賽富時 (CRM) 2024 Q1 法說會逐字稿

Welcome to Salesforce Fiscal 2024 First Quarter Results Conference Call. (Operator Instructions) I would like to hand over the conference to your speaker, Mike Spencer, Executive Vice President of Investor Relations. Sir, you may begin.

歡迎參加 Salesforce 2024 財年第一季度業績電話會議。 （操作員說明）我想將會議交給您的發言人，投資者關係執行副總裁 Mike Spencer。先生，您可以開始了。

Good afternoon, and thanks for joining us today on our fiscal 2024 first quarter results conference call. Our press release, SEC filings and a replay of today's call can be found on our website. With me on the call today is Marc Benioff, Chair and CEO; Amy Weaver, President and Chief Financial Officer; and Brian Millham, President and Chief Operating Officer.

下午好，感謝您今天加入我們的 2024 財年第一季度業績電話會議。我們的新聞稿、SEC 文件和今天電話會議的重播可以在我們的網站上找到。今天與我通話的是董事長兼首席執行官馬克·貝尼奧夫 (Marc Benioff)；總裁兼首席財務官 Amy Weaver；總裁兼首席運營官 Brian Millham。

As a reminder, our commentary today will include non-GAAP measures. Reconciliations between our GAAP and non-GAAP results and guidance can be found in our earnings and press release. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions, which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results could differ materially from these forward-looking statements. A description of these risks, uncertainties and assumptions and other factors that could affect our financial results is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and any other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements.

提醒一下，我們今天的評論將包括非 GAAP 措施。我們的 GAAP 和非 GAAP 結果和指導之間的調節可以在我們的收益和新聞稿中找到。我們今天的一些評論可能包含前瞻性陳述，這些陳述受風險、不確定性和假設的影響，這些陳述可能會發生變化。如果這些風險中的任何一個成為現實，或者如果我們的假設被證明是不正確的，公司的實際結果可能與這些前瞻性陳述存在重大差異。對這些風險、不確定性和假設以及可能影響我們財務業績的其他因素的描述包含在我們向美國證券交易委員會提交的文件中，包括我們關於 10-K 表格、10-Q 表格和任何其他向美國證券交易委員會提交的文件的最新報告。除法律要求外，我們不承擔更新這些前瞻性陳述的任何責任。

And with that, let me hand the call to Marc.

就這樣，讓我把電話交給馬克。

Thanks, Mike, and thank you all for being on the call. On our last call in March, we told you about how Salesforce had radically accelerated our transformation to profitable growth. We shared with you how we hit the hyperspace button across the key areas of our transformation: restructuring for the short and long term; reigniting our performance culture by focusing on productivity, operational excellence and profitability; prioritizing our core innovations that drive customer success; building even stronger relationships with you, our investors.

謝謝，邁克，感謝大家接聽電話。在 3 月的最後一次電話會議上，我們向您介紹了 Salesforce 如何從根本上加速我們向盈利增長的轉型。我們與您分享了我們如何在轉型的關鍵領域按下超空間按鈕：短期和長期重組；通過專注於生產力、卓越運營和盈利能力來重新點燃我們的績效文化；優先考慮推動客戶成功的核心創新；與您，我們的投資者建立更牢固的關係。

Our Q1 results show that we continue to make great progress. As I said in March, we're just getting started with this incredible transformation. We continue to scrutinize every dollar of investment, every resource and every spend, and we're transforming every corner of our company.

我們的第一季度業績表明我們繼續取得長足進步。正如我在 3 月份所說，我們才剛剛開始這個令人難以置信的轉變。我們繼續審查每一美元的投資、每一種資源和每一筆支出，我們正在改變我們公司的每一個角落。

Our progress over the last 5 months, well, it's very impressive, and I could not be more grateful to our entire team for their leadership. In fact, you may hear me say that several times on this call.

我們在過去 5 個月裡取得的進步非常令人印象深刻，我非常感謝我們整個團隊的領導。事實上，您可能會在這次電話會議上多次聽到我這樣說。

Our transformation drove our Q1 financial results. As I said on our last call, well, improving profitability is our highest priority. As a result, we significantly exceeded our margin target for the quarter, delivering a non-GAAP operating margin of 27.6%, up 1,000 basis points year-over-year. Incredible. And there is no greater point of evidence to our transformation than this amazing result following the tremendous operating margin in Q4.

我們的轉型推動了我們第一季度的財務業績。正如我在上次電話會議上所說，提高盈利能力是我們的首要任務。因此，我們大大超出了本季度的利潤率目標，實現了 27.6% 的非 GAAP 營業利潤率，同比增長 1,000 個基點。極好的。在第四季度實現巨大的營業利潤率之後，沒有比這個驚人的結果更能證明我們轉型的證據了。

In Q1, we delivered $8.2 billion in revenue, up 11% year-over-year and 13% in constant currency. We had some amazing wins in the quarter with Northwell Health, Paramount, Siemens, Spotify, NASA and the U.S. Department of Agriculture, among others. We delivered $4.5 billion in operating cash flow, up 22% year-over-year. Our remaining performance obligation ended the quarter at $46.7 billion, an increase of 11% year-over-year. And through Q1, we've now returned more than $6 billion in share repurchases. As a result, for the third quarter in a row, we ended the quarter with fewer shares year-over-year, another amazing point of evidence on this incredible transformation.

第一季度，我們實現了 82 億美元的收入，同比增長 11%，按固定匯率計算增長 13%。我們在本季度與 Northwell Health、Paramount、Siemens、Spotify、NASA 和美國農業部等公司取得了一些驚人的勝利。我們交付了 45 億美元的運營現金流，同比增長 22%。我們剩餘的履約義務在本季度結束時為 467 億美元，同比增長 11%。到第一季度，我們已經返還了超過 60 億美元的股票回購。結果，我們連續第三個季度以同比減少的股票結束了本季度，這是這一令人難以置信的轉型的另一個驚人證據。

Now turning to our financial guidance. While the economy is not in our control, our margins are, which is why we're raising our margin target for the full fiscal year. For FY '24, we're raising our non-GAAP operating margin to 28%, an improvement of 550 basis points year-over-year. And we remain confident that we'll hit 30% non-GAAP operating margins in the first quarter of fiscal year '25. We could not be more excited about our progress. We're maintaining our fiscal year '24 revenue guidance of approximately $34.5 billion to $34.7 billion, over 10% projected growth year-over-year. I couldn't be more proud of how our team has come together, stepped up and delivered these results.

現在轉向我們的財務指導。雖然經濟不在我們的控制之下，但我們的利潤率卻在，這就是為什麼我們要提高整個財政年度的利潤率目標。對於 24 財年，我們將非 GAAP 營業利潤率提高到 28%，同比提高 550 個基點。我們仍然相信，我們將在 25 財年第一季度達到 30% 的非 GAAP 營業利潤率。我們對我們的進步感到無比興奮。我們維持我們的 24 財年收入指引在大約 345 億美元至 347 億美元之間，預計同比增長超過 10%。我為我們的團隊如何團結一致、加緊努力並取得這些成果感到無比自豪。

I've also been asked numerous times this quarter by our investors and our customers how we're able to make so much progress so fast and deliver these incredible numbers. It's very simple. It's our Ohana culture. It's our superpower. And again, I'd like to thank our amazing team for this incredible accomplishment.

本季度，我們的投資者和客戶也多次問我，我們如何能夠如此迅速地取得如此大的進步並交付這些令人難以置信的數字。這很簡單。這是我們的 Ohana 文化。這是我們的超級大國。再一次，我要感謝我們出色的團隊取得的這一令人難以置信的成就。

Last quarter, I told you of how our AI team is getting ready to launch Einstein GPT, the world's first generative AI for CRM. At Trailhead DX in March in front of thousands of trailblazers here in San Francisco, that's exactly what we did.

上個季度，我告訴過您我們的 AI 團隊如何準備推出 Einstein GPT，這是世界上第一個用於 CRM 的生成 AI。在三月份的 Trailhead DX 上，在舊金山這裡的數千名開拓者面前，這正是我們所做的。

At its foundation, Einstein GPT is open and extensible. Customers can connect to multiple large language models, including from partners like OpenAI, Anthropic and others. This is a whole new way to work for our customers, users and trailblazers. Users on Salesforce are seeing new AI generative features across all of their most common workflows. And while many of these will be created by Salesforce developers, far more will be created by our incredible Trailblazer ecosystem.

Einstein GPT 在其基礎上是開放和可擴展的。客戶可以連接到多個大型語言模型，包括來自 OpenAI、Anthropic 等合作夥伴的模型。對於我們的客戶、用戶和開拓者來說，這是一種全新的工作方式。 Salesforce 的用戶在他們所有最常見的工作流程中都看到了新的 AI 生成功能。雖然其中許多將由 Salesforce 開發人員創建，但更多將由我們令人難以置信的 Trailblazer 生態系統創建。

For low-code trailblazers, Einstein GPT will provide a tool set to design generative AI apps, built on reasonable prompts. For pro code trailblazers, Einstein GPT will offer an extensible ecosystem of LLM providers with configurable grounding. And Einstein GPT is the culmination of tremendous research and engineering by our world-class AI team, and I'd like to congratulate them on this amazing results.

對於低代碼開拓者，Einstein GPT 將提供一個工具集來設計基於合理提示的生成式 AI 應用程序。對於專業代碼開拓者，Einstein GPT 將提供具有可配置基礎的可擴展 LLM 提供商生態系統。 Einstein GPT 是我們世界級 AI 團隊大量研究和工程的結晶，我要祝賀他們取得這一驚人的成果。

And one more amazing result, this week, Einstein, Salesforce Einstein that we've been talking about for so many years on these calls, will generate an incredible 1 trillion predictions for our customers, an incredible milestone on our AI journey.

另一個驚人的結果是，本週，Einstein，Salesforce Einstein，我們多年來一直在這些電話會議上討論，將為我們的客戶產生令人難以置信的 1 萬億預測，這是我們 AI 旅程中令人難以置信的里程碑。

We saw more of the incredible work of our AI team at our New York City World Tour this month when we demonstrated Slack GPT. Slack is a secure treasure trove of company data that generative AI can use to give every company and every employee their own powerful AI assistant, helping every employee be more productive in transforming the future of work. Slack GPT can leverage the power of generative AI, deliver instant conversation summaries, research tools and writing assistance directly in Slack. And you may never need to leave Slack to get a question answered.

在本月的紐約市世界巡迴演唱會上，我們展示了 Slack GPT，我們看到了更多 AI 團隊令人難以置信的工作。 Slack 是公司數據的安全寶庫，生成式 AI 可以利用它為每家公司和每位員工提供自己強大的 AI 助手，幫助每位員工提高工作效率，改變未來的工作方式。 Slack GPT 可以利用生成人工智能的力量，直接在 Slack 中提供即時對話摘要、研究工具和寫作幫助。而且您可能永遠不需要離開 Slack 來獲得問題的解答。

Slack is the perfect conversational interface for working with LLMs, which is why so many AI companies are Slack first and why OpenAI, ChatGPT and Anthropic quad can now use Slack as a native interface. Slack is also delivering integrated sales and service experiences powered by native GPT to be the best interface for all of our Salesforce customers, and there's a lot more magic to come with Slack and generative AI.

Slack 是與 LLM 合作的完美對話界面，這就是為什麼這麼多人工智能公司首先使用 Slack，以及為什麼 OpenAI、ChatGPT 和 Anthropic quad 現在可以使用 Slack 作為本地界面。 Slack 還提供由本機 GPT 提供支持的集成銷售和服務體驗，成為我們所有 Salesforce 客戶的最佳界面，而且 Slack 和生成 AI 帶來更多魔力。

In this month, we also announced Tableau GPT at our Tableau Conference, where we had over 8,000 in-person attendees. Tableau GPT simplifies data analysis for all of our users, enabling anyone to inquire about their data using Einstein GPT and obtain AI-driven insights at scale. The intelligence and automation that Tableau GPT provides is tremendously important in this area of hyperscale data that we're all entering.

本月，我們還在 Tableau 大會上宣布了 Tableau GPT，我們有超過 8,000 名現場與會者。 Tableau GPT 為我們的所有用戶簡化了數據分析，使任何人都可以使用 Einstein GPT 查詢他們的數據並大規模獲得 AI 驅動的見解。 Tableau GPT 提供的智能和自動化在我們都進入的這個超大規模數據領域非常重要。

The coming wave of generative AI will be more revolutionary than any technology innovation that's come before in our lifetime or maybe any lifetime. Like Netscape Navigator, which opened the door to a greater Internet, a new door has opened with generative AI, and it is reshaping our world in ways that we've never imagined. Every CEO realizes they're going to have to invest in AI aggressively to remain competitive. And Salesforce is going to be their trusted partner to get them to do just that.

即將到來的生成式人工智能浪潮將比我們一生或任何一生中出現的任何技術創新更具革命性。就像 Netscape Navigator 打開了通向更大互聯網的大門一樣，一扇新的大門已經打開了生成人工智能，它正在以我們從未想像過的方式重塑我們的世界。每個 CEO 都意識到他們將不得不積極投資人工智能以保持競爭力。 Salesforce 將成為他們值得信賴的合作夥伴，幫助他們做到這一點。

Every CEO I've spoken with sees AI as a revolution beginning and ending with the customer. And every CIO I've spoken with wants more productivity, more automation and more intelligence through using AI.

與我交談過的每一位首席執行官都將 AI 視為一場從客戶開始和結束的革命。與我交談過的每位 CIO 都希望通過使用 AI 來提高生產力、自動化程度和智能程度。

A great example already deploying this technology is Gucci. We're working with them to augment their client advisers by building AI chat technology that creates a Gucci-fied tone of service, well, incredible new voice, amplifying brand, storytelling and incremental sales as well. It's an incredibly exciting vision for generative AI to transform which was customer service into now customer service, marketing and sales, all through augmenting Gucci employee capabilities using this amazing generative AI. But we can only do all of this with trust.

已經部署這項技術的一個很好的例子是 Gucci。我們正在與他們合作，通過構建 AI 聊天技術來增強他們的客戶顧問，這種技術可以創造 Gucci 化的服務基調，嗯，令人難以置信的新聲音，擴大品牌、講故事和增加銷售量。對於生成式人工智能來說，將客戶服務轉變為現在的客戶服務、營銷和銷售，這是一個令人難以置信的令人興奮的願景，所有這一切都是通過使用這種驚人的生成式人工智能來增強 Gucci 員工的能力。但我們只能在信任的情況下做這一切。

Our customers need to understand where their data is going, and they must be able to maintain data integrity and access and privacy controls. Large customers must maintain data compliance as a critical part of their governance while using generative AI and LLMs. This is not true in the consumer environment, but it is true for our customers, our enterprise customers, who demand the highest levels of this capability. For customers who are for years have used relational databases as the secure mechanism of their trusted data, they already have that high level of security to the row and cell level. We all understand that. And that is why we have built our GPT trust layer into Einstein GPT.

我們的客戶需要了解他們的數據去向，並且他們必須能夠維護數據完整性以及訪問和隱私控制。大客戶在使用生成 AI 和 LLM 時，必須將數據合規性作為其治理的關鍵部分。這在消費者環境中並非如此，但對於我們的客戶、我們的企業客戶來說卻是真實的，他們需要最高級別的此功能。對於多年來一直使用關係數據庫作為其可信數據的安全機制的客戶，他們已經擁有行和單元級別的高級別安全性。我們都明白這一點。這就是我們將 GPT 信任層構建到 Einstein GPT 中的原因。

The GPT trust layer gives connected LLMs secure real-time access to data without the need to move all of your data into the LLM itself. It's an incredible breakthrough for our customers in working with LLMs in a secure and trusted way. And while they're using the LLMs, the data itself is not moving and being stored in the LLM. That is what our customers want. They can be sure that the customer data is where they know it is, where they can be assured that it is for their compliance and for their governance. And I cannot be more excited about our AI CRM and delivering on this future of trusted AI through our new Salesforce GPT trust layer.

GPT 信任層為連接的 LLM 提供了對數據的安全實時訪問，而無需將所有數據移動到 LLM 本身。對於我們的客戶以安全可靠的方式與 LLM 合作而言，這是一個令人難以置信的突破。當他們使用 LLM 時，數據本身並沒有移動和存儲在 LLM 中。這就是我們的客戶想要的。他們可以確定客戶數據就在他們知道的地方，他們可以確信這些數據是為了他們的合規性和治理。我對我們的 AI CRM 以及通過我們新的 Salesforce GPT 信任層實現可信 AI 的未來感到無比興奮。

Finally, I can't talk about AI without talking about the success of our data cloud. Data Cloud is the heart of Customer 360 and now our fastest-growing cloud ever. Data Cloud creates a real-time intelligent data lake that brings together and harmonizes all of our customers' data in one place.

最後，我不能不談我們數據云的成功就談人工智能。數據云是 Customer 360 的核心，現在是我們增長最快的雲。數據云創建了一個實時智能數據湖，將我們所有客戶的數據匯集並協調在一個地方。

In Q1, we closed one of our largest health care industry deals ever with Northwell Health, New York's largest private employer. They have 21 hospitals, 900 patient -- 900 outpatient facility or ambulatory facilities and their own medical school all in New York. By integrating Data Cloud with Health Cloud, Tableau, MuleSoft, well, our entire Customer 360 vision, Northwell is improving patient care by bringing together its vast data resources to create a single source of truth and using AI to govern data use and maintain regulatory compliance.

在第一季度，我們與紐約最大的私人雇主 Northwell Health 達成了有史以來最大的醫療保健行業交易之一。他們在紐約擁有 21 家醫院、900 名患者——900 名門診設施或門診設施以及他們自己的醫學院。通過將 Data Cloud 與 Health Cloud、Tableau、MuleSoft 以及我們整個客戶 360 度願景相集成，Northwell 正在通過整合其龐大的數據資源來創建單一的真實來源並使用 AI 來管理數據使用並保持合規性，從而改善患者護理.

This is the future of our customers and our industry. It's AI plus data, plus CRM. And of course, this AI revolution is just getting started, which is why we've invested $250 million in our new AI venture fund to fuel start-ups developing our trusted generative AI vision. We'll be talking more about this at our AI Day event on June 12 in New York City, and I hope that you'll join me there.

這是我們客戶和我們行業的未來。它是 AI 加上數據，再加上 CRM。當然，這場 AI 革命才剛剛開始，這就是為什麼我們向新的 AI 風險基金投資了 2.5 億美元，以推動初創企業開發我們值得信賴的生成 AI 願景。我們將在 6 月 12 日於紐約市舉行的 AI 日活動中更多地討論這個問題，我希望你能加入我的行列。

To wrap up. We're transforming every corner of our company. We're laser-focused on our short-term and long-term restructuring, improving productivity and performance, prioritizing our core innovations and delivering for our shareholders. As a result, productivity is up, profitability is up, revenue is up, cash flow is up, and we've dramatically increased our margin guidance. And just like the cloud, mobile and social, well, AI, this revolution is a new innovation cycle.

總結一下。我們正在改變我們公司的每一個角落。我們專注於我們的短期和長期重組，提高生產力和績效，優先考慮我們的核心創新並為我們的股東提供服務。結果，生產率提高了，盈利能力提高了，收入提高了，現金流也提高了，我們大幅提高了利潤率指引。就像雲、移動和社交一樣，好吧，人工智能，這場革命是一個新的創新周期。

It's going to be a new spending cycle as well, which is going to spark a massive new tech buying cycle. And we've led the industry through each of these cycles, and I couldn't be more excited for our future as we continue on a path for our long-term goal to make Salesforce the largest, most profitable enterprise software company in the world and the #1 safest and most trusted AI CRM.

這也將是一個新的支出週期，這將引發一個大規模的新技術購買週期。我們在每個週期中都引領著行業，我對我們的未來感到無比興奮，因為我們將繼續朝著我們的長期目標邁進，使 Salesforce 成為世界上最大、盈利能力最強的企業軟件公司以及排名第一的最安全、最值得信賴的 AI CRM。

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

有了這個，布賴恩，我會把它交給你。

Thanks, Marc. As Marc said, we're continuing our transformation across every part of our company. Our focus on performance culture and operational excellence contributed to our strong first quarter results. Since our last call, we've removed layers to get closer to our customers and took complexity out of our business to help us accelerate through the rest of the year. We clearly defined our return in remote office guidelines for our employees, and it's been great to get together even more in our offices and with our customers around the globe. I had the chance to visit many of our offices this quarter, and the energy is incredible.

謝謝，馬克。正如馬克所說，我們正在繼續我們公司各個部門的轉型。我們對績效文化和卓越運營的關注促成了我們強勁的第一季度業績。自從我們上次通話以來，我們已經刪除了層次以更貼近我們的客戶，並消除了我們業務的複雜性，以幫助我們在今年餘下的時間裡加速發展。我們為我們的員工明確定義了我們的遠程辦公室回報指南，很高興能在我們的辦公室和全球各地的客戶中有更多的人聚在一起。本季度我有機會參觀了我們的許多辦公室，精力充沛。

As you heard from Marc, our transformation plan continues to deliver top and bottom line growth as we help our customers increase productivity, drive efficiency and become AI-first companies, but we're still operating in an uncertain macro environment. Customers continue to scrutinize every deal, and we see elongated deal cycles and deal compression, particularly in our more transactional revenue streams like SMB, create and close and self-serve.

正如您從 Marc 那裡聽到的那樣，我們的轉型計劃繼續實現收入和利潤增長，因為我們幫助客戶提高生產力、提高效率並成為人工智能優先的公司，但我們仍在不確定的宏觀環境中運營。客戶繼續審查每筆交易，我們看到交易週期延長和交易壓縮，特別是在我們更多的交易收入流中，如 SMB、創建和關閉以及自助服務。

Also in Q1, our Professional Service business started to see less demand for multiyear transformations and, in some cases, delayed projects as customers focus on quick wins and fast time to value. But for this reason, we saw a strong performance from some of our fast time-to-value efficiency-focused products with sales performance management, sales productivity and digital service all growing annual recurring revenue above 40% in the quarter.

同樣在第一季度，我們的專業服務業務開始看到對多年轉型的需求減少，並且在某些情況下，由於客戶關注速贏和快速實現價值，項目被推遲。但出於這個原因，我們看到我們的一些以快速實現價值為重點的效率產品表現強勁，這些產品具有銷售績效管理、銷售生產力和數字服務，所有這些產品在本季度的年度經常性收入都增長了 40% 以上。

As customers look to reduce complexity and achieve faster time to value, they're expanding their adoption of Salesforce Cloud, a key growth strategy for us.

隨著客戶希望降低複雜性並實現更快的價值實現，他們正在擴大對 Salesforce Cloud 的採用，這是我們的一項關鍵增長戰略。

The world's most recognized companies are relying on Salesforce. More than 90% of the Fortune 100 use Salesforce, and they average more than 5 of our clouds. This is why we are so excited about our AI plus data, plus CRM strategy.

世界上最知名的公司都依賴 Salesforce。超過 90% 的財富 100 強企業使用 Salesforce，他們平均擁有超過 5 個我們的雲。這就是為什麼我們對我們的 AI 加數據以及 CRM 策略如此興奮。

As Marc explained, we're building Einstein GPT and Data Cloud into every cloud in our Customer 360, and we're perfectly positioned to help our customers harness the phenomenal power of AI.

正如 Marc 解釋的那樣，我們正在將 Einstein GPT 和數據云構建到我們 Customer 360 的每個雲中，我們完全有能力幫助我們的客戶利用 AI 的非凡力量。

Our core offerings remain resilient. In Q1, 9 of our top 10 deals included sales, service and platform. Industry clouds continued to be a tailwind to our growth, and we saw momentum with great customers like Northwell, USDA Rural Development and NASA that we showcased at World Tour D.C. in April. Once again, 8 of our industry clouds grew ARR above 50%. I met with hundreds of customers in the quarter, and we hosted 700 meetings in our innovation centers with our top customers and prospects. Generative AI is top of mind for all of them as they look to benefit from the intelligence automation and cost savings that Salesforce is uniquely positioned to deliver. We're seeing tremendous appetite for our new generative AI products, starting with Einstein GPT, Slack GPT and Data Cloud. Our generative AI products will be a catalyst for our future growth.

我們的核心產品保持彈性。在第一季度，我們的前 10 筆交易中有 9 筆涉及銷售、服務和平台。行業雲繼續成為我們增長的順風，我們看到了 Northwell、USDA Rural Development 和 NASA 等大客戶的發展勢頭，我們在 4 月份的 World Tour D.C. 上展示了這一點。再次，我們的 8 個行業雲的 ARR 增長超過 50%。我在本季度會見了數百名客戶，我們在創新中心與頂級客戶和潛在客戶舉行了 700 場會議。生成式 AI 是他們所有人的首要考慮，因為他們希望從 Salesforce 具有獨特優勢的智能自動化和成本節約中獲益。從 Einstein GPT、Slack GPT 和 Data Cloud 開始，我們看到了對我們新的生成 AI 產品的巨大需求。我們的生成式 AI 產品將成為我們未來增長的催化劑。

As Marc mentioned, Data Cloud continues to be one of our fastest-growing products, and we had great wins in the quarter with companies like Major League Soccer and Giorgio Armani. Armani uses Data Cloud to deliver hyper-personalized online and in-store experiences, real-time engagement and curated shopping recommendations. We can see how Data Cloud and Einstein GPT are going to create experiences that weren't possible before and really drive growth.

正如 Marc 所提到的，Data Cloud 仍然是我們增長最快的產品之一，我們在本季度與 Major League Soccer 和 Giorgio Armani 等公司取得了巨大的成功。 Armani 使用 Data Cloud 提供超個性化的在線和店內體驗、實時參與和精心策劃的購物推薦。我們可以看到 Data Cloud 和 Einstein GPT 將如何創造以前不可能實現的體驗並真正推動增長。

In an environment where customers are optimizing their current tech stacks, integration and automation continue to be efficiency drivers. MuleSoft again delivered strong results with wins at Siemens, Lenovo and Vodafone. For the first time, Salesforce was ranked #1 in integration by market share in the latest IDC Software Tracker, a great testament to our MuleSoft team.

在客戶優化其當前技術堆棧的環境中，集成和自動化仍然是效率驅動因素。 MuleSoft 再次在西門子、聯想和沃達丰贏得了勝利。 Salesforce 首次在最新的 IDC Software Tracker 中按市場份額在集成方面排名第一，這很好地證明了我們的 MuleSoft 團隊。

Tableau is unleashing the power of our Data Cloud, unlocking customer data and delivering actionable real-time insights. In the quarter, we had great wins at customers like UnionBank of the Philippines, Discover Financial Service, Moderna, ADT Solar and Alaska Air. We've made great investments to reaccelerate Tableau, including new leadership along with product innovations like Tableau GPT and Revenue Intelligence, now one of our fastest-growing add-ons. I'm really encouraged by the Slack team who has created an ambitious product road map with generative AI at the center. In Q1, we saw amazing momentum with customers like the California Office of System Integration, Paramount Global, Revel and OpenAI, and rolled out an AI-ready platform, Slack Canvas, and app integrations with ChatGPT and Anthropic Cloud.

Tableau 正在釋放我們數據云的力量，解鎖客戶數據並提供可操作的實時見解。本季度，我們在菲律賓聯合銀行、Discover Financial Service、Moderna、ADT Solar 和 Alaska Air 等客戶中取得了巨大成功。我們進行了大量投資以重新加速 Tableau，包括新的領導層以及 Tableau GPT 和 Revenue Intelligence 等產品創新，後者現在是我們增長最快的插件之一。我真的很受 Slack 團隊的鼓舞，他們創建了一個以生成 AI 為中心的雄心勃勃的產品路線圖。在第一季度，我們看到了與加州系統集成辦公室、Paramount Global、Revel 和 OpenAI 等客戶的驚人勢頭，並推出了人工智能就緒平台 Slack Canvas，以及與 ChatGPT 和 Anthropic Cloud 的應用程序集成。

Overall, I could not be more thrilled with our offerings and the market position especially as it relates to delivering on the promise of AI. We're looking forward to continuing the energy and momentum at our AI Day in just a couple of weeks. I'm very proud of the teams and of our partners. Their focus on customer success continues to be outstanding. As Marc said, our productivity is up. Profitability is up. Revenue is up, cash flow is up. We're increasing our margin guidance and Salesforce is leading the way as the #1 AI CRM.

總的來說，我對我們的產品和市場地位感到非常興奮，尤其是因為它與實現人工智能的承諾有關。我們期待在幾週後的 AI 日繼續保持活力和勢頭。我為團隊和我們的合作夥伴感到非常自豪。他們對客戶成功的關注仍然很突出。正如馬克所說，我們的生產力提高了。盈利能力上去了。收入增加，現金流增加。我們正在提高我們的利潤率指導，Salesforce 作為第一大 AI CRM 處於領先地位。

Now over to you, Amy.

現在輪到你了，艾米。

Thank you, Brian. As Marc said, a key part of our transformation to profitable growth is short and long-term restructuring of the company. We have now largely completed the restructuring announced in January, and we're completing our comprehensive operating and go-to-market review. As we shift to the implementation phase, we're executing against 3 key pillars: optimization of resources and organization structure, product investment prioritization; and operational record.

謝謝你，布萊恩。正如馬克所說，我們向盈利增長轉型的一個關鍵部分是公司的短期和長期重組。我們現在已經基本完成了 1 月份宣布的重組，我們正在完成全面的運營和上市審查。當我們轉向實施階段時，我們正在針對 3 個關鍵支柱執行：優化資源和組織結構、產品投資優先級；和操作記錄。

We continue to use sales and marketing and G&A as the primary drivers of leverage, while R&D remains an important investment area. Our profitable growth framework, disciplined capital allocation strategy and opportunity to drive shareholder value are represented in our actions and in our results.

我們繼續將銷售和營銷以及 G&A 作為槓桿的主要驅動力，而研發仍然是一個重要的投資領域。我們的盈利增長框架、嚴格的資本分配策略和推動股東價值的機會體現在我們的行動和結果中。

Now turning to our results for Q1 fiscal year '24, beginning with top line commentary. For the first quarter, revenue was $8.2 billion, up 11% year-over-year or 13% in constant currency, with the beat primarily driven by strong momentum in MuleSoft and more resilient core performance. Geographically, we saw strong new business growth in parts of EMEA and LatAm, specifically Switzerland, Italy and Brazil, while we experienced continued pressure in the United States.

現在轉向我們 24 財年第一季度的業績，從頂線評論開始。第一季度，收入為 82 億美元，同比增長 11% 或按固定匯率計算增長 13%，增長的主要原因是 MuleSoft 的強勁勢頭和更具彈性的核心業績。從地域上看，我們在 EMEA 和 LatAm 的部分地區看到了強勁的新業務增長，特別是瑞士、意大利和巴西，而我們在美國經歷了持續的壓力。

In Q1, the Americas revenue grew 10%, EMEA grew 12% or 17% in constant currency. And APAC grew 16% or 24% in constant currency.

第一季度，美洲收入增長 10%，歐洲、中東和非洲增長 12%，按固定匯率計算增長 17%。亞太地區按固定匯率計算增長了 16% 或 24%。

From an industry perspective, manufacturing, automotive and energy all performed well, while high tech and financial services remained under pressure. Q1 revenue attrition ended the quarter at approximately 8%. As expected, we saw a modest increase in Q1, partially attributed to the inclusion of Tableau in the metric. We also noted some incremental weakness in our marketing and commerce attrition.

從行業來看，製造業、汽車業和能源業均表現良好，而高科技和金融服務業繼續承壓。第一季度的收入流失率在本季度結束時約為 8%。正如預期的那樣，我們看到第一季度出現適度增長，部分原因是將 Tableau 納入了指標。我們還注意到我們的營銷和商業減員中出現了一些漸進的弱點。

As Marc said, non-GAAP operating margin finished strong in Q1 at 27.6%, driven by our disciplined investment strategy and accelerating our restructuring efforts. Q1 operating cash flow was $4.5 billion, up 22% year-over-year. This includes a 910 basis points headwind from restructuring. Q1 free cash flow was $4.2 billion, up 21% year-over-year.

正如 Marc 所說，在我們嚴格的投資策略和加速重組工作的推動下，第一季度非 GAAP 營業利潤率強勁，達到 27.6%。第一季度運營現金流為 45 億美元，同比增長 22%。這包括重組帶來的 910 個基點逆風。第一季度自由現金流為 42 億美元，同比增長 21%。

Turning to remaining performance obligation, or RPO, which represents all future revenue under contract. This ended Q1 at $46.7 billion, up 11% year-over-year. Current remaining performance obligation, or CRPO, ended at $24.1 billion, up 12% year-over-year in both nominal and constant currency, ahead of expectations driven by strong core performance, partially offset by continued create and close softness.

轉向剩餘履約義務或 RPO，它代表合同項下的所有未來收入。第一季度末為 467 億美元，同比增長 11%。當前剩餘履約義務 (CRPO) 收於 241 億美元，按名義貨幣和固定匯率計算均同比增長 12%，超出了強勁核心業績推動的預期，但部分被持續創造和收盤疲軟所抵消。

And finally, we continue to deliver on our capital return commitment. In Q1, we returned $2.1 billion in the form of share repurchases, bringing the total return to more than $6 billion since the program was initiated last August, representing more than 38 million shares.

最後，我們繼續履行我們的資本回報承諾。第一季度，我們以股票回購的形式返還了 21 億美元，自去年 8 月啟動該計劃以來，總回報超過 60 億美元，代表超過 3800 萬股。

Before moving to guidance, I wanted to briefly touch on the current macro environment that Brian discussed. The more measured buying behavior persisted in Q1. And as Brian noted, in Q1, we started to see weakness in our Professional Services business. We expect these factors to persist, which is incorporated in our guidance.

在轉向指導之前，我想簡要談談 Brian 討論的當前宏觀環境。第一季度持續了更慎重的購買行為。正如 Brian 指出的那樣，在第一季度，我們開始看到我們的專業服務業務疲軟。我們預計這些因素將持續存在，這已納入我們的指導方針。

Let's start with fiscal year '24. On revenue, we are holding our guidance of $34.5 billion to $34.7 billion, representing over 10% growth year-over-year in both nominal and constant currency. The strength in our Q1 performance is offset by the pressure in our professional services business, as previously discussed. For fiscal year '24, we are raising non-GAAP operating margin guidance to 28%, representing a 550 basis points improvement year-over-year. This guidance increase is driven by the acceleration of our restructuring efforts and also includes reinvestment in targeted areas, namely in R&D. I'm proud of our progress and remain confident in our trajectory as we progress towards our 30% non-GAAP operating margin target in Q1 '25.

讓我們從 24 財年開始。在收入方面，我們維持 345 億美元至 347 億美元的指導，按名義和固定匯率計算，同比增長超過 10%。如前所述，我們第一季度業績的優勢被我們專業服務業務的壓力所抵消。對於 24 財年，我們將非 GAAP 營業利潤率指引提高至 28%，同比提高 550 個基點。這一指引的增加是由我們重組工作的加速推動的，還包括對目標領域（即研發）的再投資。我為我們的進步感到自豪，並在我們朝著 25 年第一季度 30% 的非 GAAP 營業利潤率目標邁進的過程中對我們的軌跡充滿信心。

We also remain focused on stock-based compensation and continue to expect it to improve this year to below 9% as a percent of revenue.

我們還繼續關注基於股票的薪酬，並繼續預計今年它佔收入的百分比將提高到 9% 以下。

Before moving to EPS, on restructuring, we now expect the charges in FY '24 to come in towards the higher end of the range previously provided in our last earnings release. As a result of these updates, we now expect fiscal year '24 GAAP EPS of $2.67 to $2.69, including estimated charges for the restructuring of $1.11. Non-GAAP EPS is now expected to be $7.41 to $7.43. And we are raising our fiscal year '24 operating cash flow growth to be approximately 16% to 17%, which now includes a 14- to 16-point headwind from restructuring. As a reminder, we will see an increase in our cash taxes in fiscal '24 as we draw down our remaining net operating losses.

在轉向 EPS 之前，在重組方面，我們現在預計 24 財年的費用將接近我們上次財報發布中提供的範圍的高端。由於這些更新，我們現在預計 24 財年 GAAP 每股收益為 2.67 美元至 2.69 美元，包括 1.11 美元的重組費用估計。 Non-GAAP 每股收益現在預計為 7.41 美元至 7.43 美元。我們將 24 財年的運營現金流增長率提高到大約 16% 到 17%，其中現在包括重組帶來的 14 到 16 個百分點的逆風。提醒一下，隨著我們減少剩餘的淨運營虧損，我們將在 24 財年看到現金稅增加。

CapEx for the fiscal year is expected to be slightly below 2.5% of revenue. This results in free cash flow growth of approximately 17% to 18% for the fiscal year.

本財年的資本支出預計將略低於收入的 2.5%。這導致本財年的自由現金流量增長約 17% 至 18%。

Now to guidance for Q2. On revenue, we expect $8.51 billion to $8.53 billion, growth of approximately 10% in both nominal and constant currency. CRPO growth for Q2 is expected to be approximately 10% year-over-year in nominal and constant currency. Our guidance incorporates the momentum of our execution in Q1, offset by the persistent measured buying behavior and a decline in Professional Services' fixed fees contribution. The professional services impact represents approximately a 1 point headwind to growth.

現在為第二季度提供指導。在收入方面，我們預計在 85.1 億美元至 85.3 億美元之間，按名義和固定匯率計算均增長約 10%。按名義和固定匯率計算，第二季度的 CRPO 增長率預計將同比增長約 10%。我們的指引結合了我們在第一季度的執行勢頭，被持續衡量的購買行為和專業服務固定費用貢獻的下降所抵消。專業服務的影響代表了大約 1 點的增長逆風。

For Q2, we expect GAAP EPS of $0.79 to $0.80 and non-GAAP EPS of $1.89 to $1.90. And as we focus on shareholder return and disciplined capital allocation, we continue to expect to fully offset our stock-based compensation dilution through our share repurchases in fiscal year '24.

對於第二季度，我們預計 GAAP 每股收益為 0.79 美元至 0.80 美元，非 GAAP 每股收益為 1.89 美元至 1.90 美元。由於我們專注於股東回報和有紀律的資本分配，我們繼續期望通過 24 財年的股票回購完全抵消我們基於股票的薪酬稀釋。

In closing, we continue to transform every corner of the company. We are hyper-focused on delivering the next wave of innovation led by Data Cloud and Einstein GPT. And Salesforce is well-positioned to remain the market leader in this new AI-first world. We are committed to delivering long-term shareholder value, and I personally want to thank our shareholders for their continued support. Now Mike, let's open up the call for questions.

最後，我們繼續改造公司的每個角落。我們非常專注於提供由 Data Cloud 和 Einstein GPT 引領的下一波創新。 Salesforce 處於有利地位，可以在這個以 AI 為先的新世界中保持市場領先地位。我們致力於為股東創造長期價值，我個人要感謝股東們一直以來的支持。現在邁克，讓我們開始提問。

Thanks, Amy. Operator, we'll move to questions now. (Operator Instructions) In addition, I'd like to introduce Srini Tallapragada, our Head of Engineering, who will be joining us for Q&A today. With that, Emma, let's move to the questions.

謝謝，艾米。接線員，我們現在開始提問。 （操作員說明）此外，我想介紹我們的工程主管 Srini Tallapragada，他今天將加入我們的問答環節。有了這個，艾瑪，讓我們轉向問題。

(Operator Instructions) Your first question today comes from the line of Kirk Materne with Evercore.

（操作員說明）您今天的第一個問題來自 Kirk Materne 與 Evercore 的合作。

Congrats on the good start to the year. Marc, you've been through a number of cycles from a technology perspective. I was just kind of curious where you think we are in terms of people investigating AI versus when the spending cycle around it might kick in. Can you just give us an idea of sort of your thoughts on that and really just the opportunity for you all to monetize AI within your product base?

祝賀今年開局良好。馬克，從技術的角度來看，你經歷了很多周期。我只是有點好奇，你認為我們在研究 AI 的人方面以及圍繞它的支出週期何時可能開始。你能告訴我們你對此的想法嗎？真的只是你們所有人的機會在您的產品庫中通過 AI 獲利？

Well, I think this is the absolute question of the day, which is we are about to enter an unbelievable super cycle for tech and everyone can see that. This is an incredible opportunity for not only Salesforce but our entire industry. I mean perhaps only a year ago or less than a year ago, no one on this call even new what GPT was. Today, ChatGPT is the fastest-growing consumer product of all time and has transformed many, many lives. It's definitely not just the technology of this lifetime, but maybe any lifetime. It's an incredible technology. And every company is going to have to transform because every company is going to have to become more productive, more automated more intelligent through this technology to be competitive with our companies.

好吧，我認為這是當今的絕對問題，我們即將進入一個令人難以置信的科技超級週期，每個人都可以看到這一點。這不僅對 Salesforce 如此，對我們整個行業來說都是難得的機會。我的意思是，也許就在一年前或不到一年前，參加這次電話會議的人甚至都不知道 GPT 是什麼。如今，ChatGPT 是有史以來增長最快的消費產品，改變了許許多多的生活。絕對不僅僅是這一世的技術，也許是任何一世。這是一項不可思議的技術。每家公司都必須轉型，因為每家公司都必須通過這項技術變得更高效、更自動化、更智能，才能與我們的公司競爭。

And just yesterday, I'm in a room here at the top of Salesforce Tower on the 60th floor, and we have the CEO of a very large bank here. And like every other sales call I've made in the last quarter, there's only one thing that customers want to talk about, and that's artificial intelligence and specifically, generative AI.

就在昨天，我在 Salesforce Tower 60 樓頂層的一個房間裡，我們有一家非常大的銀行的首席執行官。就像我在上個季度打的所有其他銷售電話一樣，客戶只想談論一件事，那就是人工智能，特別是生成人工智能。

Of course, we have been a leader in this area with Einstein, more than 1 trillion transactions delivered this week. But these are primarily predictive transactions built on machine intelligence, machine learning and deep learning. But in 2018, deep learning evolved and became much more sophisticated and became generative as these neural networks expanded their capabilities and also the hardware went to another level as well. So now we have this incredible new capability. It's a new platform for growth, and I couldn't be more excited.

當然，我們與 Einstein 在這方面一直處於領先地位，本週交付了超過 1 萬億筆交易。但這些主要是建立在機器智能、機器學習和深度學習基礎上的預測交易。但在 2018 年，隨著這些神經網絡擴展了它們的能力，並且硬件也達到了另一個水平，深度學習得到了發展，變得更加複雜和具有生成性。所以現在我們擁有了這種令人難以置信的新功能。這是一個新的成長平台，我無比興奮。

But yesterday, there were many questions from my friend who I'm not going to give you his name because he's one of the -- the CEO of one of the largest and most important banks in the world. And I'll just say that, of course, his primary focus is on productivity. He knows that he wants to make his bankers a lot more successful. He wants every banker to be able to rewrite a mortgage, but not every banker can, because writing the mortgage takes a lot of technical expertise.

但是昨天，我的朋友提出了很多問題，我不會告訴你他的名字，因為他是世界上最大和最重要的銀行之一的首席執行官之一。我只想說，當然，他的主要關注點是生產力。他知道他想讓他的銀行家們更加成功。他希望每個銀行家都能重寫抵押貸款，但不是每個銀行家都能，因為編寫抵押貸款需要大量的技術專長。

But as we showed him in the meeting through a combination of Tableau, which we demonstrated and Slack, which we demonstrated, and Salesforce's Financial Services Cloud, which he has tens of thousands of users on, that banker understood that this would be incredible. But I also emphasize to him that LLMs, or large language models, they have a voracious appetite for data. They want every piece of data that they can consume. But through his regulatory standards, he cannot deliver all that data into the LLM because it becomes amalgamated.

但是當我們在會議上通過我們展示的 Tableau 和我們展示的 Slack 以及他擁有數万用戶的 Salesforce 金融服務雲的組合向他展示時，這位銀行家明白這將是不可思議的。但我也向他強調，LLM，或大型語言模型，他們對數據有著貪婪的胃口。他們想要他們可以使用的每一條數據。但是通過他的監管標準，他無法將所有這些數據都提供給 LLM，因為它被合併了。

Today, he runs on Salesforce, and his data is secured down to the row and cell level. He knows that readers don't block writers, that there's all types of security provisions on regarding who can see what data about what account or what customer. And when you put it into an LLM, those permissions are not understood. So that is a very powerful moment to realize that the way that LLMs operate is in a way state where they're kind of consuming all this data and then giving us that information back out, well, that Salesforce's opportunity. That's why we built this GPT trust layer.

如今，他在 Salesforce 上運行，他的數據被保護到行和單元格級別。他知道讀者不會阻止作者，關於誰可以看到關於什麼賬戶或什麼客戶的什麼數據有各種類型的安全規定。當你把它放到 LLM 中時，這些權限是不被理解的。因此，這是一個非常有力的時刻，讓我們意識到 LLM 的運作方式處於一種狀態，他們正在消耗所有這些數據，然後將這些信息返回給我們，好吧，Salesforce 的機會。這就是我們構建此 GPT 信任層的原因。

And through the GPT trust layer and rebuilding all of our apps, including Slack and Tableau, but as we demonstrated him yesterday, a new Sales Cloud, a new Service Cloud, a new marketing cloud, and what we'll show on June 12 in New York City, a complete reconceptualization of our product line, what that means for this customer and for every customer is that they have an opportunity to transform their business. And for Salesforce, that also means an opportunity to transform ourselves and for our industry, a new super cycle where every company will have to transform to be AI first.

通過 GPT 信任層並重建我們所有的應用程序，包括 Slack 和 Tableau，但正如我們昨天向他展示的那樣，一個新的銷售雲、一個新的服務雲、一個新的營銷雲，以及我們將在 6 月 12 日展示的內容紐約市，我們產品線的完全重新概念化，這對這個客戶和每個客戶來說意味著他們有機會轉變他們的業務。對於 Salesforce 而言，這也意味著一個轉變我們自己和我們行業的機會，一個新的超級週期，每個公司都必須首先轉變為 AI。

Your next question comes from the line of Keith Weiss with Morgan Stanley.

你的下一個問題來自 Keith Weiss 與摩根士丹利的對話。

This is Elizabeth Porter on for Keith Weiss. I wanted to ask on the potential disruption from rebooting the sales enablement process. Are we past the point of seeing disruption? Or could that be a future risk? And if so, how is it included in guidance? The CRPO guidance for 10% looks like a bit of a slowdown despite the easier comp. And Amy, you called out Pro Services a 1-point headwind. But just any other factors we should keep in mind that may create a challenge over the next couple of months?

這是 Keith Weiss 的 Elizabeth Porter。我想詢問重新啟動銷售支持流程的潛在中斷。我們是否已經過了看到中斷的地步？或者這可能是未來的風險？如果是這樣，它是如何包含在指南中的？儘管比較容易，但 10% 的 CRPO 指導看起來有點放緩。艾米，你把 Pro Services 稱為 1 點逆風。但是我們應該牢記的任何其他因素可能會在接下來的幾個月中帶來挑戰嗎？

Well, I'll tell you that I think that as you know, in Q1, we went through tremendous disruption with human resources in our company, and it was very disruptive to our Ohana. And I'm so grateful to them for how they supported the whole company, all the customers and themselves during what was probably one of the most disruptive quarters that I've seen and yet we delivered these incredible numbers and this incredible technology vision going forward.

好吧，我會告訴你，我認為如你所知，在第一季度，我們公司的人力資源經歷了巨大的混亂，這對我們的 Ohana 造成了很大的破壞。我非常感謝他們在我所見過的可能是最具破壞性的季度之一期間如何支持整個公司、所有客戶和他們自己，但我們交付了這些令人難以置信的數字和這一令人難以置信的技術願景.

In terms of enablement, the sales organization, its ability to kind of move forward, that is not, I would say, a material part of what happened in the quarter or what's going to happen for the year. Our sales organization remains with a very high level of productivity. But let me turn it over to Brian to speak directly to his strategy on delivering the year.

在支持方面，銷售組織及其向前發展的能力，我想說，這不是本季度發生的事情或今年將要發生的事情的重要組成部分。我們的銷售組織保持著非常高的生產力水平。但讓我把它交給布賴恩直接談談他交付年度的策略。

Yes, Marc, thank you. I appreciate it. And Elizabeth, thank you for the question. I think you're referencing some comments we made on previous calls about enablement being an important strategy for us. As we saw during the pandemic, not as many of our AEs and SEs and leaders were as enabled as we would like. We've made those changes, and we've really invested in the time to make sure our AEs understand our product portfolio, the entire Customer 360, and we're on sort of the next generation of enablement.

是的，馬克，謝謝你。我很感激。伊麗莎白，謝謝你提出這個問題。我想你是在引用我們在之前的電話會議上發表的關於支持是我們的重要戰略的一些評論。正如我們在大流行期間看到的那樣，我們的 AE 和 SE 以及領導者並沒有像我們希望的那樣獲得支持。我們已經做出了這些改變，我們真的投入了時間來確保我們的 AE 了解我們的產品組合，整個 Customer 360，並且我們正在進行下一代支持。

As Marc has talked about, this new AI wave is going to create a huge opportunity for us. And we need to make sure that we're investing in the enablement to bring our teams along. It's been a very short window around this innovation, and we've got some work to do on this, but we're very, very excited with our path forward, our position in the market, all that we're doing with our customers, the demand we're feeling from our customers. Marc mentioned it, and I had the same experience, every CEO in the world is talking to us about generative AI right now. And we are investing heavily to make sure our account executives, our sales teams, in fact, the entire company is able to articulate our value proposition to our customers.

正如 Marc 所說，這一新的 AI 浪潮將為我們創造巨大的機會。我們需要確保我們正在投資於支持我們的團隊。這是圍繞這項創新的一個非常短的窗口，我們在這方面還有一些工作要做，但我們對我們的前進道路、我們在市場中的地位以及我們與客戶所做的一切感到非常、非常興奮，我們從客戶那裡感受到的需求。 Marc 提到過，我也有同樣的經歷，現在世界上每個 CEO 都在和我們談論生成人工智能。我們正在大力投資，以確保我們的客戶主管、我們的銷售團隊，事實上，整個公司都能夠向我們的客戶闡明我們的價值主張。

So Amy, I don't know if you have any further comments there?

那麼艾米，我不知道你是否有任何進一步的意見？

Sure. Elizabeth, you mentioned CRPO in Professional Services, so let me jump in on that. For our guide for this next quarter, we are seeing some pressures from the macro situation and then also specifically from Professional Services. And there's a bit of a nuance with ProServ that I want to make sure people understand.

當然。伊麗莎白，你在專業服務中提到了 CRPO，所以讓我來談談。對於我們下一季度的指南，我們看到了來自宏觀形勢的一些壓力，特別是來自專業服務的壓力。我想確保人們理解 ProServ 的一些細微差別。

So if you back up, our customers can contract for Professional Services in 2 ways, either on a time and materials basis, which is typically used for smaller projects, or on a fixed fee kind of milestone basis. For purposes of CRPO, we only include projected revenue from fixed fee deals. One of the things that we are seeing right now is not only a Professional Services as a whole seeing pressure, but more customers are choosing to contract on a time and materials basis, which is not included in our CRPO. So as a result, we're seeing kind of a double pressure there. And I'm expecting a full 1-point headwind to CRPO for the quarter from Professional Services.

因此，如果您支持，我們的客戶可以通過兩種方式簽訂專業服務合同，一種是基於時間和材料，通常用於較小的項目，另一種是基於里程碑式的固定費用。出於 CRPO 的目的，我們僅包括固定費用交易的預計收入。我們現在看到的一件事不僅是整個專業服務面臨壓力，而且越來越多的客戶選擇按時間和材料簽訂合同，這不包括在我們的 CRPO 中。因此，我們在那裡看到了某種雙重壓力。我預計本季度專業服務對 CRPO 的不利影響將達到 1 個百分點。

Your next question comes from the line of Brad Sills with Bank of America.

你的下一個問題來自美國銀行的 Brad Sills。

I wanted to ask a question to Brian, I think, here on the efforts here to improve productivity. You mentioned removing some layers here. My question is, we think of all these actions that you're taking as drivers of margin expansion. But are you starting to see some early traction here on the sales productivity front, such that perhaps that's driving some upside here across the business, perhaps larger deals now that you're seeing coming out of the field and pipeline and some of the deal closure?

我想問布賴恩一個問題，我想，關於這里為提高生產力所做的努力。你提到在這裡刪除一些層。我的問題是，我們認為您正在採取的所有這些行動都是利潤率擴張的驅動力。但是你是否開始在銷售生產力方面看到一些早期的牽引力，這樣也許這正在推動整個業務的一些上行，也許是更大的交易，因為你看到了現場和管道的出現以及一些交易的結束？

Thanks, Brad, for the question. I really appreciate it. As you know, we're operating in a constrained environment right now. And so we are really focused on this productivity measure and metric for our organization right now, investing heavily, as I mentioned earlier, and the enablement part of our organization, also looking at other ways to drive productivity. And one of the things that we're talking quite a bit about right now is pricing and packaging, bringing together logical products that we can be selling in a single motion versus our go-to-market, which is largely aligned by product how do we focus on a larger average deal size for every transaction. And so big investments on that front, really a strong focus on productivity as it relates to moving people upmarket as well.

謝謝布拉德提出這個問題。對此，我真的非常感激。如您所知，我們現在在一個受限的環境中運作。因此，我們現在真正專注於我們組織的這種生產力衡量和指標，正如我之前提到的那樣，我們組織的支持部分進行了大量投資，同時也在尋找其他提高生產力的方法。我們現在談論的很多事情之一是定價和包裝，將我們可以在單一動作中銷售的合乎邏輯的產品與我們的上市相結合，這在很大程度上取決於產品如何做我們專注於每筆交易的平均交易規模更大。在這方面的如此大的投資，實際上是對生產力的高度關注，因為它也與將人們推向高端市場有關。

We're thinking about self-serve in the bottom end of our market. How do we drive a self-serve motion automated motion at the low end of our market to bring our account executives upmarket to drive higher productivity in the sales organization?

我們正在考慮在我們市場的底端提供自助服務。我們如何在我們的低端市場推動自助服務自動化運動，將我們的客戶經理帶到高端市場，從而提高銷售組織的生產力？

So clearly, a big motion for us right now. Feel very good about our big deal motion. Actually in Q4, we saw some -- sorry, in Q1, we saw some very good big deal execution from the team. That is not really an area that has held us back. We feel very good about our ability to transform companies and transact these large businesses. It really is the velocity business that has held us back a bit on our crate and close, some of the SMB transactions. So we have a clear focus in this area to drive the productivity with our plans going into Q2 and beyond into Q4.

很明顯，現在對我們來說是一個重大動議。對我們的重大議案感到非常滿意。實際上在第四季度，我們看到了一些——抱歉，在第一季度，我們看到了團隊的一些非常好的大交易執行。這並不是真正阻礙我們前進的領域。我們對我們改造公司和處理這些大型企業的能力感到非常滿意。確實是速度業務使我們在箱子上有點退縮並關閉了一些 SMB 交易。因此，我們明確關注這一領域，以通過我們進入第二季度和第四季度的計劃來提高生產力。

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

你的下一個問題來自 Brent Thill 與 Jefferies 的合作。

Amy, regarding Americas, that was a pretty large decel, one of your slowest growth quarters, I think, ever in Americas. The rest of the world did decel, but maybe not quite as the magnitude of the Americas. Can you just speak to what happened there in that region?

艾米，關於美洲，這是一個相當大的減速，我認為，這是美洲有史以來增長最慢的季度之一。世界其他地區確實減速了，但可能沒有美洲那麼大。你能談談那個地區發生的事情嗎？

Sure. So thanks, Brent, for the question. The Americas do see deceleration, a 10% year-on-year revenue growth compared to 17% in EMEA and about 24% in nominal APAC. We are continuing to see most of the pressure in North America. There were some real pockets of acceleration in EMEA and in LatAm, particularly in Switzerland, I think Brazil, Italy. So we are seeing some good things, but North America has taken the brunt of the deceleration.

當然。謝謝布倫特提出的問題。美洲確實出現了減速，收入同比增長 10%，而歐洲、中東和非洲地區的增長率為 17%，名義亞太地區的增長率約為 24%。我們繼續看到北美的大部分壓力。在 EMEA 和 LatAm 有一些真正的加速，特別是在瑞士，我認為是巴西和意大利。所以我們看到了一些好事，但北美首當其衝。

Brian, do you want to come in and see if you can address that?

布賴恩，你想進來看看你能不能解決這個問題？

Sure, yes. I think when we think about our business from an industry perspective, we have a very nice footprint of our great technology companies and financial services company, both of which were a bit slower than we would have liked in the Americas in Q1. And so as we think about the all-in size of our Americas business, those industries felt a little bit more of the economic headwinds in the quarter in Q1. And so I think a bit of a slowdown from that perspective is a result you're seeing in the Americas business.

當然，是的。我認為，當我們從行業的角度考慮我們的業務時，我們偉大的科技公司和金融服務公司的足跡非常好，這兩家公司在第一季度都比我們在美洲的預期要慢一些。因此，當我們考慮我們美洲業務的整體規模時，這些行業在第一季度感受到了更多的經濟逆風。所以我認為從這個角度來看有點放緩是你在美洲業務中看到的結果。

Your next question comes from the line of Mark Murphy with JPMorgan.

你的下一個問題來自摩根大通的馬克墨菲。

And I'll add my congrats. So Marc, it feels like the tech and software industry has had a recession without the broader economy being in a recession quite yet, and that's very unusual. Do you think with all the purging and optimizing of IT budgets, which is already taking place, plus Salesforce's headcount optimization already being underway that perhaps the next recession might actually be more manageable or easier to navigate than what you had seen in some of the prior cycles?

我要表示祝賀。所以馬克，感覺科技和軟件行業已經陷入衰退，而整體經濟還沒有陷入衰退，這是非常不尋常的。您是否認為，隨著 IT 預算的所有清理和優化（已經在進行），加上 Salesforce 的員工人數優化已經在進行中，也許下一次經濟衰退實際上可能比您在之前的一些經濟衰退中看到的更易於管理或更容易駕馭？週期？

Well, I think that this is a great question. And I tried to address it on the last call. I just really think you have to look at 2020, 2021 was just this massive super cycle called the pandemic. I don't know if you remember, but we had a pandemic a couple of years ago. And during that, we saw tech buying like we never saw. It was incredible and everybody surged on tech buying. So you're really looking at comparisons against that huge mega cycle. And that is what I think is extremely important to understand, the relative comparisons. And that is where my head is at, which is I am constantly comparing against what happened in 2021, but also looking at 2020 and 2019.

好吧，我認為這是一個很好的問題。我試圖在最後一次通話中解決這個問題。我只是真的認為你必須看看 2020 年，2021 年就是這個被稱為大流行的巨大超級週期。我不知道你是否記得，但幾年前我們經歷了一場大流行病。在那期間，我們看到了前所未有的技術購買。這太不可思議了，每個人都熱衷於購買科技產品。所以你真的在看與那個巨大的巨型週期的比較。這就是我認為非常重要的理解，即相對比較。這就是我的想法，我不斷地與 2021 年發生的事情進行比較，同時也在關注 2020 年和 2019 年。

That's a little bit different than '08 and that's a little bit different than '01. We didn't exactly have these huge mega cycles that kind of we were exiting. And I -- that's also what gives me tremendous confidence going forward and that what we're really seeing is that customers are absorbing the huge amounts of technology that they bought. And that is about to come, I believe, to a close. I can't give you the exact date, and it's going to be accelerated by this AI super cycle.

這與 08 年和 01 年有點不同。我們並沒有完全擁有我們正在退出的那種巨大的巨型週期。而我——這也讓我對未來充滿信心，我們真正看到的是客戶正在吸收他們購買的大量技術。我相信，這即將結束。我不能給你確切的日期，它會被這個 AI 超級週期加速。

Your next question comes from the line of Brent Bracelin with Piper Sandler.

你的下一個問題來自 Brent Bracelin 和 Piper Sandler 的台詞。

I wanted to circle back to the generative AI discussion, if we could. I totally understand how large enterprises are turning to Microsoft, given the productivity tools and suite that they have, but as you start to engage with customers, what's resonating relative to the Salesforce Gen AI journey? Is it the data layer and Customer 360 message resonating? Is it the app layer around sales automation functionality that you're going to offer? Just double quick on what customers are coming to Salesforce and engaging the you around some of the new things that we'll hear about it sounds like in June.

如果可以的話，我想回到生成人工智能的討論上。我完全理解大型企業是如何轉向微軟的，考慮到他們擁有的生產力工具和套件，但是當你開始與客戶互動時，與 Salesforce Gen AI 之旅相關的是什麼？是數據層和 Customer 360 消息產生共鳴嗎？您要提供的是圍繞銷售自動化功能的應用程序層嗎？只需加倍了解 Salesforce 的客戶，並讓您了解我們將在 6 月份聽到的一些新事物。

Well, I think that when you look at our artificial intelligence strategy, which we're talking to the largest, most important companies and governments in the world, it has to be architected around security. It has to be architected around compliance, around trust. It has to be architected around governance. And this is very important. And of course, we're also architecting it around being open. That is we're working with many AI companies to provide the best solutions for our company.

好吧，我認為當你看一下我們正在與世界上最大、最重要的公司和政府討論的人工智能戰略時，它必須圍繞安全來構建。它必須圍繞合規性和信任來構建。它必須圍繞治理來構建。這非常重要。當然，我們也在圍繞開放來構建它。那就是我們正在與許多人工智能公司合作，為我們公司提供最好的解決方案。

Of course, we have a tremendous relationship with Open AI. We also just invested in Anthropic. I hear many of these companies. But I think, ultimately, this is going to be a solution that enterprise customers are going to come in and make sure that their data is protected. And it's also protected down at the user level.

當然，我們與 Open AI 有著密切的關係。我們也剛剛投資了 Anthropic。我聽說過很多這樣的公司。但我認為，最終，這將成為企業客戶進入並確保他們的數據受到保護的解決方案。而且它還在用戶級別受到保護。

And Srini, do you want to come in and talk about exactly what we're doing to make sure that we're delivering the best possible solutions for our customers for AI?

Srini，你想進來談談我們正在做什麼，以確保我們為我們的客戶提供最好的 AI 解決方案嗎？

Yes, Marc. So I think I met about 70 customers in the last quarter. And like Marc was saying, the only conversation everybody is interested in is on AI. And while everybody understands the use cases, they're really worried about trust. And what they are looking for us is guidance on how to solve that.

是的，馬克。所以我想我在上個季度遇到了大約 70 位客戶。就像 Marc 所說的，每個人唯一感興趣的話題就是 AI。雖然每個人都了解用例，但他們真的很擔心信任。他們正在尋找我們的是如何解決這個問題的指導。

For example, so we are doing a lot of things as the basic security level, like we are really doing tenant level isolation coupled with 0 retention architecture, the LLM level. So the LLM doesn't remember any of the data. Along with that, they -- for them to use these use cases, they want to have -- they have a lot of these compliances like GDPR, ISO, SOC, Quadrant, they want to ensure that those compliances are still valid, and we're going to solve it for that. In addition, the big worry everybody has is people have heard about hallucinations, toxicity, bias, this is what we call model trust. We have a lot of innovation around how to ground the data on 360 data, which is a huge advantage we have. And we are able to do a lot of things at that level.

例如，我們正在做很多基本安全級別的事情，比如我們真的在做租戶級別隔離加上 0 保留架構，即 LLM 級別。所以 LLM 不記得任何數據。除此之外，他們——為了讓他們使用這些用例，他們想要——他們有很多這樣的合規性，比如 GDPR、ISO、SOC、Quadrant，他們想確保這些合規性仍然有效，我們將為此解決它。此外，每個人最大的擔憂是人們聽說過幻覺、毒性、偏見，這就是我們所說的模型信任。我們有很多創新是圍繞如何將數據建立在 360 數據之上的，這是我們擁有的一個巨大優勢。我們能夠在那個級別上做很多事情。

And then the thing, which I think Marc hinted at, which is LLMs are not like a database. These intra-enterprise trust, even once you have an LLM, you can't open the data to everybody in the company. So you need ability to do this -- who can access this data, how is it doing both before the query and after the query, we have to build that. And then we have to be not only open, but also optimized. We are running an open -- the way we'll run is we'll run like [we're top of it] because one of the things everybody has to watch out is it's great, but what about the cost to serve, not all models are equal.

然後，我認為 Marc 暗示過，LLM 不像數據庫。這些企業內部的信任，即使你有了LLM，你也不能把數據公開給公司裡的每個人。所以你需要有能力做到這一點——誰可以訪問這些數據，它在查詢之前和查詢之後的表現如何，我們必須構建它。然後我們不僅要開放，還要優化。我們正在運行一個開放的——我們將運行的方式是我們將像 [我們處於領先地位] 一樣運行，因為每個人都必須注意的一件事是它很棒，但服務成本如何，而不是所有模型都是平等的。

So we are going to run this and pick very -- we are going to pick a very cost-optimized curve, so the value is very high. And our Salesforce AI research has a lot of sales for -- state-of-the-art models and industry cases, which we are optimizing to run at very low cost and high value.

所以我們要運行這個並選擇非常 - 我們將選擇一個非常成本優化的曲線，所以價值非常高。我們的 Salesforce AI 研究有很多銷售——最先進的模型和行業案例，我們正在優化它們以非常低的成本和高價值運行。

Add to that, we've got the trades platform, which allows low code, high code and many other things -- and we're going to optimize sort of jobs to be done for each industry and jobs. That's really what they're looking for because they have been using our AI platform. Like Marc mentioned, we already do 1 trillion transactions per day. And by the way, the Data Cloud, just in a month, we are importing more than 7 trillion reports into the data layer, so which is a very powerful asset we have. So coupled with all of this is what they are looking for guidance and how we think we can deliver significant value to our customers.

除此之外，我們還有交易平台，它允許低代碼、高代碼和許多其他東西——我們將優化每個行業和工作要做的工作種類。這正是他們正在尋找的，因為他們一直在使用我們的 AI 平台。正如 Marc 提到的，我們每天已經進行了 1 萬億筆交易。順便說一句，數據云，僅在一個月內，我們就將超過 7 萬億份報告導入數據層，這是我們擁有的一項非常強大的資產。因此，與所有這些相結合，他們正在尋找指導，以及我們認為我們可以如何為客戶提供重要價值。

Srini, I want to ask you a question. In January, you published a paper in nature from your research team, which was called Large Language Models, generating functional protein sequences across diverse families. And you really showed something amazing, which was that deep learning language models have shown this incredible promise that you just articulated in various biotechnological applications, including protein design, engineering. And you also described very well one of our models that we've created internally, ProGen, which was a language model that can generate protein sequences with predictable function across large protein families. I was very impressed with that. And the entire research team deserves a huge amount of congratulations.

斯里尼，我想問你一個問題。一月份，您的研究團隊在自然界發表了一篇論文，名為大型語言模型，生成跨不同家族的功能性蛋白質序列。你真的展示了一些驚人的東西，那就是深度學習語言模型已經展示了你剛剛在各種生物技術應用中表達的令人難以置信的承諾，包括蛋白質設計、工程。你還很好地描述了我們內部創建的一個模型 ProGen，它是一種語言模型，可以生成跨大型蛋白質家族具有可預測功能的蛋白質序列。我對此印象深刻。整個研究團隊值得熱烈祝賀。

So when you look at that, especially generating dramatically and semantically correct natural language sentences for diverse topics or how you're going to use that inside our platform against other models that you're seeing like Llama, OpenAI's model, Anthropic and others, when will Salesforce use our own models like CoGen, ProGen, tcode, our Blitz model, when will we use an outside commercial model like an OpenAI or an Anthropic? And when will we go to an open source model like we've seen emerge so many of those, including like Llama?

因此，當你看到這一點時，尤其是為不同的主題生成顯著且語義正確的自然語言句子，或者你將如何在我們的平台內使用它來對抗你看到的其他模型，如 Llama、OpenAI 的模型、Anthropic 等，當Salesforce 會使用我們自己的模型，例如 CoGen、ProGen、tcode、我們的 Blitz 模型，我們什麼時候會使用外部商業模型，例如 OpenAI 或 Anthropic？我們什麼時候才能採用開源模型，就像我們已經看到的那樣，包括 Llama？

Yes. I think you hinted something very important. I think as you know, Marc, we have -- our AI research team is one of the best-in-class model, state-of-the-art models from different areas. The way we are thinking of it is like anything else, where the world is going to go, which we strongly believe is, is going to be multiple models. And depending on the use case, you will pick the right models, which will provide you the value at the lowest cost.

是的。我認為你暗示了一些非常重要的事情。我想你知道，馬克，我們有——我們的人工智能研究團隊是一流的模型之一，來自不同領域的最先進的模型。我們對它的思考方式與其他任何事情一樣，我們堅信世界將走向何方，這將是多種模式。根據用例，您將選擇合適的模型，以最低的成本為您提供價值。

Where we have to run with highly regulated industries, where the data cannot leave the trust boundary or where we have significant advantage, where we can train on industry-specific data or Salesforce-specific 360-specific data, like, for example, our FX model are helping our customers implement our flow, we will use our internal model. Where we need more generated image models or something, where it needs public image databases, we may use a Coherent, Anthropic or OpenAI.

我們必須與高度監管的行業合作，數據不能離開信任邊界，或者我們有顯著優勢，我們可以訓練行業特定數據或 Salesforce 特定 360 特定數據，例如，我們的 FX模型正在幫助我們的客戶實施我們的流程，我們將使用我們的內部模型。在我們需要更多生成的圖像模型或其他東西的地方，在需要公共圖像數據庫的地方，我們可以使用 Coherent、Anthropic 或 OpenAI。

It depends on the use case and which is why, at a given request, a secure trusted gateway will decide smartly, which is the best use case, which is the model, and we always keep running the [total main], which is what I mean.

這取決於用例，這就是為什麼在給定的請求下，安全可信網關會明智地決定，哪個是最好的用例，哪個是模型，我們總是繼續運行 [total main]，這是什麼我是說。

So today, one particular model may be good. Tomorrow, something else will come. And we'll behind -- the team flip it, but our customers don't need to know that. We will handle all of it. We'll handle the model trust. We'll handle all the compliances and all behind the scenes. And this is always what we promise to our customers, we'll always future-proof. That's the Salesforce promise to our customers so that they can focus on the business use case.

所以今天，一個特定的模型可能是好的。明天，會有別的事情發生。我們會落後 - 團隊翻轉它，但我們的客戶不需要知道這一點。我們會處理所有這一切。我們將處理模型信任。我們將在幕後處理所有合規事宜。這始終是我們對客戶的承諾，我們將永遠面向未來。這是 Salesforce 對我們客戶的承諾，以便他們可以專注於業務用例。

So just one last follow-up question. You've described very well the GPT trust layer, which I think is going to be a significant amount of value added that we're going to provide to our customers that's going to be quite amazing. And then you develop these specific grounding techniques, which are going to allow us to keep our customers' data safe and not be consumed by these voracious large language models, which are so hungry for all of our customers' data. What is going to be the key to actually delivering this now across regulated industries?

所以只有最後一個後續問題。你已經很好地描述了 GPT 信任層，我認為這將是我們將提供給客戶的大量附加值，這將是非常驚人的。然後你開發這些特定的基礎技術，這將使我們能夠保護我們客戶的數據安全，而不是被這些貪婪的大型語言模型所消耗，這些模型非常渴望我們所有客戶的數據。現在在受監管的行業中真正實現這一目標的關鍵是什麼？

I think the key is innovations we are doing, which people will see starting next month, is around what we call ground generation and grounding. These are techniques, which we'll have to do, but it will work only because we have all of this as based on underlying data. We have the Data Cloud, where we have all the 360 data, which is there. So we're able to ground these models and do it.

我認為關鍵是我們正在做的創新，人們將從下個月開始看到，圍繞我們所謂的地面生成和接地。這些是我們必須做的技術，但它之所以有效，只是因為我們擁有所有這些基於基礎數據的技術。我們擁有數據云，我們擁有所有 360 度數據。所以我們能夠將這些模型作為基礎並做到這一點。

So there are a lot of other techniques which are very technical, which we put it on our block. But that's the innovation that we're doing. And you have to remember that Salesforce also is a metadata model. So we have a semantic understanding of what our customers are trying to do. We're going to leverage the Metadata platform and do this grounding automatically for our customers, of course, while keeping the trust. That's the base line.

所以還有很多其他技術性很強的技術，我們把它們放在我們的塊上。但這就是我們正在做的創新。你必須記住，Salesforce 也是一個元數據模型。所以我們對我們的客戶試圖做什麼有語義上的理解。我們將利用 Metadata 平台並自動為我們的客戶做這件事，當然，同時保持信任。這是底線。

Absolutely. Thank you so much, Srini.

絕對地。非常感謝，斯里尼。

Your next question comes from the line of Raimo Lenschow with Barclays.

你的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Question for Amy and Brian maybe more. The improvement in profitability or the raise guidance for profitability and cash is that all timing? Can you talk a little bit about that? Is it just timing? Or are there other factors we should consider here?

艾米和布賴恩的問題可能更多。盈利能力的改善或盈利能力和現金的提高指導是所有時機嗎？你能談談嗎？只是時機嗎？還是我們應該在這裡考慮其他因素？

So Raimo, why don't I start then I can turn it over to Brian for a little bit more color. So in terms of the great Q1 that we just saw, really pleased to see us coming in at 27.6% and also really pleased about the 28% -- the race to 28% for the full year.

所以 Raimo，為什麼我不開始，然後我可以把它交給 Brian 來增加一點顏色。因此，就我們剛剛看到的出色的第一季度而言，我們真的很高興看到我們以 27.6% 的成績進入市場，也對 28% 的成績感到非常高興——全年達到 28% 的比賽。

What really drove the 27.6 was 2 things. It were the actions that we took that we announced in January with the restructuring. Executing on that as well as having a very disciplined reinvestment strategy, and that led to that. And that's also where we're going to see this going through the rest of the year, driving the expansion 28% and then also putting us on track for the 30% margin in Q1 of next year.

真正推動 27.6 的是兩件事。這是我們在 1 月份宣布重組時採取的行動。執行這一點以及有一個非常有紀律的再投資策略，這導致了這一點。這也是我們將在今年餘下時間看到這種情況的地方，推動擴張 28%，然後也讓我們有望在明年第一季度實現 30% 的利潤率。

As I look through overall at transformation, I would really divide it into 2 stages. Benefits that we're getting from that initial transformation, and again, that's what you're seeing in Q1 and this year. And then the second stage, which is really as we've been going through this comprehensive operating and go-to-market review, that review is going to enable the second phase of our transformation. And that's something that's going to be ongoing and long term over the next few years. You'll see benefits to our margin in outer years beyond FY '24. Brian, anything you would add?

當我從整體上看轉型時，我會將其分為兩個階段。我們從最初的轉型中獲得的好處，這也是你在第一季度和今年看到的。然後是第二階段，也就是我們一直在進行全面的運營和上市審查，該審查將使我們轉型的第二階段成為可能。在接下來的幾年裡，這將是持續和長期的事情。在 24 財年之後的外部年份，您會看到我們的利潤率有所提高。布賴恩，你有什麼要補充的嗎？

Yes, thanks for the question. When we think about longer-term structures, we obviously took the action in Q1. But longer term, we're looking at things like how do we leverage comp plan redesign to drive better efficiencies in our organization going forward? How do we continue to look at self-serve at the low end of the market to drive better efficiencies in our organization? So resellers, as a potential investment that we'll make in emerging markets, is long-term leverage on the efficiency gains.

是的，謝謝你的提問。當我們考慮長期結構時，我們顯然在第一季度採取了行動。但從長遠來看，我們正在研究如何利用重新設計的薪酬計劃來提高我們組織的效率？我們如何繼續關注低端市場的自助服務，以提高我們組織的效率？因此，作為我們將在新興市場進行的潛在投資，經銷商是提高效率的長期槓桿。

So lots of things that we're doing that will be in sort of the Phase 2 oriented around process improvement and systems improvement. And again, as I mentioned, top plan design that will drive better efficiencies in the organization.

因此，我們正在做的很多事情將在第 2 階段以流程改進和系統改進為導向。同樣，正如我提到的，頂層計劃設計將推動組織提高效率。

Your next question will come -- is from Karl Keirstead with UBS.

您的下一個問題將來自瑞銀的 Karl Keirstead。

Okay. Great. I'll direct this to Amy as well. Amy, congrats on that margin improvement. I've got a 2-parter both related to margins. First, what is the timing of the receipt of that Bain operational review that might ostensibly kick off the second phase of cost cutting?

好的。偉大的。我也會把它轉給艾米。艾米，祝賀利潤率提高。我有一個 2-parter 都與邊距有關。首先，表面上可能啟動第二階段成本削減的貝恩運營審查的收到時間是什麼時候？

And then secondly, you and Brian talked about this reinvestment in R&D and investing heavily around AI. I'm wondering if those planned investments are greater than you anticipated when you initially set the guidance 3 months ago, such that you need to run a little bit harder on OpEx management to offset it and keep delivering on your stated margin targets.

其次，你和布賴恩談到了對研發的再投資以及圍繞人工智能的大量投資。我想知道這些計劃的投資是否比您在 3 個月前最初設定指導時預期的要多，這樣您就需要在 OpEx 管理上更加努力地運行以抵消它並繼續實現您規定的利潤率目標。

Great. Thanks, Karl. So first on the timing. As I mentioned, we've been doing this end-to-end comprehensive operating and go-to-market review. The entire company has been involved in that. There's really no stone unturned. We're getting close to the end of that process, and then we will be moving into the implementation. You'll be hearing more about that in future quarters.

偉大的。謝謝，卡爾。所以首先是時間。正如我提到的，我們一直在進行這種端到端的綜合運營和上市審查。整個公司都參與其中。真的是千方百計。我們接近該流程的尾聲，然後我們將進入實施階段。在未來的幾個季度中，您會聽到更多相關信息。

Turning to reinvestment. We are keeping a very close eye on reinvestment, very excited particularly about artificial intelligence, much of what Srini has been talking to you about. I don't view this as a greater investment from what we were looking at earlier. We're really going along with our current plans. We are looking at operating expenses management, and we're looking at it seriously every day, but that's not something that has changed.

轉向再投資。我們正在密切關注再投資，特別是對人工智能非常興奮，這是 Srini 一直在與您談論的大部分內容。我不認為這是我們之前看到的更大的投資。我們真的在按照我們目前的計劃進行。我們正在研究運營費用管理，我們每天都在認真研究它，但這並沒有改變。

Thanks, Karl. Operator, we'll move to our last question now, please.

謝謝，卡爾。接線員，我們現在轉到最後一個問題。

Our last question comes from the line of Kash Rangan with Goldman Sachs.

我們的最後一個問題來自 Kash Rangan 與高盛的合作。

Congratulations on putting up terrific operational results, good cash flow, good margins, et cetera. Marc, you talked about a super cycle of buying in technology in the years ahead. Can you just parse for us, if you don't mind, what is new about generative AI as far as Salesforce's opportunities are concerned, netting out against what Einstein has been able to accomplish for you -- for the company? And how does it show up in the product in terms of productivity? What are the scenarios by which customers can experience this amazing productivity? And how can you charge more for delivering that kind of value?

祝賀您取得了出色的經營業績、良好的現金流、良好的利潤率等。馬克，你談到了未來幾年購買技術的超級週期。如果您不介意的話，您能否為我們解析一下，就 Salesforce 的機會而言，生成式 AI 有何新意，並與 Einstein 為您——為公司所取得的成就進行比較？它在生產力方面如何體現在產品中？客戶可以在哪些場景下體驗到這種驚人的生產力？你怎麼能為提供這種價值收取更多費用呢？

Well, thanks, Kash, for giving me the opportunity to talk about our AI vision, and I'm also going to ask Srini again to fill in some of the details. But I think it started to occur to me -- I think folks know, I have -- my neighbor Sam Altman is the CEO of OpenAI, and I went over to his house for dinner, and it was a great conversation as it always is with him. And he had -- he said, "Oh, just hold on one second, Marc, I want to get my laptop." And he brought his laptop out and gave me some demonstrations of advanced technologies that are not appropriate for the call.

好吧，謝謝 Kash，讓我有機會談論我們的 AI 願景，我也將再次請 Srini 補充一些細節。但我想我開始想到了——我想人們知道，我有——我的鄰居山姆奧特曼是 OpenAI 的首席執行官，我去他家吃晚飯，這是一次很棒的談話，一如既往和他一起。他有——他說，“哦，等一下，馬克，我想拿我的筆記本電腦。”他拿出他的筆記本電腦，向我展示了一些不適合通話的先進技術。

But I did notice that there was only one application that he was using on his laptop and that was Slack. And the powerful part about that was I realized that everything from day 1 at OpenAI have been in Slack. And as we kind of brainstorm and talked about -- of course, he was paying a Slack user fee and on and on, and he's a great Slack customer. We've done a video about them, it's on YouTube.

但我確實注意到他在筆記本電腦上只使用了一個應用程序，那就是 Slack。最重要的是，我意識到從 OpenAI 的第一天起，一切都在 Slack 中。正如我們集思廣益和談論的那樣——當然，他支付了 Slack 用戶費等等，他是 Slack 的一個偉大客戶。我們製作了一段關於他們的視頻，它在 YouTube 上。

But I realize that taking an LLM and embedding it inside Slack, well, maybe Slack will wake up. I mean there is so much data in Slack, I wonder if it could tell him what are the opportunities in OpenAI. What are the conflicts, what are the conversations, what should be his prioritization. What is the big product that got repressed that he never knew about.

但我意識到，獲得法學碩士學位並將其嵌入到 Slack 中，嗯，也許 Slack 會醒來。我的意思是 Slack 裡有這麼多數據，我想知道它是否可以告訴他 OpenAI 中有哪些機會。衝突是什麼，對話是什麼，他應該優先考慮什麼。什麼是他一直不知道的被打壓的大貨。

And I realized in my own version of Slack at Salesforce, I have over 95 million Slack messages, and these are all open messages. I'm not talking about closed messaging or direct messaging or secure messaging between employees. I'm talking about the open framework that's going on inside Salesforce and with so many of our customers.

我在 Salesforce 的 Slack 版本中意識到，我有超過 9500 萬條 Slack 消息，這些都是公開的消息。我不是在談論員工之間的封閉式消息傳遞或直接消息傳遞或安全消息傳遞。我說的是 Salesforce 內部以及我們眾多客戶正在使用的開放框架。

And then I realized, wow, I think Slack could wake up, and it could become a tremendous asset with an LLM consuming all that data and driving it. And then, of course, the idea is, is that is a new version of Slack. Not only do you have the free version of Slack, not only do you have the per user version of Slack, but then you have the additional LLM version of Slack. And for each one of our products, in every single one of our categories, there's that opportunity to upsell and cross-sell into the next version of generative AI.

然後我意識到，哇，我認為 Slack 可以醒來，它可以成為一個巨大的資產，LLM 可以消耗所有數據並驅動它。然後，當然，這個想法是，這是一個新版本的 Slack。您不僅擁有免費版本的 Slack，不僅擁有每個用戶版本的 Slack，而且還擁有額外的 LLM 版本的 Slack。對於我們的每一種產品，在我們的每一個類別中，都有機會追加銷售和交叉銷售到下一版本的生成人工智能。

Not just with Slack, but you can also imagine, for example, even with Salesforce, the ability as we're going to see in June, that many of our trailblazers are amazing low-code, no-code trailblazers, but soon they'll have the ability to tap into our LLMs like ProGen and CoGen that have the ability to code for them automatically. They aren't coders. They didn't graduate computer science degrees. And if they need to write a sophisticated Apex code or other code, it can be a challenge for them, but because you know what is there only 8 million or 10 million coders in the whole world. But now with LLMs, everybody can start to code. That's an amazing productivity and augmentation of everybody's skill set.

不僅僅是 Slack，你也可以想像，例如，即使有了 Salesforce，我們將在 6 月看到的能力，我們的許多開拓者都是令人驚嘆的低代碼、無代碼開拓者，但很快他們您將能夠利用我們的 LLM，例如 ProGen 和 CoGen，這些 LLM 能夠自動為他們編碼。他們不是編碼員。他們沒有獲得計算機科學學位。如果他們需要編寫複雜的 Apex 代碼或其他代碼，這對他們來說可能是一個挑戰，但因為你知道全世界只有 800 萬或 1000 萬編碼員。但是現在有了 LLM，每個人都可以開始編碼。這是一個驚人的生產力和每個人的技能組合的增強。

And that's a great way to look at what could happen, for example, with our core products, but even with Tableau, which has tremendous programmatic engine as well or even MuleSoft, which is a highly programmatic product that then coupled with an LLM can have the ability to go forward. But of course, those LLMs are highly trained models for those specific types of code. And then that is something that we would add on either through partnership or through our own LLM, as Srini described. It's another layer of value that we can provide to our customers.

這是查看可能發生的事情的好方法，例如，我們的核心產品，但即使是 Tableau，它也具有強大的程序化引擎，甚至是 MuleSoft，這是一個高度程序化的產品，然後與 LLM 相結合前進的能力。但是，當然，這些 LLM 是針對那些特定類型的代碼訓練有素的模型。然後，正如 Srini 所描述的那樣，我們將通過合作夥伴關係或我們自己的法學碩士來補充這一點。這是我們可以為客戶提供的另一層價值。

In all cases, customers are going to be more productive. They're going to be more automated, and they're going to be more intelligent. And as we look at some of the examples that we've given like at the New York World Tour, you saw our Marketing Cloud do something very cool that it couldn't do even just 6 months ago. It segmented the database on its own. It wrote an e-mail on its own. Of course, it required editing, and it also built a landing page on its own. That was amazing.

在所有情況下，客戶的工作效率都會提高。它們將變得更加自動化，而且它們將變得更加智能。當我們查看我們在紐約世界巡迴賽中給出的一些示例時，您會看到我們的營銷雲做了一些非常酷的事情，即使在 6 個月前它也做不到。它自己對數據庫進行了分段。它自己寫了一封電子郵件。當然，它需要編輯，它還自己建立了一個登陸頁面。那太精彩了。

Or as we saw at the Tableau conference, we saw Tableau being able to create its own visions or visualizations that was incredible. And what we saw at our Trailhead DX, we saw Einstein GPT which started to do these amazing next-generation things.

或者正如我們在 Tableau 會議上看到的那樣，我們看到 Tableau 能夠創建自己的願景或可視化效果，這令人難以置信。我們在 Trailhead DX 上看到的是 Einstein GPT，它開始做這些令人驚嘆的下一代事情。

And I think in each of these areas, we can offer more value, but we must do it in the auspices of trust, data integrity and governance. And that is what we have been working on now for a considerable amount of time. Of course, we've led -- we have always wanted to be the #1 AI CRM. And we are, if you look at Einstein's transaction level, I think that that's enough evidence right there. But I think this idea of generative AI, this starts to reconceptualize every product. And we will start to build and develop not only extensions to all of our current products but entirely new products as well. And we have a lot of exciting ideas of things that we can do to help our customers connect with their customers in a new way using generative AI.

我認為在這些領域中的每一個領域，我們都可以提供更多價值，但我們必須在信任、數據完整性和治理的支持下做到這一點。這就是我們現在一直在努力的相當長的時間。當然，我們一直處於領先地位——我們一直想成為排名第一的 AI CRM。我們是，如果你看看愛因斯坦的交易水平，我認為這已經足夠了。但我認為這種生成人工智能的想法，開始重新定義每一種產品。我們不僅會開始構建和開發所有當前產品的擴展，還會構建和開發全新的產品。我們有很多令人興奮的想法，我們可以做這些事情來幫助我們的客戶使用生成人工智能以一種新的方式與他們的客戶建立聯繫。

Srini, do you want to come in and talk about that?

Srini，你想進來談談這個嗎？

Thanks, Marc. So I think the way I see it is this AI technologies are a continuum that is predictive, then they generate, and the real long-term goal is autonomous. The initial version of the generative AI will be more in terms of assistance. And like Marc was saying, we are seeing like the most common use case everybody understands implicitly is self-service bots or in the call center or agent-assistant assistance, which I think really helps productivity.

謝謝，馬克。所以我認為我的看法是，人工智能技術是一個連續體，可以預測，然後生成，真正的長期目標是自主的。生成人工智能的初始版本將更多地在輔助方面。就像馬克所說的那樣，我們看到每個人都隱含地理解的最常見用例是自助服務機器人或呼叫中心或代理助理協助，我認為這確實有助於提高生產力。

But the other use cases, which we are going to see, and in fact, I have rolled out our own code elements in our engineering org and we are already seeing minimum 20% productivity. And in both cases...

但是我們將要看到的其他用例，事實上，我已經在我們的工程組織中推出了我們自己的代碼元素，我們已經看到至少 20% 的生產力。在這兩種情況下......

Well, that's a very key point. Is it that you're seeing a 30% productivity increase in your own engineers using our own?

嗯，這是一個非常關鍵的點。您是否看到您自己的工程師使用我們自己的產品提高了 30% 的工作效率？

20%, we are seeing minimum. In some cases, up to 30%. Now a lot of our customers are asking the same. We are going to roll Einstein GPT for our developers in the ecosystem, which will not only help not only the local developers bridge the gap, where there's a talent gap but also reduce the cost of implementations for a lot of people. So there's a lot of value.

20%，我們看到的是最低值。在某些情況下，高達 30%。現在我們的很多客戶都在問同樣的問題。我們將為生態系統中的開發人員推出 Einstein GPT，這不僅可以幫助本地開發人員彌合人才缺口，還可以降低很多人的實施成本。所以有很多價值。

This assistant model is where we'll see a lot of uptick. And then I think the fully autonomous cases, for example, in our own internal use cases with our models, we are able to detect 60% of instance and auto remediate. That requires a little bit more fine-tuning and we'll have to work with specific customers to get to that level of model performance. So I see this is just the start of this cut. The assistant model is the initial thing to build trust and a human in the loop and validate it. And then as the models get better and better, we'll keep taking use cases where we can fully automate it.

這個助手模型是我們會看到很多提升的地方。然後我認為完全自主的案例，例如，在我們自己的模型內部用例中，我們能夠檢測到 60% 的實例並自動修復。這需要更多的微調，我們必須與特定客戶合作才能達到該模型性能水平。所以我看到這只是這次剪輯的開始。助手模型是建立信任和循環中的人並驗證它的最初的東西。然後隨著模型變得越來越好，我們將繼續採用可以完全自動化的用例。

And address this one issue that a lot of customers come in like they did yesterday, and they tell us they think they're just going to take all of their data, all their customer data, all of their information and put it into an LLM and create a corporate knowledge base. And it's going to be one amalgamated database. Why is that a false prophecy?

並解決這個問題，許多客戶像昨天一樣進來，他們告訴我們他們認為他們將獲取所有數據，所有客戶數據，所有信息並將其放入 LLM並創建企業知識庫。它將成為一個合併的數據庫。為什麼這是一個錯誤的預言？

Because even today, any example you see, even though we have hundreds of Slack channels, there are a lot of specific Slack channels, which only you want access to. You don't want that. LLM doesn't know. There is no concept of -- it combines all this information. So unless you put the layer both before who can access the data and then when it generates response, what he can do you don't want one wealth manager to centrally generate a report, an account report where you're mixing customers' balances.

因為即使在今天，你看到的任何例子，即使我們有數百個 Slack 頻道，也有很多特定的 Slack 頻道，只有你想訪問。你不想要那個。 LLM不知道。沒有概念——它結合了所有這些信息。因此，除非你把這個層放在誰可以訪問數據之前，然後在它生成響應之前，他可以做什麼，你不希望一個財富經理集中生成報告，一個你混合客戶餘額的賬戶報告。

So there are a lot of trust issues we have to solve. So LLMs are good for a lot of very creative, generative use cases. Initially, where it's public data that everybody can use it, those are use cases. I think there is enough of low-hanging fruit in the initial phases with assistant model, which we'll solve. The really complex automated cases, the role level, record level sharing, we have a lot of techniques, which we are developing, which we will do. It's also a research area, too. That one, I think we should be tempered with expectations. But there's enough of, like I said, the develop, for example, I gave product example there's enough opportunity which we'll get.

因此，我們必須解決很多信任問題。所以 LLM 適合許多非常有創意的、生成性的用例。最初，它是每個人都可以使用的公共數據，這些都是用例。我認為在輔助模型的初始階段有足夠的容易實現的成果，我們將解決這些問題。真正複雜的自動化案例，角色級別，記錄級別共享，我們有很多技術，我們正在開發，我們將這樣做。這也是一個研究領域。那個，我認為我們應該對期望有所緩和。但是，就像我說的那樣，開發已經足夠了，例如，我給出了產品示例，我們將獲得足夠的機會。

Well, we're really excited to show all of this technology at our AI Day on June 12 in New York City. And then also when we get to Dreamforce GPT, we're going to have an incredible demonstration of this technology.

好吧，我們真的很高興能夠在 6 月 12 日於紐約市舉行的人工智能日展示所有這些技術。然後當我們進入 Dreamforce GPT 時，我們將對這項技術進行令人難以置信的演示。

So with that, we want to thank everyone for joining us today, and we look forward to seeing everyone over the coming weeks. Have a great one.

因此，我們要感謝大家今天加入我們，我們期待在未來幾週內見到大家。有一個偉大的。

This concludes today's conference call. You may now disconnect.

今天的電話會議到此結束。您現在可以斷開連接。