board.

我先簡單提幾件事，然後把電話交給我們的執行長們。首先，今年 1 月，TikTok 美國完成了將其美國數據業務從位元組跳動剝離，成立了一家獨立公司，甲骨文目前持有該公司 15% 的股權，並在董事會中佔有一席之地。

In terms of impact to our financials, there is no impact to the revenue related to the services we have been providing. As to the equity investment, we will be accounting for this under the equity method, and we will recognize our share of the new company's earnings for the period from the close of the investment in late January to March 31 in our Q4 results as there is there is a two-month reporting period time lag. It will be recorded as non-operating income or loss on our income statement and is incremental and additive to our financials.

就對我們財務狀況的影響而言，我們所提供服務相關的收入並未受到影響。至於股權投資，我們將採用權益法進行核算，並將我們在新公司1月下旬投資完成至3月31日期間應佔的收益份額計入第四季度業績，因為存在兩個月的報告期滯後。它將作為非經營性收入或損失記錄在我們的損益表中，並且是對我們財務狀況的增量和加性影響。

Second, in February, we announced our intent to raise up to $50 billion in debt and equity financing along with the statement that we do not expect to issue any additional bonds beyond this amount in calendar year 2026.

其次，在 2 月份，我們宣布了籌集高達 500 億美元的債務和股權融資的計劃，並聲明我們預計在 2026 年日曆年內不會發行超過此金額的任何額外債券。

Within days of the announcement, we raised $30 billion through a combination of investment, trade bonds, and mandatory convertible preferred stock with a record order book that was substantially oversubscribed. As noted in our release, we have not yet initiated the at-the-market equity portion of the financing program.

公告發布後幾天內，我們透過投資、貿易債券和強制性可轉換優先股的組合籌集了 300 億美元，訂單簿創下紀錄，並獲得了大幅超額認購。正如我們在新聞稿中所述，我們尚未啟動融資計劃中的以市場價格發行股票部分。

Finally, I'd be remiss not to remind everyone, we are reporting our financial results just 10 days after the last day of the quarter, despite the increasing size and complexity of our business.

最後，我不得不提醒大家，儘管我們的業務規模和複雜性不斷增加，但我們仍然在季度末結束後的短短 10 天內公佈了財務業績。

Using Oracle Fusion, we continue to close and file our financial results faster than any other company in the S&P 500, providing us with a significant strategic advantage as well as an opportunity to help our Fusion customers do the same with their businesses.

透過 Oracle Fusion，我們能夠比標準普爾 500 指數中的任何其他公司更快地完成財務結算和提交財務報告，這為我們提供了重要的策略優勢，同時也為我們提供了幫助我們的 Fusion 客戶在其業務中實現同樣目標的機會。

With that, let me now turn the call over to Mike.

那麼，現在讓我把電話交給麥克。

Thanks, Doug. And as Doug just detailed, we really had an excellent quarter across the board and continue to see strong execution. So let me say a few words about our applications business.

謝謝你，道格。正如道格剛才詳細介紹的那樣，我們本季整體表現非常出色，並且繼續保持著強勁的執行力。那麼，讓我簡單介紹一下我們的應用程式業務。

Oracle has the fastest-growing, most complete suite of cloud applications in the market, full stop. Our SaaS solutions are industry complete platforms with highly scalable, trusted, secure, and regulatory compliance systems and processes in which our customers trust us to run the systems that run their businesses.

Oracle 擁有市場上成長最快、最完整的雲端應用套件，毋庸置疑。我們的 SaaS 解決方案是業界完整的平台，擁有高度可擴展、值得信賴、安全且符合監管規定的系統和流程，我們的客戶信任我們來運行他們業務所需的系統。

In constant currency, cloud applications revenue was up 11% of the quarter, reaching an annualized run rate of $16.1 billion. Within that, Fusion ERP was up 14%, Fusion SCM up 15%, Fusion HCM up 15%, Fusion CX up 6%, NetSuite was up 11%, industry staff solutions for hospitality, construction, retail, banking, restaurants, local governments, and telecommunications combined were up 19%. So certainly, very happy with the applications growth in the quarter.

以固定匯率計算，雲端應用營收本季成長 11%，年化運作率為 161 億美元。其中，Fusion ERP 成長 14%，Fusion SCM 成長 15%，Fusion HCM 成長 15%，Fusion CX 成長 6%，NetSuite 成長 11%，旅館、建築、零售、銀行、餐飲、地方政府和電信等產業的員工解決方案合計成長 19%。所以，我對本季的應用成長非常滿意。

In the context of that, I'll say a few words about the reported SaaS apocalypse. You've all heard the thesis or theory that new companies coding quickly using AI will spell the death of SaaS. I don't agree with that at all.

在此背景下，我想就報道中的 SaaS 末日說幾句。你們都聽過這樣一種觀點或理論：利用人工智慧快速編寫程式碼的新公司將導致 SaaS 的消亡。我完全不同意這種說法。

I do think that AI tools and their coding capabilities would be a threat if we weren't adopting them, but we are, and very rapidly. Oracle is using the best AI coding tools and the best developers not only to accelerate our SaaS business, but to deliver solutions that enable entire ecosystems across numerous industries. The use of AI coding tools inside Oracle is enabling smaller engineering teams to deliver more complete solutions to our customers more quickly. We are building brand-new SaaS products using AI and also embedding AI agents right into our existing applications suites.

我確實認為，如果我們不採用人工智慧工具及其編碼能力，它們將會構成威脅，但我們正在採用，而且速度非常快。Oracle 正在利用最好的 AI 編碼工具和最好的開發人員，不僅加速我們的 SaaS 業務，而且還提供能夠支援許多行業整個生態系統的解決方案。Oracle 內部使用 AI 編碼工具，讓規模較小的工程團隊能夠更快地為客戶提供更完整的解決方案。我們正在利用人工智慧建立全新的SaaS產品，並將人工智慧代理直接嵌入到我們現有的應用程式套件中。

By embracing AI with small engineering teams, we have just built three brand-new CX applications: Lead Generation and Qualification, Sales Orchestration and Automated Selling, and our new Website Generator. In fact, we just use the Website Generator to build and launch the new oracle.com.

透過與小型工程團隊合作，運用人工智慧技術，我們剛剛建立了三個全新的客戶體驗應用程式：潛在客戶開發和資格審查、銷售協調和自動化銷售，以及我們全新的網站產生器。事實上，我們只是使用網站產生器來建立和發布新的oracle.com網站。

We've built these new CX products to help our customers sell, not simply to administer a forecast or generate email opens. These are three products that salesforce.com does not have. And of course, salesforce.com also doesn't have OCI, the AI data platform, Fusion ERP, and complete industry suites. Complete AI-powered end-to-end ecosystem automation platforms are quite unique to Oracle.

我們開發這些新的客戶體驗產品是為了幫助我們的客戶進行銷售，而不僅僅是為了管理預測或提高電子郵件開啟率。salesforce.com 沒有這三款產品。當然，salesforce.com 也沒有 OCI（人工智慧資料平台）、Fusion ERP 和完整的行業套件。完整的、由人工智慧驅動的端到端生態系統自動化平台是 Oracle 獨有的。

In addition to that, we've already delivered well over 1,000 agents right inside our horizontal back office and industry applications. This doesn't even include the agents that our customers are building themselves or the fleet of agents that we're using internally. These are AI features built right into our applications and existing processes. And a great example, I think, is in healthcare where our brand-new AI-powered ambulatory EHR, electronic health record, system is live in the market, and the results are quite clear. We're reducing administrative overhead, we're allowing clinicians to see more patients, we're improving access to care, and we're increasing provider satisfaction.

除此之外，我們已經在我們的橫向後台和行業應用程式中交付了超過 1000 個代理程式。這還不包括我們的客戶自行建立的代理，也不包括我們內部使用的代理團隊。這些都是直接內建在我們的應用程式和現有流程中的人工智慧功能。我認為，醫療保健領域就是一個很好的例子，我們全新的人工智慧驅動的門診電子健康記錄 (EHR) 系統已經投入市場，結果非常明顯。我們正在減少行政開支，讓臨床醫生能夠接收更多患者，改善醫療服務取得途徑，並提高醫護人員的滿意度。

And another example in banking, we provide a comprehensive AI-powered SaaS platform including everything from commercial banking, retail banking, investment banking, anti-money laundering, financial crimes and compliance, payments, supply chain financing, CX, ERP, and HCM. That banking suite alone contains hundreds of embedded AI agents, all available at no additional cost to our customers.

銀行業的另一個例子是，我們提供全面的人工智慧驅動的 SaaS 平台，涵蓋商業銀行、零售銀行、投資銀行、反洗錢、金融犯罪和合規、支付、供應鏈融資、客戶體驗、企業資源計劃和人力資本管理等各個方面。單單這套銀行服務套件就包含了數百個嵌入式人工智慧代理，所有這些代理商都無需我們的客戶支付額外費用即可使用。

In retail, our AI-enabled solutions span merchandizing, assortment planning, supply chain management, point of sale, commerce, and of course ERP, CX, and HCMs.

在零售領域，我們的人工智慧解決方案涵蓋商品銷售、品類規劃、供應鏈管理、銷售點、商務，當然還有 ERP、CX 和 HCM。

In summary, these are not systems that can be replaced by a small collection of these features cobbled together and bolted on in the name of AI.

總之，這些系統不能被簡單地拼湊起來，打著人工智慧的旗號強加於其上的一小部分功能所取代。

So yes, some smaller or single-focused SaaS players may well be disrupted, but Oracle will not be among them. Now, let me focus on a key -- a few key wins in Q3 in the application space, and by all means, this is a very short list, not an exhaustive list.

所以，一些規模較小或專注於單一領域的 SaaS 企業可能會受到衝擊，但 Oracle 不會是其中之一。現在，讓我專注於一個關鍵點——第三季度在應用領域取得的一些關鍵勝利，當然，這只是一個非常簡短的列表，並非詳盡的列表。

Memorial Hermann Health Systems selected Fusion ERP, SCM, and HCM. This was a win over Workday. The University of New South Wales also selected Fusion ERP and HCM, also a win over Workday.

Memorial Hermann Health Systems 選擇 Fusion ERP、SCM 和 HCM。這是對Workday的一次勝利。新南威爾斯大學也選擇了 Fusion ERP 和 HCM，再次擊敗了 Workday。

Gray Media selected Fusion EPM and ERP, a win again over Workday and also over SAP. Investec Bank selected Fusion EPM and ERP over SAP. HID Global Corporation also selected Fusion ERP and SCM over SAP.

Gray Media 選擇 Fusion EPM 和 ERP，再次擊敗了 Workday 和 SAP。Investec Bank 選擇 Fusion EPM 和 ERP 而不是 SAP。HID Global Corporation 也選擇了 Fusion ERP 和 SCM 而不是 SAP。

Ethiopian Shipping and Logistics Services Enterprises selected Fusion ERP, SCM, and HCM, again, over SAP. A major Wall Street bank elected to standardize on Fusion ERP for the entirety of their business and all of their business units, replacing SAP full stop.

埃塞俄比亞航運物流服務企業再次選擇了 Fusion ERP、SCM 和 HCM，而不是 SAP。華爾街一家大型銀行選擇在所有業務部門和業務系統中全面採用 Fusion ERP 系統，徹底取代 SAP。

Loudoun County Public Schools selected Fusion ERP, EPM, HCM, and SCM. The J.M. Smucker Company selected Fusion ERP and EPM. Westfield Insurance picked Fusion ERP, EPM, HCM, and procurement. Mitsubishi UFG Financial Group is an existing cloud customer and database customer. They're now moving into both our Fusion ERP and industry SaaS applications. [SDC Kuwait], an existing major tech customer, is moving EBS to the cloud to support their growth. So just this very small list of major application wins in the quarters.

勞登縣公立學校選擇了 Fusion ERP、EPM、HCM 和 SCM。J.M. Smucker 公司選擇了 Fusion ERP 和 EPM。Westfield Insurance選擇了Fusion ERP、EPM、HCM和採購系統。三菱日聯金融集團是現有的雲端客戶和資料庫客戶。他們現在正逐步遷移到我們的 Fusion ERP 和產業 SaaS 應用平台。 [SDC Kuwait] 是我們現有的主要技術客戶，他們正在將 EBS 系統遷移到雲端以支援其業務成長。以上僅列舉了本季一些主要的申請成功案例。

In the quarter, we had over 2,000 customers go live in Q3, 2,000 customers when you think about our industry applications and our Fusion applications put together over 2,000 went to live. And more importantly, we continue to see the median time from live decreased a very small sample of go-lives in the quarter. Herst expanded their ERP with EPM as well as HCM. J.M. Huber companies across Fusion ERP and HCM. Emirates Health Services went live with HCM, which enabled a comprehensive HR, payroll, and talent suite to elevate their workforce management.

第三季度，我們有超過 2000 位客戶上線，如果您考慮我們的行業應用程式和 Fusion 應用程序，加起來有超過 2000 位客戶上線。更重要的是，我們持續看到，本季上線的中位數時間有所減少，而這只是本季上線案例中很小的一部分。Herst 將 EPM 和 HCM 整合到其 ERP 系統中。J.M. Huber 公司在 Fusion ERP 和 HCM 方面擁有豐富的經驗。阿聯酋健康服務公司正式啟用 HCM 系統，該系統提供全面的人力資源、薪資和人才管理套件，從而提升了其員工隊伍管理水準。

Niagara bottling that went live on SCM moving from on-premise ERP to Fusion. Seadrill is now live across ERP, HCM, SCM, and EPM. Again, very -- with 2,000 lives in the quarter, that's just a very, very short list of go-lives, but you can see, hopefully, not only momentum but multi-pillar momentum with these customers.

尼亞加拉瓶裝廠已上線 SCM，從本地 ERP 系統遷移到 Fusion 系統。Seadrill現已在ERP、HCM、SCM和EPM系統中上線。再說一遍，非常——本季度只有 2000 個上線案例，這只是非常非常少的上線案例，但希望您能看到，不僅有勢頭，而且這些客戶帶來了多方面的勢頭。

I also have an equally shortlist compared to the overall list of key tech wins in Q3. Lockheed Martin selected OCI high-performance compute to scale AI across their environment efficiently. Rambus selected OCI compute, networking and storage for AI video and security across all of their workloads.

與第三季主要技術成果的總體清單相比，我也有一個同樣簡短的清單。洛克希德馬丁公司選擇 OCI 高效能運算來高效地擴展其環境中的 AI 規模。Rambus 為其所有工作負載中的 AI 視訊和安全性選擇了 OCI 運算、網路和儲存解決方案。

Lucid Motors selected OCI core services for data and connectivity in order to expand into European markets. Infomart in Japan selected OCI for their mission-critical B2B platform. Claro Brazil selected OCI alloy for sovereign AI.

Lucid Motors 選擇 OCI 的數據和連接核心服務，以拓展歐洲市場。日本 Infomart 選擇 OCI 作為其關鍵業務 B2B 平台。Claro Brazil 選擇 OCI 合金用於主權人工智慧。

Air France KLM, which is a multicloud win featuring a win with the Oracle database at Azure, and that led to a 13x performance improvement at a significantly lower cost for Air France KLM and Activision Blizzard, an existing Oracle E-Business Suite was also an Oracle database at Azure win.

法國航空荷航集團 (Air France KLM) 成功部署了多雲系統，其中在 Azure 上使用 Oracle 資料庫取得了成功，這使得法國航空荷航集團的效能提高了 13 倍，而成本卻顯著降低。動視暴雪 (Activision Blizzard) 現有的 Oracle E-Business Suite 也是在 Azure 上使用 Oracle 資料庫的成功案例。

Oracle's embrace of AI across our strategic applications is leading to broader enterprise conversations with our customers involving our full stack, OCI, AI data platform, Fusion applications, industry suites. These conversations are about ecosystem automation. They're not about single apps. They're about automating the entire ecosystem, and they further been able to by our simplified go-to-market model, which we spoke about in our last earnings call. This is allowing us to close more multiproduct deals with more customers combining the power of the Oracle database, our OCI platform, our AI tooling, and our complete application suites.

Oracle 在其策略應用中對人工智慧的全面應用，正促使我們與客戶就我們的全端產品、OCI、人工智慧資料平台、Fusion 應用程式和產業套件等展開更廣泛的企業對話。這些對話是關於生態系統自動化的。它們並非針對單一應用程式。他們的目標是實現整個生態系統的自動化，而且他們也透過我們簡化的市場推廣模式進一步實現了這一目標，我們在上次財報電話會議上談到了這一點。這使我們能夠與更多客戶達成更多多產品交易，將 Oracle 資料庫、我們的 OCI 平台、我們的 AI 工具和我們完整的應用程式套件的強大功能結合起來。

In constant currency, cloud applications deferred revenue was up 14% versus in-quarter cloud applications revenue growth of 11%, which further supports our acceleration thesis.

以固定匯率計算，雲端應用遞延收入成長了 14%，而當季雲端應用收入成長了 11%，這進一步支持了我們的加速成長論點。

With that, Clay, I'll turn it over to you.

克萊，接下來就交給你了。

Thank you, Mike. Okay. So I'm going to talk about two segments of our business: our multicloud database and AI infrastructure. Both are growing extremely quickly. Multicloud database revenue grew 531% year over year. AI infrastructure revenue grew 243% year over year. Both also have demand that exceeds supply and a clear execution plan for Oracle that will rapidly turn that demand into profitable recurring revenue.

謝謝你，麥克。好的。接下來我將談談我們業務的兩個面向：我們的多雲資料庫和人工智慧基礎設施。兩者都在快速增長。多雲資料庫營收年增 531%。AI基礎設施營收年增243%。兩者都存在供不應求的情況，而 Oracle 制定了明確的執行計劃，將迅速將這種需求轉化為盈利的經常性收入。

Oracle database has run on any hardware and operating system for decades. Oracle Database Cloud Services, up until recently, were only available in a single cloud, OCI. We created our multicloud partnerships with first Microsoft, then Google, and finally, Amazon to bring the best database platform to all cloud. Those partnerships unlock an enormous backlog of demand. Our database customers who want to use our database in other clouds.

幾十年來，Oracle資料庫已經可以在任何硬體和作業系統上運行。直到最近，Oracle 資料庫雲端服務還只能在單一雲端平台 OCI 中使用。我們首先與微軟建立了多雲合作關係，然後是谷歌，最後是亞馬遜，目的是將最好的資料庫平台帶到所有雲端平台。這些合作關係釋放了巨大的需求積壓。希望在其他雲端平台上使用我們資料庫的客戶。

This quarter, we achieved an important milestone. We have global region coverage in all of our partner cloud. We now have 33 regions live with Microsoft and 14 live with Google. We delivered significant growth with AWS beginning Q3 with two AWS regions live, exiting Q3 with eight AWS regions live, and we will exit Q4 with 22 AWS regions live.

本季度，我們取得了一項重要的里程碑。我們所有合作夥伴雲端平台均涵蓋全球區域。目前我們有 33 個地區與微軟合作，14 個地區與Google合作。我們在 AWS 方面實現了顯著成長，第三季開始時有兩個 AWS 區域上線，第三季末有八個 AWS 區域上線，第四季末我們將有 22 個 AWS 區域上線。

AI is also accelerating the adoption of our database cloud services. The improvement in model coding fields and agentic capabilities pushes customers to move their most valuable data into our cloud services. They need access to the latest AI features to support vector embeddings and CP server access and advanced security controls. Customers also need their data to be co-located with the agents themselves, and our multicloud database makes that easy. Our multicloud architecture brings the best of Oracle Cloud into our partner regions. This ensures that we will rapidly turn billions of pipelines into highly profitable database service revenue.

人工智慧也在加速我們資料庫雲端服務的普及。模型編碼領域和代理能力的改進促使客戶將他們最有價值的資料遷移到我們的雲端服務。他們需要存取最新的 AI 功能，以支援向量嵌入、CP 伺服器存取和高級安全控制。客戶還需要將他們的資料與代理商的資料放在一起，而我們的多雲資料庫可以輕鬆實現這一點。我們的多雲架構將Oracle雲端的最佳效能帶到了我們合作夥伴的區域。這將確保我們能夠迅速將數十億條管道轉化為高利潤的資料庫服務收入。

Demand for AI infrastructure, both GPU and CPU, continues to exceed supply. This is directly visible in our $553 billion RPO. I want to share a model for how that RPO turns into profitable recurring revenue as well as some operational metrics that are early indicators of our progress.

人工智慧基礎設施（包括GPU和CPU）的需求持續超過供應。這一點在我們5,530億美元的RPO（招募流程外包）中顯而易見。我想分享一個模型，說明 RPO 如何轉化為盈利的經常性收入，以及一些可以早期指示我們進展的營運指標。

AI infrastructure begins with data centers and power generation. Through our partners, we have secured more than 10 gigawatts of power and data center capacity coming online over the next three years. Those infrastructure investments also need funding and greater than 90% of that capacity is fully funded through our partners, with the remainder planned to finish this month.

人工智慧基礎設施始於資料中心和發電系統。透過我們的合作夥伴，我們已確保未來三年內將有超過 10 吉瓦的電力和資料中心容量投入使用。這些基礎設施投資也需要資金，其中 90% 以上的資金已由我們的合作夥伴全額提供，其餘部分則計劃在本月完成。

Once the data center is secured, several things must come together. The data center and on-site power generation has to be constructed. Compute, networking, and storage has to be designed, manufactured, delivered and installed. All the capacity inside the data center also has to be funded.

資料中心安全保障到位後，還需要多面向因素共同作用。需要建造資料中心和現場發電設施。運算、網路和儲存都需要設計、製造、交付和安裝。資料中心內部的所有容量也都需要資金支持。

We continue to innovate across each of these steps. We optimize our data center construction through standardized designs. Our supply chain has improved with more suppliers and deeper relationships. We have tripled our manufacturing sites and increased rack output by 4x all in the last year.

我們持續在這些步驟中進行創新。我們透過標準化設計優化資料中心建置。我們的供應鏈得到了改善，供應商數量增加，合作關係也更加深入。在過去一年裡，我們的生產基地數量增加了兩倍，貨架產量增加了四倍。

We have scaled our installation processes to enable multiple phases of delivery in parallel. Time from rack delivery to revenue has reduced by 60% in the past several months.

我們已擴展了安裝流程，以實現多個階段的並行交付。過去幾個月，從貨架交付到產生收入的時間縮短了 60%。

We also continue to innovate on our business models. On our last earnings call, I shared multiple ideas for how we can incrementally grow our AI infrastructure without Oracle raising more debt or issuing equity. We have signed more than $29 billion of contracts since then, across multiple customers using that new model. A combination of bring your own hardware and upfront customer payments enables us to continue expanding without any negative cash flow from Oracle. Of course, this $29 billion is in addition to other deals we signed this quarter.

我們也在不斷創新我們的商業模式。在上次財報電話會議上，我分享了多個想法，探討如何在不增加 Oracle 債務或發行股票的情況下逐步擴展我們的 AI 基礎設施。自那時以來，我們已與多家採用該新模式的客戶簽訂了超過 290 億美元的合約。自帶硬體和客戶預付款相結合，使我們能夠在不產生來自 Oracle 的任何負現金流的情況下繼續擴張。當然，這290億美元還不包括我們本季簽署的其他協議。

Ultimately, all of this results in capacity delivered to customers and revenue to Oracle. In Q3, we delivered more than 400 megawatts to customers. 90% of that committed capacity was delivered on or ahead of schedule as we've consistently done over several quarters. This is why customers continue to choose Oracle for their infrastructure needs.

最終，這一切都將轉化為向客戶交付的產能和為 Oracle 帶來的收入。第三季度，我們向客戶交付了超過400兆瓦的電力。與過去幾季一樣，我們90%的承諾容量都準時或提前交付。這就是為什麼客戶持續選擇 Oracle 來滿足其基礎架構需求的原因。

Investing in the AI infrastructure is capital-intensive, but our operating model is optimized to ensure profitability. Flexible infrastructure design, high utilization, and rapid handover combined with diversified customers create an incredible business. Increased scale spreads our fixed costs over a larger base, increasing profitability. It's unprecedented to scale a capital-intensive business so quickly while also increasing profitability.

投資人工智慧基礎設施需要大量資金，但我們的營運模式經過優化，可以確保獲利能力。靈活的基礎設施設計、高利用率和快速交接，再加上多元化的客戶群，造就了一項了不起的業務。規模擴大可以將固定成本分攤到更大的基數上，從而提高獲利能力。在如此短的時間內擴大資本密集型業務規模並提高盈利能力，這在以前是前所未有的。

Looking at the AI capacity we delivered in Q3, our gross margin for that remained above our 30% guidance at 32%. Now, combine that with our other segments of OCI, which have much higher margins, like our database services, and you can see why Oracle is growing so quickly and profitably.

從我們第三季交付的人工智慧產能來看，我們的毛利率維持在 32% 以上，高於我們 30% 的預期。現在，再加上我們 OCI 的其他業務部門（例如資料庫服務），這些板塊的利潤率要高得多，您就能明白為什麼 Oracle 能夠如此快速且盈利地增長了。

Our numbers speak for themselves. We are overdelivering on FY26 revenue and earnings, and we are constantly raising our FY27 forecast. This is made possible by Oracle's transition from a predominantly seasonal license business into a highly predictable recurring revenue class business.

我們的數據足以說明一切。我們2026財年的營收和獲利均超額完成，我們正在持續提高2027財年的預測。這得歸功於 Oracle 從季節性的授權業務轉型為高度可預測的經常性收入業務。

Demand for AI and advanced compute will continue to expand broadly across the economy. There will be many successful models, agentic platforms, and businesses that emerge. We support hundreds of the most advanced AI customers today and more continually want to work with us. We build infrastructure that is flexible, fungible, and can support the smallest workloads up to the largest. We continue to offer the latest in accelerators from the most recent NVIDIA AMD options to emerging designs from companies like [Cerebriu and Peloton].

整個經濟領域對人工智慧和先進運算的需求將繼續廣泛增長。將會湧現許多成功的模式、代理商平台和企業。我們目前為數百家最先進的人工智慧客戶提供支持，而且越來越多的客戶希望與我們合作。我們建構的基礎設施靈活、可互換，能夠支援從最小到最大的各種工作負載。我們持續提供最新的加速器產品，從最新的 NVIDIA 和 AMD 產品到其他公司的新興設計，例如[Cerebriu 和 Peloton]。

Altogether, we are confident that the investments we make now in data centers, compute capacity, and customer relationships will only grow more valuable time.

總而言之，我們相信，我們現在對資料中心、運算能力和客戶關係所做的投資，未來只會變得更有價值。

Back to Ken for questions.

把問題交給肯恩。

Thank you, Clay. Regina, if you could please poll the audience for questions.

謝謝你，克萊。雷吉娜，請你向觀眾徵集一些問題。

(Operator Instructions) John DiFucci, Guggenheim.

（操作說明）約翰·迪富奇，古根漢美術館。

Thank you. Wow, a lot going on here. So listen, I'm going to let others ask about the AI infrastructure question. But we've heard Doug talk about a halo effect that the AI infrastructure business is having on the rest of your business.

謝謝。哇，這裡發生了很多事。所以，關於人工智慧基礎設施的問題，我還是讓其他人來問吧。但我們聽道格說過，人工智慧基礎設施業務對其他業務產生了光環效應。

This quarter was strong, and you said that the RPO increase was from large-scale AI contracts. At the same time, we're hearing from the field now that halo effect is actually turning into business.

本季業績強勁，您曾說過 RPO 的成長來自大規模 AI 合約。同時，我們現在從業內人士那裡了解到，光環效應實際上正在轉化為商業價值。

Outside of AI infrastructure, it sounds like the go-lives are steady, but the business activity and especially the pipeline are up materially from more traditional cloud workloads, including dedicated regions, sovereign clouds, even alloy deals we've started hearing about.

除了 AI 基礎設施之外，上線情況似乎很穩定，但業務活動，尤其是專案儲備，相比更傳統的雲端工作負載（包括專用區域、主權雲，甚至是我們已經開始聽說的合金交易）有了顯著增長。

In addition to what Mike started talking about, with the often related apps deals. I realize these types of deals aren't the scale of these AI deals. But can you talk about what seems to be an underlying momentum building in these businesses? Am I right to be thinking of this? And if I could, on a sort of related topic, can you give us any visibility into CapEx for fiscal '27?

除了麥克開始談論的內容之外，還有經常相關的應用程式交易。我意識到這類交易的規模遠不及人工智慧交易。但您能否談談這些企業中似乎正在形成的潛在發展動能？我這樣想對嗎？另外，關於一個相關的話題，您能否透露一下 2027 財年的資本支出狀況？

Okay. Hi, John. This is Mike. I'll take the question. So yes, we absolutely are seeing a halo effect, and let me add a little bit of color on that.

好的。嗨，約翰。這是麥克。我來回答這個問題。所以，是的，我們確實看到了光暈效應，讓我再補充一些細節。

As far as the apps business, the fact that we're training so many models on OCI and so closely provisioned to our applications allows us to embed very high-quality AI services right into our applications, as I said, as features. So not only are we serving these customers, serving the model vendors for training. But we're also embedding a lot of the output, right, into our applications. Of course, we're doing prompt engineering and things like that to make it relevant to the business.

至於應用業務，正如我所說，由於我們在 OCI 上訓練了大量模型，並且這些模型與我們的應用緊密結合，因此我們可以將非常高品質的 AI 服務直接嵌入到我們的應用中，作為功能。因此，我們不僅為這些客戶提供服務，也為這些模型供應商提供培訓服務。但是，我們也把很多輸出結果嵌入到我們的應用程式中，對吧。當然，我們正在進行快速的工程改進等等，以使其與業務相關。

But the fact that that we are the custodian in our applications business of so much of the world's mission-critical data. We have very close provisioning, very close proximity to these models. Putting those two things together allows customers to get value from AI very, very quickly.

但事實上，在我們的應用程式業務中，我們是全球眾多關鍵任務資料的保管者。我們與這些模型有著非常緊密的聯繫和密切的合作。將這兩者結合起來，可以讓客戶非常非常快速地從人工智慧中獲得價值。

And if you've heard any criticism with AI and well, I can't get value quick enough. Well, actually, when you bundle up as a service and expose private data to AI that we are the custodian of the applications that we've seen terrific wins. I mentioned some of the verticals you heard about there, but I think that's true across the board.

如果你聽過任何關於人工智慧的批評，而且嗯，我無法快速獲得價值。實際上，當你將資料打包成服務並將私人資料暴露給人工智慧時，作為應用程式的管理者，我們已經看到了巨大的成功。我剛才提到了一些你聽說過的垂直領域，但我認為這在各個方面都是如此。

The other piece that is a very interesting halo effect is leveraging our infrastructure, just OCI, infrastructure as a budget creator for customers. You've heard us say it before, we're faster and cheaper than everybody else. And when customers are thinking about these large-scale application or large-scale infrastructure transformations, we can also help them get to a position of a budget creation to be able to fund that transformation simply by moving their workloads to OCI because we can run them more quickly and more efficiently and less expensively than our competitors.

另一個非常有趣的連鎖反應是利用我們的基礎設施，也就是 OCI，作為客戶的預算創造者。您之前也聽我們說過，我們比其他任何人都更快、更便宜。當客戶考慮大規模應用程式或大規模基礎設施轉型時，我們還可以幫助他們制定預算，透過將工作負載遷移到 OCI 來為轉型提供資金，因為我們可以比競爭對手更快、更有效率、更經濟地運行這些工作負載。

And then finally, the other halo effect before I turn it over to Doug, for your question on CapEx is around sovereign AI. Our sovereign story is not new and it's not a knee jerk reaction to the things that are happening in the world. Combine other with our alloy story, we're really seeing increasing pipeline across the world.

最後，在我把問題交給 Doug 之前，還有另一個關於資本支出的光環效應的問題，這個問題與主權人工智慧有關。我們的主權故事並非新鮮事，也不是對世界正在發生的事情的倉促反應。結合其他因素和我們的合金故事，我們確實看到世界各地的管道運輸量都在增加。

The fact that our form factor, and we're so differentiated in our form factor, and we can deliver not just the smaller form factor, but complete OCI services on top of that form factor no matter how many racks are involved, whether it's 3 racks or 500 racks, we think that's a huge differentiator in the market. So you put you put apps together, you put OCI AI services together, you put sovereignty together. And yes, it's a pretty big halo effect.

我們的外形尺寸非常獨特，而且我們不僅能夠提供更小的外形尺寸，還能在此基礎上提供完整的 OCI 服務，無論涉及多少機架，無論是 3 個機架還是 500 個機架，我們認為這在市場上是一個巨大的差異化優勢。所以，你把應用程式組合在一起，把 OCI AI 服務組合在一起，把主權組合在一起。沒錯，這確實會產生相當大的光環效應。

Yeah. And John, just let we start by acknowledging the creativity in getting two questions at the same time, it's always fascinating to watch.

是的。約翰，首先讓我們讚揚一下你同時提出兩個問題的創造力，這總是令人著迷的。

So on CapEx, I think we'll get back to everyone next -- after the end of the fiscal year and talk about next year's CapEx at that point in time. But I will say a couple of things.

關於資本支出，我想我們會在財政年度結束後再和大家討論明年的資本支出。但我還是要說幾句。

Obviously, from what Clay has gone through, the most interesting thing that you just start thinking about is the uncoupling of CapEx with capital requirements from Oracle. Obviously, when we have these additional funding mechanisms, there may be additional CapEx, but it doesn't require out-of-pocket cash from Oracle, which is quite interesting.

顯然，從 Clay 的經驗來看，最有趣的事情莫過於 Oracle 的資本支出與資本需求脫鉤。顯然，有了這些額外的融資機制，可能會增加資本支出，但甲骨文公司不需要自掏腰包，這很有趣。

So underlying that, as we remain committed to what we talked about last quarter, which is maintaining the investment-grade rating at Oracle as well as staying within the financing envelope that we talked about, obviously, of which we've announced that we're doing $50 billion this calendar year of that total.

因此，在此基礎上，我們仍然致力於上個季度我們談到的內容，即維持 Oracle 的投資等級評級，並保持在我們談到的融資範圍內，顯然，我們已經宣布，我們將在今年完成 500 億美元的融資。

So more to come, John, on the CapEx after next quarter.

約翰，下個季度之後還會有更多關於資本支出方面的資訊。

Very much appreciate the color on that, Doug. And Mike, your prepared remarks on AI and how Oracle approaches it, everybody should use that because it's a logical approach. So thanks, guys, and nice job.

道格，我非常喜歡這幅畫的顏色。麥克，你事先準備好的關於人工智慧以及Oracle如何應對人工智慧的發言，大家都應該借鑒，因為這是一種合乎邏輯的方法。謝謝各位，幹得漂亮！

Mark Murphy, JPMorgan.

馬克墨菲，摩根大通。

Thank you. Congrats on the acceleration, Clay. As Oracle transitions to higher levels of AI inferencing, what do you view as the right strategy for trying to optimize the location of your data centers.

謝謝。恭喜你取得加速成績，克萊。隨著 Oracle 向更高層次的 AI 推理過渡，您認為優化資料中心位置的正確策略是什麼？

For instance, you have these huge centralized data centers in Texas and Wyoming, they're very close to power, but they're pretty far from the population centers and the fiber routes that are out there on the seaboard.

例如，德州和懷俄明州有龐大的集中式資料中心，它們離電力供應很近，但距離人口中心和沿海地區的光纖線路卻相當遠。

So it crosses our minds that the users and the devices are a long distance away. So as you make us move more into inferencing, are you seeing any reason to try to pivot those locations a little closer to where the users and the traffic are.

因此，我們不禁想到，使用者和裝置之間可能存在很遠的距離。所以，隨著你們讓我們更多地轉向推理，你們認為有什麼理由嘗試將這些位置稍微調整得更靠近用戶和流量所在的地方嗎？

Sure. This is Clay. Great question, Mark. So let me start by, I think, highlighting our perspective on inferencing and how that impacts kind of data center deployment.

當然。這是克萊。問得好，馬克。那麼，我想先強調我們對推理的看法，以及推理如何影響資料中心的部署。

So first thing, I would say, is I think we are -- for a while, there's a lot of training going on. Inferencing is very rapidly growing, everywhere and anywhere. I think it's because of higher and higher utilization of the models themselves and also new use cases.

所以首先我想說的是，我認為我們——在一段時間內，會有很多訓練進行。推理技術正在迅速發展，遍及世界各地。我認為這是因為模型本身的利用率越來越高，以及出現了新的應用場景。

As anyone who's been using Claude or Codex recently in the software space nodes, these are incredible tools that are changing how we do everything. So inferencing is going to have a huge amount of demand.

對於最近在軟體領域節點中使用過 Claude 或 Codex 的人來說，這些都是非常棒的工具，它們正在改變我們做事的方式。因此，推理技術將會有巨大的需求。

Now, when you talk about data center location, you mentioned latency is the one. Realistically, there are several reasons you might care about the location. It might be the cost, it might be just overall availability, it might be for sovereignty. So there's different reasons to pick a location.

現在，說到資料中心位置，你提到延遲是其中一個因素。實際上，你可能出於多種原因而關心地理位置。可能是成本問題，可能是整體可用性問題，也可能是主權問題。所以選擇某個地點的原因有很多。

But honing in on your point about latency, the thing, I think, to understand is that latency is all proportional, meaning, if what you're trying to do is you're trying to do a very, very low legacy trade on the stock market, waiting for the 100-millisecond round trip from coast to coast is a bad idea.

但回到你提到的延遲問題，我認為需要理解的是，延遲是成比例的，也就是說，如果你想在股票市場上進行一筆非常非常低的傳統交易，等待從東海岸到西海岸的 100 毫秒往返時間是一個糟糕的想法。

If what you're doing is you're asking a question for your business, it's going to take an AI model several seconds to think about an extra 40 milliseconds of latency from New York to Wyoming is not going to hurt you.

如果你正在為你的業務提出問題，那麼人工智慧模型需要幾秒鐘的時間來思考，從紐約到懷俄明州額外的 40 毫秒延遲不會對你造成任何影響。

And so when you actually talk to customers about use cases where they need lower latency, the latency problem right now is not actually the location of the hardware. It's the type of hardware that's being deployed. And that's why you're seeing so much innovation going on around these AI accelerators. If you look at what the Groq Rock does or Cerebras or Positron, all of these different types of customers are saying, well, not only how do we reduce the cost of inferencing, but also how can we significantly reduce the latency of it.

因此，當你真正與客戶討論他們需要更低延遲的使用場景時，目前的延遲問題實際上並不是硬體的位置。這是正在部署的硬體類型。這就是為什麼你會看到圍繞這些人工智慧加速器湧現出如此多的創新。如果你看看 Groq Rock、Cerebras 或 Positron 的產品，你會發現所有這些不同類型的客戶都在問，我們不僅要如何降低推理成本，還要如何大幅降低推理延遲。

I think if you look forward to GTC from NVIDIA next week, you'll see announcements from them. But across the board, I think the way that an industry we're going to consolidate and kind of reduce latency has to first start with a different architecture for that inferencing.

我認為，如果你有在關注下周英偉達舉辦的GTC大會，你會看到他們發布的一些公告。但總的來說，我認為我們想要整合整個產業並降低延遲的方式，首先必須從不同的推理架構開始。

And thankfully, the data center location is actually a very tiny part of that. So it makes much more flexible for us to go out and put the data centers where power is abundant, land is plentiful, and we can actually optimize for what's available to meet this ever-increasing demand.

值得慶幸的是，資料中心的位置實際上只佔其中很小的一部分。因此，我們可以更靈活地選擇電力充足、土地豐富的地區建設資料中心，並根據現有資源進行最佳化，以滿足不斷增長的需求。

Thank you very much.

非常感謝。

Siti Panigrahi, Mizuho.

Siti Panigrahi，瑞穗銀行。

Great. Thanks for taking my question. I want to ask about the opportunity with your AI database and the AI data platform. So with recent excitement on AI and on enterprises now adopting tools from Frontier LLMs. So what are you hearing from customers about training their private data and building their private LLMs? And how confident are you in seeing the inflection in your AI database growth that you talked about at the Analyst Day in October?

偉大的。謝謝您回答我的問題。我想諮詢貴公司的人工智慧資料庫和人工智慧資料平台的相關合作機會。因此，隨著近期人工智慧領域的熱潮以及企業開始採用 Frontier LLMs 的工具，那麼，您從客戶那裡了解到哪些關於訓練他們的私有資料和建立他們的私有LLM的資訊？您在 10 月的分析師日上提到的 AI 資料庫成長拐點，您對此有多大信心？

Thanks. This is Clay. So look, I think there are two parts to that question. One is, how much adoption are we seeing a kind of private LLMs and then how much are we seeing of using AI with private data.

謝謝。這是克萊。所以你看，我認為這個問題包含兩個部分。一是我們看到私有LLM的採用程度如何，二是我們看到AI與私有資料結合使用的程度如何。

I think in the early days, a lot of people thought that most customers will be doing very specific training of their own large language model. I think that has largely proven to not be the case. Instead, what I think is incredibly popular growing in popularity is people taking the best models and wanting them to combine that in a private way with their private data, and we're seeing a lot of demand for that.

我認為在早期，很多人都認為大多數客戶會對自己的大型語言模型進行非常具體的訓練。我認為，事實在很大程度上並非如此。相反，我認為越來越受歡迎的是，人們希望將最好的模型以私密的方式與他們的私人數據結合起來，我們看到這方面的需求很大。

If you listen to Mike earlier talk about how we're embedding these AI models into our applications, that's one use case. But obviously, not everything, unfortunately, runs inside of an Oracle application and lots of customer applications are written. So we added a lot of functionality to our Oracle AI database, make it easy to connect whether it be through the MCP servers or natural language to SQL that you can use these models to use.

如果你聽過 Mike 之前談到我們如何將這些 AI 模型嵌入到我們的應用程式中，那就是一個用例。但很顯然，不幸的是，並非所有程式都能在 Oracle 應用程式中運行，而且許多應用程式都是由客戶編寫的。因此，我們為 Oracle AI 資料庫添加了許多功能，使其更容易連接，無論是透過 MCP 伺服器還是自然語言到 SQL，您都可以使用這些模型。

But also, we have our AI data platform product, which is really about solving this exact problem. You have a lot of data, maybe application data, it may be custom data and different data lakes and lake houses and may be data in a structured database. All that together gives you an agentic platform to quickly build applications on as well as access to all of the greatest models from multiple providers.

此外，我們還有人工智慧資料平台產品，它正是為了解決這個問題而開發的。您有很多數據，可能是應用程式數據，也可能是自訂資料、不同的資料湖和資料倉儲，也可能是結構化資料庫中的資料。所有這些加起來為您提供了一個代理平台，您可以在其上快速建立應用程序，並可以訪問來自多個提供者的所有最佳模型。

So across the stack, we're seeing a lot of momentum across that. And that's why in my prepared remarks, I talked about the growth that we're seeing with our multicloud database.

因此，從整體來看，我們看到了許多上漲勢頭。所以，在我的發言稿中，我談到了我們在多雲資料庫方面所看到的成長。

What we see is that for customers to take advantage of the latest and greatest AI, they first have to be in the cloud, and there's still a lot of data that's not in the cloud. And so we see acceleration of moving that most important private data to a cloud environment, so they can then take advantage of the latest and greatest AI with that data.

我們看到，客戶要利用最新、最強大的 AI 技術，首先必須使用雲端服務，但目前仍有許多資料不在雲端。因此，我們看到企業加速將最重要的私有資料遷移到雲端環境，以便利用最新的人工智慧技術處理這些資料。

Great. Thanks for the color.

偉大的。謝謝你提供的色彩。

Mark Moerdler, Sanford Bernstein.

馬克‧莫德勒，桑福德‧伯恩斯坦。

Thank you very much for taking my question, and congratulations on what's a really good quarter, really great work. I'm going to change over a little bit and discuss on the financial side a little bit. Now that you've completed your major debt raise, can you explain, given the blend of the cost of the -- building out the AI data center and the cost of raising capital to fund the AI data center, how comfortable are you with the values you're creating from the AI data center business itself?

非常感謝您回答我的問題，也祝賀您度過了一個非常棒的季度，工作做得非常出色。我打算稍微轉換一下話題，談談財務上的事情。既然你們已經完成了主要的債務融資，考慮到建造人工智慧資料中心的成本以及為人工智慧資料中心籌集資金的成本，你們對人工智慧資料中心業務本身所創造的價值有多大信心？

And then as an adjacency, if you don't mind, can you talk a little bit more on the sovereign cloud? Can you discuss how you parlay the AI data center business into being the AI provider for sovereign clouds? And how that should impact your -- the value of -- to Oracle? Thanks.

另外，如果不介意的話，能否再多談談主權雲？您能否談談您如何將人工智慧資料中心業務轉型為主權雲端的人工智慧提供者？那這對你──對Oracle的價值──又會產生怎樣的影響呢？謝謝。

Sure. I think we're going to split this one up, Mark. This is Clay. I'll take the first half, and then I'm going to throw it to Mike to talk about some of the sovereign cloud stuff.

當然。馬克，我覺得我們要把這件事分成兩個部分來做。這是克萊。我先講前半部分，然後交給麥克，讓他談談主權雲方面的一些內容。

So look, when you think about the overall profitability of these AI data centers, there's two pieces. One is how profitable is it purely on the accelerator themselves. We made guidance in the past that we see gross margin in the 30% to 40% range on that, that continues to hold for us.

所以你看，當你考慮這些人工智慧資料中心的整體獲利能力時，你會發現有兩個面向。一是單憑加速器本身能帶來多少利潤。我們過去曾預測毛利率將在 30% 至 40% 之間，這項預測目前仍然有效。

And as we continue to get better and better at running these data centers, delivering them more cheaply, optimizing the amount of cost of -- for networking and hardware spend as well as power, we see that continuing to incrementally improve. So we're very pleased with that.

隨著我們在營運這些資料中心方面不斷進步，以更低的成本交付它們，優化網路和硬體支出以及電力成本，我們看到這種情況會繼續逐步改善。我們對此非常滿意。

The other thing to understand is that in these AI data centers, whether it be for inferencing or for training workloads, only thing being procured is not AI accelerators. There's a lot of general purpose compute. There's a lot of whether it be high performance or large-scale blob storage, there's load balancing, there's identity security products, et cetera, et cetera.

另一點要了解的是，在這些人工智慧資料中心中，無論是用於推理還是用於訓練工作負載，所購買的並非只有人工智慧加速器。有很多通用運算資源。無論是高效能還是大規模資料塊存儲，還有負載平衡、身分安全產品等等，都有很多相關產品。

That typically on the order of 10% to 20% of the total spend is going to adjacent services. And when you factor that in, which have higher margins being on the mix of services, the overall profitability continues to improve. And that's without taking into account, as I mentioned earlier, about our multicloud database business, that's a much higher margin business, more in the 60% to 80% range. It's growing very, very rapidly.

通常情況下，總支出的 10% 到 20% 會用於相關服務。考慮到服務類產品利潤率較高，整體獲利能力持續提高。而且，正如我之前提到的，這還沒有考慮到我們的多雲資料庫業務，這是一個利潤率更高的業務，利潤率在 60% 到 80% 之間。它的成長速度非常非常快。

And so when you combine all of these pieces together, the overall margin profile of OCI continues to strengthen and rose rapidly. I mean, the thing I would say, the question that I think underlies this that maybe people don't understand is the limitation on the profitability is not on the capacity we delivered.

因此，綜合所有這些因素來看，OCI 的整體利潤率狀況持續增強並迅速上升。我的意思是，我想說的是，我認為這個問題背後的原因，也許人們並不理解，那就是獲利能力的限制並不在於我們交付的產能。

So let's say that I'm building a data center and has four data halls. And I deliver the first data hall that one is profitable. The reason that we're not even more profitable right now, despite the fact that we are continuing to grow EPS, et cetera, is because we have so much under construction at one time, and we have some expenses for those things.

假設我正在建造一個資料中心，有四個資料機房。我交付了第一個獲利的數據大廳。儘管我們每股收益等指標持續成長，但我們目前獲利能力並未進一步提高，原因是我們同時在進行許多建設項目，而這些項目需要一定的費用。

Now, we're really good at that. We're very, very good at minimizing the time under which that construction is happening. We're very, very good at reducing those costs during that time period, but they're not zero.

現在，我們真的很擅長這件事。我們非常非常擅長最大限度地縮短施工時間。我們非常非常擅長在這段期間降低這些成本，但這些成本並非為零。

And so as our business is going through this hyper-growth phase, that's the only drag on profitability. But thankfully, we're getting -- we're very good and getting better at delivering that capacity that capacity when we deliver it is all already contracted for at a very profitable rate.

因此，在我們業務經歷高速成長階段之際，這是唯一拖累獲利能力的因素。但值得慶幸的是，我們——我們在這方面做得非常好，而且越來越好——我們交付的產能都是已經以非常有利可圖的價格簽訂了合約的。

So when you combine those things together, we're extremely confident in both the capacity we delivered and the continuing to increase profitability of our AI business.

因此，綜合以上因素，我們對我們所交付的能力以及人工智慧業務持續成長的獲利能力都充滿信心。

Mike, do you want to talk about sovereignty?

麥克，你想談談主權問題嗎？

Yes. So sovereignty, as I mentioned earlier, I think we're very well-positioned. A year ago, sovereignty was about data sovereignty. And there were some faux solutions in the market where there was sovereign data from a primary perspective, but DR and maybe somewhere else, maybe in another country. Of course, that's no longer acceptable. Sovereignty is about sovereign data, sovereign operations, and even sovereign contracting.

是的。所以，就主權而言，正如我之前提到的，我認為我們處於非常有利的地位。一年前，主權指的是資料主權。市場上有一些虛假的解決方案，從根本上說擁有主權數據，但實際數據可能來自其他地方，例如另一個國家。當然，這種情況現在已經不能接受了。主權關乎主權資料、主權行動，甚至主權合約。

Our alloy model is perfectly positioned to deliver on all three of those things. And by delivering full stack solutions, again, the big difference between what we're doing with sovereignty and what some of our competitors are doing, we're not simply putting an edge sovereign zone in. We're putting full stack OCI, which had all of our OCI services, and, as you mentioned, margin mix also allows us to run all of our application suite, our AI data platform in that software zone as well. Of course, the margins on some of those are different than our infrastructure margins.

我們的合金模型完美契合這三點需求。透過提供全端解決方案，我們與一些競爭對手在主權領域所做的工作之間的最大區別在於，我們不僅僅是建立一個邊緣主權區。我們正在部署全端 OCI，其中包含了我們所有的 OCI 服務，而且，正如您所提到的，利潤組合也允許我們在該軟體區域運行我們所有的應用程式套件和 AI 資料平台。當然，其中一些項目的利潤率與我們的基礎設施利潤率不同。

So I think that we're in a very unique position to deliver all that we have at Oracle in a sovereign zone. That sovereign zone can be as small or as large as the customer wants it to be.

所以我認為，我們擁有非常獨特的優勢，可以在一個主權區域內交付我們在 Oracle 的所有產品和服務。此主權區域的大小可依顧客的需求而定，可大可小。

The other piece is that we have full flexibility as to where we draw the line of sovereignty. We often think about sovereignty in terms of lines of customers, but we also have customers we've been talking with enterprise customers who may operate across multiple countries, let's say, in Europe or in Africa, that actually want to have a sovereign zone, a sovereign zone that they control and they operate in their data center, and they're serving customers in a certain vertical industry like healthcare, for example, or retail, for example, and their sovereign zone is drawn in their alloy across those countries. We can accommodate all of that.

另一方面，我們在劃定主權界線方面擁有完全的彈性。我們通常從客戶線的角度來考慮主權，但我們也與一些企業客戶進行過交流，這些客戶可能在多個國家/地區運營，例如歐洲或非洲，他們實際上希望擁有一個主權區域，一個由他們控制並在其數據中心運營的主權區域，他們為特定垂直行業的客戶提供服務，例如醫療保健或零售業，他們的主權區域就是在這些國家/地區用他們的合金的地區。我們可以滿足所有這些要求。

We have the most flexibility. We think we have the most flexibility in contract and most flexibility in delivering. And again, the most important thing is that we deliver all that Oracle has in these sovereign zones. It's not a subset. It's not a few edge devices. It's all of OCI.

我們擁有最大的靈活性。我們認為我們在合約方面和交付方面都擁有最大的靈活性。再次強調，最重要的是我們要交付 Oracle 在這些主權區域中擁有的所有功能。它不是一個子集。這並非少數邊緣設備。這就是 OCI 的全部內容。

Extremely helpful, both the answers. Much appreciated, and congrats again.

兩個答案都非常有幫助。非常感謝，再次恭喜！

Raimo Lenschow, Barclays.

雷莫·倫肖，巴克萊銀行。

Perfect. Thank you, congrats for me as well. I wanted to ask something that we are struggling a lot with when we talk to investors, and that's kind of the theme of SaaS, software application software is dead because AI is going to kill it. Just wanted to hear what you guys are hearing when you talk with customers? Is that like some one of these investor things? Is that getting discussed on the customer side as well, and how do you explain it? And I'm just thinking about like what do you guys do with a lot of deterministic rather than probabilistic. So that might probably be the explanation here. But just wanted to hear your perspective again. Thank you.

完美的。謝謝，也恭喜我。我想問一個我們在與投資者交談時經常遇到的問題，這可以說是 SaaS 的主題，軟體應用軟體已死，因為人工智慧將終結它。只是想聽聽你們在與客戶交談時都聽到了什麼？那是不是類似某種投資人活動？客戶方面也有人討論過這個問題嗎？如果有，您是如何解釋的？我只是在想，你們如何處理大量確定性問題而不是機率性問題。所以這很可能就是原因所在。不過還是想再聽聽你的看法。謝謝。

Yeah. So this is Mike. I'll take the question. So as far as the customers that I spoke with, I've not yet met a customer who tells me they're ready to give away their retail merchandising system, their core banking system, demand deposit account systems, electronic health record systems, and some small cobbling together of niche AI features are going to replace all of that over and overnight. In fact, I hear quite the opposite from the customers.

是的。這位是麥克。我來回答這個問題。就我接觸過的客戶而言，我還沒有遇到哪個客戶告訴我，他們準備放棄零售商品系統、核心銀行系統、活期存款帳戶系統、電子健康記錄系統，轉而使用一些零散的、小眾的 AI 功能，一夜之間就能取代所有這些系統。事實上，我從顧客那裡聽到的卻是截然相反的回饋。

What they're asking us is how can we get -- how can we consume as much AI out of the box you're putting into your applications across the board? And how can we get that up and live as quickly as we possibly can because we think that's the best way to actually realize value.

他們問我們的是，我們如何才能——如何盡可能地利用你們在所有應用程式中提供的開箱即用的 AI 技術？我們如何盡快實現目標並過上理想的生活呢？因為我們認為這是真正實現價值的最佳途徑。

But these systems -- what we're running at Oracle, as you know, these are highly complex mission-critical systems with -- we have decades of industry experience, decades of regulatory compliance. And these are the systems that run -- that our customers use to run their business, run their government agency, run their healthcare organization, whatever the case is.

但是，如您所知，我們在 Oracle 運行的這些系統是高度複雜的關鍵任務系統，我們擁有數十年的行業經驗和數十年的監管合規經驗。而這些系統正是我們的客戶用來經營他們的業務、政府機構、醫療保健組織等等的系統。

I really like our position here. As I said, we're leaning very heavily into AI ourselves. So we have 1,000 AI agents already live in Fusion. Our banking alone has hundreds of AI agents just inside our banking solutions.

我非常喜歡我們現在的處境。正如我所說，我們自己也在大力發展人工智慧。目前，Fusion 系統中已有 1000 個 AI 代理程式在運作。光是我們的銀行業務，其銀行解決方案中就包含了數百個人工智慧代理商。

So yes, we think AI is disruptive. We do, but we think we're the disruptor because we're actually embedding the AI right into our applications full stop, again, at no additional. These are features that come in in the application suite as part of quarterly upgrades as part of a regular cadence.

所以，是的，我們認為人工智慧具有顛覆性。沒錯，但我們認為我們才是顛覆者，因為我們實際上是將人工智慧直接嵌入到我們的應用程式中，而且不收取任何額外費用。這些功能作為季度升級的一部分，按照常規節奏添加到應用程式套件中。

So I'm actually -- instead of being -- think that AI spells the death of SaaS, at least for Oracle, I think it actually helps our SaaS position and helps us get to market even more quickly. We're thrilled with the results that we have and expect to have a lot more color on this as we go forward.

所以，我其實不認為人工智慧會終結 SaaS，至少對 Oracle 來說是這樣。我認為它實際上有助於我們在 SaaS 領域中佔有一席之地，並幫助我們更快地進入市場。我們對目前所取得的成果感到非常滿意，並期待未來能有更多精彩的內容呈現。

Okay, thank you.

好的，謝謝。

Brad Zelnick, Deutsche Bank.

布拉德‧澤爾尼克，德意志銀行。

Great, thank you very much, and I'll echo my congrats and also just say that the messaging is very, very clear and very helpful.

太好了，非常感謝！我也要表示祝賀，要說的是，訊息傳遞得非常清晰，非常有幫助。

My question is for Mike and perhaps Larry, and it extends on what Raimo has asked. You've introduced AI agent studio inside of Fusion, and we all know that the crown jewels within an enterprise live inside of Oracle Database and Oracle apps. But I'm curious, how do you see Oracle's role evolving in a world where many other players are vying to be the AI interaction layer across multiple different enterprise systems and workflows?

我的問題想問麥克，或許也想問拉里，這個問題是對雷莫提出的問題的一種補充。你們在 Fusion 中引進了 AI 代理工作室，我們都知道，企業的核心價值在於 Oracle 資料庫和 Oracle 應用。但我很好奇，在許多其他廠商都在爭奪跨多個不同企業系統和工作流程的 AI 互動層的市場地位的今天，您認為 Oracle 的角色將如何演變？

So Brad, it's Mike. So I'll start. So look, I think data gravity matters here. And I think mission-critical data gravity matters even more. So as we said, we've announced the AI agent Studio inside of Fusion.

布萊德，我是麥克。那我先來。所以你看，我認為數據引力在這裡很重要。而且我認為，對於關鍵任務數據而言，引力更為重要。正如我們所說，我們已經在 Fusion 中推出了 AI 代理 Studio。

Fusion is a system inside our customers that is the custodian of their operational data, their mission-critical data. So if you're going to build a bunch of AI agents as or your system integrator is going to build a bunch of AI agents. The question I would have is where we'd just start. Well, you can start inside the system of record, you'd start inside the system of gravity because that is the data from an inferencing standpoint, from a retrieval augmented generation standpoint is going to be highly relevant and highly specific and add a bunch of context to AI.

Fusion 是我們客戶內部的一個系統，負責保管他們的營運資料和關鍵任務資料。所以，如果你要建立一大批人工智慧代理，或者你的系統整合商要建立一大批人工智慧代理。我想問的是，我們該從哪裡開始呢？你可以從記錄系統內部開始，從重力系統內部開始，因為從推理的角度來看，從檢索增強生成的角度來看，那裡的數據將具有高度相關性和高度特異性，並為人工智慧添加大量上下文。

Now, the AI agent studio that we've released in Fusion is not just specific -- it's not specific to just Fusion data. You can build AI agents across our industry applications, across third-party applications, third parties can build AI agents in there.

現在，我們在 Fusion 中發布的 AI 代理工作室並非僅限於 Fusion 資料。您可以在我們的行業應用程式和第三方應用程式中建立 AI 代理，第三方也可以在其中建立 AI 代理。

So the fact that we're delivering an all-in-one best up solution, a full-scale SaaS application, AI powered SaaS applications and giving you the ability to create your own AI agents either on top of that or next to that in a standard upgraded, quarterly platform release schedule, I think, is going to be quite attractive because this AI agent studio that we built at Fusion, it's part of our quarterly upgrades.

因此，我們提供一體化的最佳解決方案、全面的 SaaS 應用程式、AI 驅動的 SaaS 應用程序，並允許您在此基礎上或旁邊創建自己的 AI 代理，而且我們採用標準的季度升級平台發布計劃，我認為這將非常有吸引力，因為我們在 Fusion 構建的這個 AI 代理工作室是我們季度升級的一部分。

It's part of our quarterly regular security patching. So you're getting the best we think of both worlds. You're getting packet SaaS applications. You're getting an agent studio, which is very, very close to the most mission-critical germane data that enterprise possesses and you're getting the ability to create your own custom bespoke agents if you'd like to as well.

這是我們每季例行安全修補更新的一部分。所以，您將享受到我們認為兩方面最好的結合。您獲得的是資料包SaaS應用程式。您將獲得一個代理工作室，它與企業擁有的最關鍵、最相關的數據非常接近，而且如果您願意，您還可以創建自己的定制代理。

Yeah. I'll just end with, we provide a bunch of prebuilt agents for all of our applications. But in addition, we provide a development environment, the AI data platforms development environment that allow our customers to easily add their own agents to what we build. We don't think we can build all the application agents for a banking system or all the application agents for a healthcare system. A lot of our partners are going to do that. A lot of our customers are going to do that.

是的。最後我想說的是，我們為所有應用程式提供了一系列預先建置的代理程式。此外，我們還提供了一個開發環境，即 AI 數據平台開發環境，使我們的客戶能夠輕鬆地將自己的代理商添加到我們構建的系統中。我們認為我們不可能為銀行系統建立所有應用程式代理，也不可能為醫療保健系統建立所有應用程式代理。我們的許多合作夥伴都會這樣做。我們的許多客戶都會這樣做。

What the AI data platform does is it provides a complete integrated development environment where you can build your own agents using any AI model that is in the Oracle Cloud and that is basically all of the popular AI models.

AI 資料平台的作用是提供一個完整的整合開發環境，您可以在其中使用 Oracle 雲端中的任何 AI 模型來建立自己的代理，而這基本上涵蓋了所有流行的 AI 模型。

You can use it for coding the agent, you can use it -- you do multistep reasoning for queries, we plan in our Fusion accounting system, for example. We will have a complex agent that does something called the close. So when you close your books with Fusion in the not-too-distant future, it will be an autonomous agent, no human beings involved. You will close your books by simply telling the AI agent to go ahead and close the books, and then you will get your results.

你可以用它來寫代理程式碼，你可以用它來進行多步驟查詢推理，例如，我們在 Fusion 會計系統中進行規劃。我們將有一個複雜的代理，它會執行一種稱為「關閉」的操作。因此，在不久的將來，當你與 Fusion 結束合作時，它將是一個自主代理，不再有人類參與。你只需告訴人工智慧代理人關閉帳簿，即可完成帳簿結算，然後你將獲得結果。

We provide a lot of AI capability built into our applications, but they are open. They are open that allow our customers and our partners to add to that portfolio of agents and we built an entire ecosystem that automates healthcare, automate financial services, automates retail. That is what AI is allowing us to do is to expand our horizons for the scope of the suites of a SaaS software building to automate entire ecosystems.

我們的應用程式內建了許多人工智慧功能，但它們都是開放的。它們開放，允許我們的客戶和合作夥伴增加代理商組合，我們建立了一個完整的生態系統，實現了醫療保健自動化、金融服務自動化和零售自動化。這就是人工智慧讓我們能夠做的：擴展 SaaS 軟體套件的範圍，從而實現整個生態系統的自動化。

Let me talk about healthcare. In healthcare, Epic automates hospitals, acute care hospitals, and in some cases, clinics, but primarily acute care hospitals. We automate acute care hospitals. We automate clinics. We automate laboratories. We automate the payers, the people who actually pay. We automate the insurance companies. We automate the HCM system that trains their nurses, that schedules to get the right radiologist when an MRI is given, that automates the hospital's financials, but also automates the FDA and that approves the latest drugs that deals with the pharmaceutical companies.

讓我來談談醫療保健。在醫療保健領域，Epic 為醫院、急診醫院以及在某些情況下為診所提供自動化服務，但主要為急診醫院提供自動化服務。我們實現了急診醫院的自動化。我們實現了診所的自動化。我們實現了實驗室自動化。我們實現了支付方的自動化，也就是實際付款的人的自動化。我們實現了保險公司的自動化。我們實現了 HCM 系統的自動化，該系統可以培訓護士，安排合適的放射科醫生進行 MRI 檢查，實現醫院財務的自動化，還可以實現 FDA 的自動化，並批准與製藥公司打交道的最新藥物。

That's the healthcare ecosystem. It's enormous. And thank God, we have these coding tools now that allow us to build a comprehensive set of software, agent-based software to automate a complete ecosystem like healthcare or financial services.

這就是醫療保健生態系統。它非常巨大。感謝上帝，我們現在有了這些編碼工具，使我們能夠建立一套全面的軟體，即基於代理的軟體，來自動化醫療保健或金融服務等完整的生態系統。

That's what we're doing at Oracle. That's why we think we're a disruptor. That's why we think the SaaS apocalypse applies to others but not to us.

這就是我們在甲骨文公司正在做的事情。這就是我們認為自己是顛覆者的原因。這就是為什麼我們認為 SaaS 末日論適用於其他人，但不適用於我們。

Really great stuff. Thank you, Larry. Thanks, Mike, and congrats.

真是好東西。謝謝你，拉里。謝謝你，麥克，也恭喜你。

Thank you, Brad. A telephone replay of the conference call will be available for 24 hours on our Investor Relations website.

謝謝你，布拉德。本次電話會議的錄音回放將在我們投資者關係網站上保留 24 小時。

Thank you for joining us today. And with that, I'll turn the call back to Regina for closing.

感謝您今天蒞臨。就這樣，我把電話轉回給雷吉娜，要她結束通話。

This will conclude today's call. Thank you, all, for joining. You may now disconnect.

今天的電話會議到此結束。謝謝各位的參與。您現在可以斷開連線了。