高知特 (CTSH) 2025 Q3 法說會逐字稿

Ladies and gentlemen, welcome to the Cognizant Technology Solutions third quarter 2025 earnings conference call. (Operator Instructions) I would now like to turn the conference over to Mr. Tyler Scott, Vice President, Investor Relations. Please go ahead, sir.

女士們、先生們，歡迎參加 Cognizant Technology Solutions 2025 年第三季財報電話會議。（操作員指示）現在我將會議交給投資者關係副總裁泰勒·斯科特先生。請繼續，先生。

Thank you, operator, and good morning, everyone. Welcome to Cognizant's third quarter 2025 earnings call. I'm joined today by Ravi Kumar, Chief Executive Officer; and Jatin Dalal, Chief Financial Officer.

謝謝接線員，大家早安。歡迎參加 Cognizant 2025 年第三季財報電話會議。今天與我一同出席的有執行長 Ravi Kumar 和財務長 Jatin Dalal。

By now, you should have received a copy of the earnings release and investor supplement for our third quarter results. If you have not, copies are available on our website, cognizant.com. Before we begin, I would like to remind you that some of the comments made on today's call and some of the responses to your questions may contain forward-looking statements.

現在，您應該已經收到我們第三季業績的收益報告和投資者補充資料。如果您還沒有收到，可以從我們的網站 cognizant.com 取得副本。在開始之前，我想提醒各位，今天電話會議上的一些評論以及對您提問的一些回答可能包含前瞻性陳述。

These statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Additionally, during our call today, we will reference certain non-GAAP financial measures that we believe provide useful information to our investors.

這些聲明受到公司獲利報告和向美國證券交易委員會提交的其他文件中所述的風險和不確定性的影響。此外，在今天的電話會議中，我們將提及一些我們認為能夠為投資者提供有用資訊的非GAAP財務指標。

Reconciliations of non-GAAP financial measures where appropriate to the corresponding GAAP measures can be found in the company's earnings release and other filings with the SEC.

公司獲利報告和向美國證券交易委員會提交的其他文件中，可以找到非GAAP財務指標與對應GAAP指標的調節表。

With that, over to you, Ravi.

那麼，接下來就交給你了，拉維。

Thank you, Tyler, and good morning, everyone. Thank you for joining us. We are pleased to report another industry-leading performance in the third quarter of 2025 as revenue growth and adjusted operating margin again outpaced our expectations.

謝謝你，泰勒，大家早安。感謝您的參與。我們很高興地宣布，2025 年第三季我們再次取得了業界領先的業績，營收成長和調整後的營業利潤率再次超出了我們的預期。

Our results reflect the momentum we have built over the past 2.5 years, helping clients embrace AI. Our investments in platforms, intellectual property, partnerships, and in upskilling our people are evolving Cognizant into an AI builder capable of scaling agentic AI across the enterprise.

我們的成果反映了我們在過去 2.5 年所取得的進展，幫助客戶擁抱人工智慧。我們在平台、智慧財產權、合作夥伴關係以及員工技能提升方面的投資，正在將 Cognizant 發展成為一家人工智慧建構商，能夠在企業範圍內擴展智慧人工智慧。

As AI infrastructure expands, our clients increasingly need support from partners who can help them move from experimentation to enterprise-wide adoption with speed, precision and trust.

隨著人工智慧基礎設施的擴展，我們的客戶越來越需要合作夥伴的支持，以幫助他們快速、精準、可靠地從實驗階段過渡到企業範圍內的全面採用。

Turning to third quarter highlights. Revenue grew 6.5% year over year in constant currency to $5.4 billion. All four of our operating segments grew revenue organically year over year. This breadth of performance across industries and geographies reflects the strength and resilience of our portfolio capabilities and delivery model. This is the fifth consecutive quarter of year-over-year organic revenue growth.

接下來回顧第三節精彩瞬間。以固定匯率計算，營收年增 6.5%，達到 54 億美元。我們所有四個營運部門的收入都實現了同比增長。這種跨行業和跨地域的廣泛業績反映了我們產品組合能力和交付模式的實力和韌性。這是連續第五個季度實現同比增長的有機收入。

Our strongest sequential organic growth since 2022 and another podium finish to our peer group's Winner Circle.

自 2022 年以來，我們實現了最強勁的連續有機成長，並在同行組的優勝者圈中再次名列前茅。

We signed six large deals, each with TCV of $100 million or more, bringing our year-to-date total to 16. Trailing 12 months bookings is up 5% year over year and year to date the TCV of our large deals is up from the prior year period. We are focused on converting value from AI across our 3,500 early AI engagements and embracing AI in the delivery of our services and to drive internal transformation.

我們簽署了六項大合同，每項合約的總合約價值 (TCV) 都達到或超過 1 億美元，使我們今年迄今為止的合約總數達到 16 項。過去 12 個月的預訂量年增 5%，今年迄今為止，我們大宗交易的總合約價值 (TCV) 也比去年同期有所增長。我們專注於在 3,500 個早期人工智慧專案中實現人工智慧的價值轉化，並在提供服務的過程中採用人工智慧，以推動內部轉型。

As we do this, we are also increasing our fixed bid transaction and outcome-based services mix. And we are beginning to see trends of nonlinearity emerge.

同時，我們也在增加固定報價交易和基於結果的服務組合。我們開始看到非線性趨勢的出現。

For example, on a trailing 12-month basis, revenue per employee rose 8% year over year, while adjusting operating margin income per employee grew 10%. As we continue to scale our IP and platforms, we expect more examples of non-linear AI-led growth to emerge.

例如，過去 12 個月，每位員工的收入年增 8%，而調整後的每位員工的營業利潤率則成長了 10%。隨著我們不斷擴大知識產權和平台規模，我們預計會出現更多非線性人工智慧驅動成長的例子。

Importantly, we are expanding margins while continuing to fund our organic inorganic growth initiatives and increasing returns to shareholders. Q3 adjusted operating margin improved 70 basis points year over year, driven by our disciplined expense management, along with our increasingly AI-enabled delivery model.

重要的是，我們在擴大利潤率的同時，繼續為我們的有機成長和無機成長計畫提供資金，並提高股東回報。第三季調整後營業利潤率年增 70 個基點，這得益於我們嚴格的費用管理以及我​​們日益人工智慧化的交付模式。

Our year-to-date performance has put us on track to outperform the revenue guidance we established at the beginning of the year, and we expect to meet the high end of the adjusted operating margin range we set then.

今年迄今的業績使我們預計將超過年初設定的收入預期，我們預計能夠達到當時設定的調整後營業利潤率範圍的上限。

For much of the last 30 years, IT services grew through a linear model. More people and more projects drove incremental growth. AI is reshaping that equation by compressing time, cost and complexity and redefining how value is created.

在過去30年的大部分時間裡，IT服務的發展都遵循線性模式。人員和專案的增加推動了漸進式成長。人工智慧正在透過壓縮時間、降低成本和簡化複雜性來重塑這種格局，並重新定義價值的創造方式。

The opportunity to partner with the clients and drive outcomes is now more expansive, immersive, and elastic. The progress we are sharing today reflects 2.5 years of focused execution and amplifying talent, scaling innovation and accelerating growth to return Cognizant to a leadership position in the AI era.

與客戶合作並推動成果的機會現在更加廣泛、深入和靈活。我們今天分享的進展反映了過去兩年半以來，我們專注於執行、人才培養、創新規模化和成長加速，使 Cognizant 重返人工智慧時代的領導地位。

Becoming an AI builder means building the platforms and engineering capabilities that enable agentic AI to scale across the enterprise. Our progress begins with our workforce as we enable AI fluency across the 350,000 associates.

成為人工智慧建構者意味著建構平台和工程能力，使智慧人工智慧能夠在企業範圍內擴展。我們的進步始於我們的員工，我們正在讓35萬名員工都能熟練運用人工智慧。

We continue to fuel strength and future readiness for our associates through a learning engine and access to AI tools, which is why we are hiring more new graduates across the world this year and investing in their AI upskilling.

我們透過學習引擎和人工智慧工具不斷增強員工的能力和未來發展潛力，因此，今年我們將在全球招募更多應屆畢業生，並投資提升他們的人工智慧技能。

In July, our Vibe Coding initiative earned Cognizant the Guinness World Records title for the world's largest online Generative AI Hackathon. More than 53,000 associates across 40 countries built over 30,000 working prototypes, improving their AI code assist skills and productivity. And we are continuing to expand into the AI ecosystem.

今年 7 月，我們的 Vibe Coding 計畫為 Cognizant 贏得了金氏世界紀錄「全球最大規模線上生成式人工智慧黑客馬拉松」的稱號。來自 40 個國家的 53,000 多名員工建立了 30,000 多個工作原型，提高了他們的 AI 程式碼輔助技能和生產力。我們正持續拓展人工智慧生態系統。

Recently, we entered a new collaboration with Anthropic. Under our agreement, we plan to deploy Anthropic's cloud models and agentic tooling with our platforms to help clients scale AI, while also deploying them internally to advance our own operations. Our AI Builder strategy is anchored in three distinct vectors. AI-led productivity, industrializing AI, and agentifying the enterprise. When each vector is advancing at a different velocity, together they're performing a flywheel of new value creation.

最近，我們與 Anthropic 展開了新的合作。根據我們的協議，我們計劃將 Anthropic 的雲端模型和代理工具與我們的平台一起部署，以幫助客戶擴展人工智慧，同時也將在內部部署這些模型和工具，以推進我們自身的營運。我們的AI建構器戰略基於三個不同的維度。人工智慧驅動的生產力、人工智慧的產業化以及企業的智慧化。當每個向量以不同的速度前進時，它們共同作用，形成一個不斷創造新價值的飛輪。

Let me provide an update on vector one. AI-led productivity is the funding engine for enterprise transformation as we help clients accelerate software development, lower deployment costs, and reduce technical debt that we estimate is costing enterprises hundreds of billions of dollars in annual servicing.

讓我來更新一下向量圖一的情況。人工智慧驅動的生產力是企業轉型的資金引擎，我們幫助客戶加速軟體開發、降低部署成本並減少技術債務，據估計，這些技術債務每年對企業造成數千億美元的損失。

In the third quarter, approximately 30% of our internal code was AI generated, significantly improving productivity of our developers. We believe it could reach 50% in the years ahead. A great example to illustrate our client impact with Code Assist platform partners is a recent award as the AI GitHub Services and Channel Partner of the Year in recognition of our achievements in helping clients with our AI transformation initiatives. Many clients have asked us for support in bringing wipe coding and code assist best practices to their organizations.

第三季度，我們約 30% 的內部程式碼由人工智慧生成，顯著提高了開發人員的生產力。我們認為未來幾年內這一比例可能會達到50%。為了更好地說明我們與 Code Assist 平台合作夥伴對客戶的影響，我們最近榮獲了 AI GitHub 年度服務和通路合作夥伴獎，以表彰我們在幫助客戶進行 AI 轉型計劃方面所取得的成就。許多客戶都曾向我們尋求幫助，希望我們能將擦除編碼和程式碼輔助的最佳實踐引入他們的組織中。

We recently launched a Cognizant enterprise wipe coding blueprint, bringing our playbooks and insights to clients seeking to build AI fluency across their own teams. This transformation extends beyond the developer community. Internally, we have embedded AI across more than 150 use cases from finance and operations to sales enablement and contract pricing. These applications are streamlining decision-making, improving accuracy and accelerating cycle times.

我們最近推出了 Cognizant 企業級清除編碼藍圖，將我們的經驗和見解帶給希望在其團隊中建立 AI 熟練度的客戶。這種轉變的影響範圍遠不止於開發者群體。在公司內部，我們已將人工智慧嵌入 150 多個用例中，涵蓋財務和營運、銷售賦能和合約定價等領域。這些應用簡化了決策流程，提高了準確性，並加快了週期時間。

A primary tool for executing vector one is our Flowsource platform, which integrates generative and agentic AI across the full software development life cycle. Flowsource is now being used at over 70 clients with an additional 120 in the pipeline. One of those clients is Pearson, where we are using AI and digital technologies to modernize their learning platforms, products and applications by leveraging Flowsource.

執行向量一的主要工具是我們的 Flowsource 平台，它將生成式人工智慧和智能體人工智慧整合到整個軟體開發生命週期中。Flowsource 目前已被 70 多家客戶使用，另有 120 家客戶正在籌備中。其中一位客戶是 Pearson，我們正在利用 Flowsource，透過人工智慧和數位技術來幫助他們實現學習平台、產品和應用程式的現代化。

Our proactive shift to AI native and platform-driven engineering accelerates the software development cycle by enabling engineers to deliver enterprise-grade AI-infused digital applications with greater speed and scale. This is showing up in our results with our approximately 2 billion annual run rate digital engineering business growing about 8% organically year to date.

我們積極轉向 AI 原生和平台驅動的工程技術，使工程師能夠以更快的速度和更大的規模交付企業級 AI 融合數位應用程序，從而加快軟體開發週期。這一點已體現在我們的業績中，我們年運行率約為 20 億美元的數位工程業務今年迄今實現了約 8% 的有機成長。

Vector one is also fueling our large deal momentum as clients consolidate their software estates and shift to outcome-based models, they're capturing savings and unlocking higher value. Often reinvesting those gains into vector two and vector three initiatives. It is creating a self-reinforcing cycle of transformation.

Vector one 也推動了我們的大宗交易勢頭，因為客戶正在整合他們的軟體資產並轉向基於結果的模式，他們正在節省成本並釋放更高的價值。通常將這些收益再投資於第二和第三方向的舉措。它正在形成一個自我強化的轉變循環。

A great example of this in action is our cloud and infrastructure modernization business, which grew 10% year-over-year in the quarter. Our AI tooling and services in the space has helped over 25 clients so far to build, respond and resolve to reliant and resilient IT infrastructure.

一個很好的例子就是我們的雲端和基礎設施現代化業務，該業務在本季度同比增長了 10%。我們在該領域的 AI 工具和服務迄今已協助超過 25 位客戶建置、回應和解決可靠且具彈性的 IT 基礎架構問題。

Now more on vector two or industrializing AI as the scalability layer. It's about moving AI beyond experimentation into enterprise-grade systems, building AI-ready infrastructure, integrating contextual data and operationalizing AI responsibly.

現在更多地討論向量二或將人工智慧工業化作為可擴展層。它旨在將人工智慧從實驗階段推進到企業級系統，建構人工智慧就緒的基礎設施，整合上下文數據，並負責任地實施人工智慧。

It also involves developing new business operating models, leading to an interplay of software and agentic layers, human and agentic capital and structured and unstructured data to reimagine an enterprise. We are leading this effort with our consulting basis framework and methodology to help clients reimagine business processes as they develop and deploy agents.

它還涉及開發新的業務運營模式，從而實現軟體層和代理層、人力資本和代理資本以及結構化資料和非結構化資料的相互作用，以重新構想企業。我們正在引領這項工作，運用我們的諮詢基礎架構和方法論，幫助客戶在開發和部署代理商時重新構想業務流程。

And we are deepening our expertise with the next level capability set, including Agent Foundry, a framework and library of the industry and workflow-specific agents, helping power agentic AI at scale. Together with our clients, we have developed more than 1,500 agents across the company.

我們正在透過下一代能力集來深化我們的專業知識，包括 Agent Foundry，這是一個行業和工作流程特定代理的框架和庫，有助於大規模地推動代理 AI。我們與客戶攜手合作，在公司內部培養了超過 1500 名代理商。

Second, AI data training services, where we have over 10,000 specialists fine-tuning models with domain-specific context. We have supported leading tech companies with training their machine learning systems long before generative AI entered the mainstream, and we are now bringing the same expertise to Global 2,000 clients.

其次，我們提供人工智慧資料訓練服務，擁有超過 10,000 名專家，他們利用特定領域的上下文對模型進行微調。早在生成式人工智慧成為主流之前，我們就一直支持領先的科技公司訓練其機器學習系統，現在我們將同樣的專業知識帶給全球 2000 強客戶。

Third, small language models development. Fourth, context engineering, which we believe is one of the most critical emerging disciplines in enterprise AI to capture enterprise workflows, domain and tribal knowledge, personas, rules and execution patterns. It is the connectivity tissue between models and outcomes.

第三，小型語言模型開發。第四，情境工程，我們認為它是企業人工智慧中最關鍵的新興學科之一，用於捕捉企業工作流程、領域知識和經驗知識、角色、規則和執行模式。它是模型與結果之間的連結紐帶。

In partnership with Workfabric AI, we are deploying context engineers who are helping clients build tailored foundations for AI adoption. And finally, IP on the edge, which I began describing last quarter is a horizontal foundation layer where we are bundling platforms like Neuro AI with services and IP to deliver outcomes.

我們與 Workfabric AI 合作，部署了情境工程師，幫助客戶建立量身定制的 AI 採用基礎。最後，邊緣 IP（我在上個季度開始描述的）是一個水平基礎層，我們將 Neuro AI 等平台與服務和 IP 捆綁在一起，以交付成果。

With 400 platform deployments already in motion, we are helping clients modernize core systems to reduce risk, accelerate time to market and improve experiences. As we build layers of contextual value on foundation models through a combination of context engineering, SLMs and multi-agent systems, we are delivering numerous production-grade AI use cases.

目前已有 400 個平台部署正在進行中，我們正在幫助客戶實現核心系統的現代化，以降低風險、加快產品上市速度並改善使用者體驗。透過結合情境工程、SLM 和多智能體系統，我們在基礎模型上建構多層情境價值，從而交付了眾多生產級 AI 用例。

To bring this to life, we helped the national grocery chain optimize it in-store pickup process for online orders, reducing fulfillment time by 20% to 45% through smarter inventory selection, product substitutions and routing. This is driving a measurable increase in online orders. Lastly, vector three or agentifying the enterprise is about unlocking exponential agentic capital. Historically, we built software for humans.

為了實現這一目標，我們幫助這家全國連鎖超市優化了其線上訂單的店內取貨流程，透過更智慧的庫存選擇、產品替換和路線規劃，將履行時間縮短了 20% 至 45%。這導致線上訂單量顯著增長。最後，第三個向量或企業代理化是關於釋放指數級代理資本。從歷史上看，我們開發軟體是為了服務人類。

With Agentic AI, we now reimagine processes end-to-end by deploying agents with humans in the loop to deliver outcomes. This expands the enterprise's surface area, enabling a blended human plus agent workforce across new domains.

借助智能體人工智慧，我們現在可以透過部署智能體並與人類協同工作來重新構想端到端的流程，從而交付成果。這擴大了企業的覆蓋範圍，使企業能夠在新的領域內實現人機混合型勞動力。

The agentic development life cycle or ADLC differs fundamentally from the traditional software development cycle or SDLC. SDLC is structured and deterministic, input in, output out. ADLC is adaptive and outcome-driven, to design for behavior, supervise performance and evolves capabilities over time.

智能體開發生命週期（ADLC）與傳統的軟體開發生命週期（SDLC）有著根本的差異。軟體開發生命週期是結構化的、確定性的，輸入數據，輸出數據。ADLC 具有適應性和結果導向性，旨在設計行為、監督績效並隨著時間的推移不斷發展能力。

We believe ADLC significantly expands our addressable market, demanding deep ownership to manage human digital collaboration. As an AI builder, we are creating an agentic ecosystem where agents reason, adopt and collaborate, unlocking service capabilities that weren't possible before.

我們相信 ADLC 大大擴展了我們的目標市場，需要對人機協作進行深度管理。作為人工智慧建構者，我們正在創建一個智能體生態系統，在這個生態系統中，智能體可以進行推理、採納和協作，從而釋放以前不可能實現的服務能力。

Cognizant is an early launch partner for Google Gemini Enterprise, an AI-powered platform designed for enterprises to drive unified secure AI capabilities. It seamlessly connects enterprise data, tools, and workflows and leverages Gemini models to enable agentic journeys.

Cognizant 是 Google Gemini Enterprise 的早期發布合作夥伴，Gemini Enterprise 是一個由人工智慧驅動的平台，旨在幫助企業實現統一安全的 AI 功能。它無縫連接企業資料、工具和工作流程，並利用 Gemini 模型實現代理式旅程。

And some client examples include reducing order response times from 5 days to 90 seconds with digital sales agents for a leading food distributor, helping a leading provider of cell-free DNA diagnostics reinvent patient education, access and onboarding processes, modernizing order management for a crop sciences company using Agent force, delivering intelligent lead generation for a top labeling and a packaging provider.

一些客戶案例包括：幫助一家領先的食品分銷商利用數位銷售代理將訂單響應時間從 5 天縮短到 90 秒；幫助一家領先的無細胞 DNA 診斷提供商重新設計患者教育、訪問和入職流程；利用 Agentforce 為一家作物科學公司實現訂單管理現代化；以及為一家頂級標籤和包裝提供商提供智能潛在客戶開發服務。

With TriZetto's core adjudication platform supporting health plans, we have deployed multi-agent workflows that connect TriZetto agents to front-end experience platforms such as Salesforce, Genesys, and ServiceNow to address common interactions such as requesting ID cards from a member or giving provider the status of a claim. We believe much of the vector three will flow into Intuitive Operations and automation practice, which is our BPO business, including BPaaS services.

TriZetto 的核心裁決平台支援健康計劃，我們部署了多代理工作流程，將 TriZetto 代理連接到 Salesforce、Genesys 和 ServiceNow 等前端體驗平台，以處理常見的交互，例如向會員索取身份證或向提供者提供索賠狀態。我們相信，第三股力量的大部分將流入直覺營運和自動化實踐領域，也就是我們的 BPO 業務，包括 BPaaS 服務。

Our BPO revenue grew 10% in the last two quarters and is on track to reach $3 billion in annualized revenue over the next several quarters. We believe identification will unlock new labor pools, including roles that don't yet exist. As digital labor diffuses into enterprise operations, the nature of human endeavor will evolve. Together, our work across vector one, two, and three reflects our evolution into an AI builder company, one that blends deep domain expertise with platform innovation and interdisciplinary talent.

過去兩個季度，我們的業務流程外包 (BPO) 收入成長了 10%，預計在未來幾季內實現 30 億美元的年化收入。我們相信，身分識別將釋放新的勞動力資源，包括目前尚不存在的職位。隨著數位勞動逐漸滲透到企業營運中，人類活動的本質也將隨之改變。我們在向量一、二和三方面的工作共同反映了我們向人工智慧建立公司的演變，這家公司將深厚的領域專業知識與平台創新和跨學科人才相結合。

30 years ago, IT services companies were builders, crafting the foundational systems that powered industries. Over time, the role shifted towards integration, development, and maintenance, and growth became more linear. Today, Cognizant has a unique opportunity to reclaim the builder mindset and capture a greater share of the fragmented AI market.

30年前，IT服務公司是建設者，它們打造了支撐各行各業的基礎系統。隨著時間的推移，角色逐漸轉向整合、開發和維護，成長也變得更加線性。如今，Cognizant 擁有一個獨特的機會，可以重塑建造者思維，並在分散的 AI 市場中佔據更大的份額。

The scale of this opportunity is extraordinary. While global software market is in hundreds of billions of dollars, the surrounding labor spend represents many trillions more. Classical software has barely penetrated that space. We believe AI's winners will be those who diffuse into this labor spend, reshape how work gets done. Software and agent development cycles will coexist, and Cognizant is poised to generate layers of value in this expansive new role for enterprise reimagination.

這個機會的規模非比尋常。雖然全球軟體市場規模達數千億美元，但相關的勞動支出卻高達數兆美元。傳統軟體幾乎沒有滲透到這個領域。我們相信，人工智慧的贏家將是那些滲透到勞動力支出領域，重塑工作方式的企業。軟體和代理商開發週期將並存，Cognizant 已做好準備，在這個企業重塑的全新擴展角色中創造多層次的價值。

In closing, we are proud of our Q3 results and the momentum we are building financially, commercially, and strategically. We are evolving from software implementer to AI builder powered by an engineering heritage and AI-ready workforce and proprietary innovation. We know long-term success will be determined by the outcomes we deliver for our clients, our people and our shareholders.

最後，我們對第三季的業績以及我們在財務、商業和策略方面所取得的進展感到自豪。我們正從軟體實施者轉型為人工智慧建構者，這得益於我們的工程傳承、具備人工智慧技能的員工隊伍以及專有創新。我們知道，長期的成功取決於我們為客戶、員工和股東帶來的成果。

Thank you again for joining us. I'll now turn the call over to Jatin.

再次感謝您的參與。現在我將把電話交給賈廷。

Thank you, Ravi, and thank you all for joining us. We are pleased to report third quarter results that include revenue growth above the high end of our guidance range, strong margin expansion year over year and double-digit adjusted EPS growth. Our performance once again places us in the winner circle, and we are delivering these results despite a complex demand environment and geopolitical backdrop.

謝謝你，拉維，也謝謝各位的參與。我們很高興地宣布第三季業績，其中包括營收成長超過預期範圍的上限、利潤率同比大幅擴張以及兩位數的調整後每股收益成長。我們的出色表現再次使我們躋身贏家行列，而且我們是在複雜的市場需求環境和地緣政治背景下取得這些成績的。

We continue to execute with discipline, driving improved revenue growth while investing in our people, technology and partnership to support our AI builder strategy and long-term growth. At the same time, we are delivering consistent margin expansion. These results are underpinned by balanced capital allocation framework, which we believe are key enablers to driving long-term and sustained shareholder value creation.

我們將繼續以嚴謹的態度執行，推動收入成長，同時投資我們的人才、技術和合作夥伴關係，以支持我們的人工智慧建構者策略和長期成長。同時，我們的利潤率也在持續成長。這些成果得益於均衡的資本配置框架，我們認為這是推動股東價值長期持續成長的關鍵因素。

Now moving to the details of the quarter. In Q3, we delivered revenue of $5.4 billion, up 6.5% year over year in constant currency, again led by strong growth in North America. Belcan contributed slightly less than 250 basis points of inorganic growth.

現在來看本季的具體情況。第三季度，我們實現了 54 億美元的收入，以固定匯率計算年增 6.5%，這再次得益於北美市場的強勁成長。Belcan對無機成長的貢獻略低於250個基點。

Year to date, our revenue grew 7.3% in constant currency, including 350 basis points of inorganic growth. Adjusted operating margin expanded 50 basis points and adjusted EPS grew approximately 11%. And we returned about $1.5 billion of capital to shareholders.

今年迄今為止，我們的營收以固定匯率計算成長了 7.3%，其中包括 350 個基點的非內生成長。調整後營業利益率成長 50 個基點，調整後每股盈餘成長約 11%。我們向股東返還了約15億美元的資本。

With respect to demand environment, trends in Q3 were consistent with last quarter. Clients across industries are navigating elevated levels of uncertainty around trade policy and resulting impacts to their businesses. We are also seeing clients carefully evaluate technology investments, which is resulting in a lower pace of discretionary spending in certain areas like products and resources.

就需求環境而言，第三季的趨勢與上季一致。各行各業的客戶都在應對貿易政策帶來的高度不確定性及其對業務的影響。我們也看到客戶正在仔細評估技術投資，這導致某些領域（如產品和資源）的可自由支配支出成長放緩。

At the same time, cost pressures continue to spur demand for productivity-led and vendor consolidation opportunity across segments. And we see a growing pipeline of modernization projects that lay the foundation of AI-led transformation for our clients.

同時，成本壓力持續刺激各領域對提高生產力和供應商整合機會的需求。我們看到越來越多的現代化專案正在籌備中，這些專案為我們的客戶奠定了人工智慧驅動轉型的基礎。

Now turning to segments. We delivered year-over-year organic growth in all segments in the third quarter. Financial Services led growth, driven by healthy discretionary spending trends in areas like digital engineering, legacy modernization and generative AI initiatives and improved spending among insurance customers, particularly in North America.

現在開始分段。第三季度，我們所有業務板塊均實現了同比增長。金融服務業引領成長，這得益於數位工程、傳統技術現代化和生成式人工智慧計畫等領域健康的自由支配支出趨勢，以及保險客戶（尤其是在北美）支出的增加。

Health Sciences was in line with our expectation and has remained resilient despite the uncertainty around government funding and trade policies. While we have seen pockets of discretionary spending pressure, it is being more than offset by the ramp of recent wins in payer and life sciences.

健康科學領域符合我們的預期，儘管政府撥款和貿易政策存在不確定性，但該領域仍然保持了韌性。雖然我們看到一些可自由支配支出方面存在壓力，但最近在支付方和生命科學領域的成功已經遠遠抵消了這種壓力。

Products and Resources revenue growth has improved, and we are confident we can build off these levels in the quarters ahead as we expect new deal wins to ramp up more meaningfully in 2026. And Communication, Media, and Technology grew organically and benefited from recent large deal wins that more than offset pockets of discretionary spending weakness in the quarter.

產品和資源收入成長有所改善，我們有信心在未來幾季在此基礎上繼續成長，因為我們預計 2026 年新訂單的贏得將更加顯著地增加。通訊、媒體和科技產業實現了有機成長，並受益於近期贏得的大筆交易，這些交易足以抵消本季度部分可自由支配支出疲軟的影響。

Geographically, North America once again led growth and was up nearly 8% year over year in constant currency, driven by our large deal success and Belcan. Outside of North America, demand trends in Europe and Rest of World remained stable, but not immune to impacts from recent tariff and geopolitical uncertainty.

從地理上看，北美再次引領成長，以固定匯率計算年增近 8%，這主要得益於我們的大宗交易成功以及 Belcan 的業績成長。除北美以外，歐洲和世界其他地區的需求趨勢保持穩定，但並未免受近期關稅和地緣政治不確定性的影響。

Turning to bookings. On the trailing 12-month basis, bookings grew 5% and represented a book-to-bill of 1.3. After a strong performance of 18% year-over-year growth in Q2, we experienced some lumpiness in the third quarter and bookings declined by about 5% year over year.

接下來是預訂環節。過去 12 個月，預訂量增加了 5%，預訂出貨比為 1.3。繼第二季年增 18% 的強勁表​​現之後，我們在第三季經歷了一些波動，預訂量比去年同期下降了約 5%。

Our trailing 12-month annual contract value, or ACV, growth was consistent with TCV growth. Overall, our backlog remains healthy and our sustained large deal momentum provides us good visibility as we exit 2025.

我們過去 12 個月的年度合約價值 (ACV) 成長與總合約價值 (TCV) 成長一致。整體而言，我們的訂單儲備依然充足，持續的大額交易動能讓我們在 2025 年底擁有良好的前景。

Moving on to margins. Third quarter operating margin of 16% increased by 70 basis points year over year, benefiting from NextGen program savings and the Indian rupee depreciation. Utilization held steady at 85% for third consecutive quarter, up from 84% a year ago.

接下來討論邊際效益。第三季營業利潤率為 16%，年成長 70 個基點，受益於 NextGen 計畫節省的成本和印度盧比貶值。利用率連續第三個季度保持在 85% 的穩定水平，高於一年前的 84%。

These improvements were partially offset by the ramp of large deals and the dilutive impact from Belcan. Voluntary attrition remained low at 14.5%, down 70 basis points sequentially, the third consecutive quarter of sequential decline and down 10 basis points year over year.

這些改善被大額交易的增加和 Belcan 帶來的稀釋效應部分抵消。自願離職率維持在較低水平，為 14.5%，季減 70 個基點，連續第三個季度季減 10 個基點。

A brief comment on H1B visas. Over the last several years, Cognizant has significantly reduced the dependency on visas, while increasing local hiring and our nearshore capacity. We also stepped up our investments in automation and AI productivity tooling. We, therefore, do not expect a material impact to our operations or financial performance in near term as a result of the recent policy changes in the US.

關於H1B簽證的簡短評論。過去幾年，Cognizant 大幅減少了對簽證的依賴，同時增加了本地招聘和近岸外包能力。我們也加大了對自動化和人工智慧生產力工具的投資。因此，我們預期近期美國政策的變化不會對我們的營運或財務表現產生重大影響。

Now two additional details. During the quarter, we recorded a onetime non-cash income tax expense of $390 million or $0.80 per share. As we discussed last quarter, this charge is related to a deferred income tax asset on the balance sheet that is not expected to be realized due to the enactment of the July US budget bill. Adjusted EPS, which excludes this impact, was $1.39, up 11% year over year. DSO of 82 days declined one day sequentially and increased one day year over year.

現在還有兩個細節要補充。本季度，我們確認了一次性非現金所得稅支出 3.9 億美元，即每股 0.80 美元。正如我們上個季度所討論的，這項費用與資產負債表上的遞延所得稅資產有關，由於 7 月份美國預算案的頒布，預計該資產不會實現。剔除此影響後，調整後的每股盈餘為 1.39 美元，較去年同期成長 11%。DSO 為 82 天，季減一天，較去年同期增加一天。

Third quarter free cash flow was $1.2 billion and represented 170% of adjusted net income. This compares to free cash flow of $791 million a year ago. As a reminder, cash income taxes in the third quarter were approximately $150 million, lower compared to our projections prior to the passing of the July US budget bill. For the full year, we expect that reduction to be $200 million.

第三季自由現金流為 12 億美元，佔調整後淨收入的 170%。相比之下，一年前的自由現金流為 7.91 億美元。需要提醒的是，第三季的現金所得稅約為 1.5 億美元，低於我們在 7 月美國預算案通過先前的預測。我們預計全年減幅將達2億美元。

Through the first nine months of 2025, free cash flow is $1.9 billion and represented approximately 100% of adjusted net income.

2025 年前九個月，自由現金流為 19 億美元，約佔調整後淨收入的 100%。

During the third quarter, we returned $600 million of capital to shareholders through share repurchases and dividends, bringing the year-to-date total to approximately $1.5 billion. We are on track with our plan to return $2 billion to shareholders in 2025. This will bring total capital returned to shareholders since 2022 to nearly $5 billion. We ended the quarter with cash and short-term investments of $2.4 billion or net cash of $1.8 billion.

第三季度，我們透過股票回購和分紅向股東返還了 6 億美元的資本，使年初至今的返還總額達到約 15 億美元。我們正按計畫推進，力爭在 2025 年向股東返還 20 億美元。這將使自 2022 年以來返還給股東的總資本接近 50 億美元。本季末，我們持有現金及短期投資24億美元，淨現金18億美元。

Finally, our M&A pipeline remains active, and we have ample flexibility to invest strategically in the quarters ahead while continuing to return substantial capital to shareholders.

最後，我們的併購專案依然活躍，我們有充足的彈性在未來幾季進行策略性投資，同時繼續向股東返還大量資本。

Now turning to our forward guidance. For the fourth quarter, we expect revenue to grow 2.5% to 3.5% year over year in constant currency, which is all organic. We, therefore, now expect full year revenue to grow 6% to 6.3% in constant currency, above our prior guidance range of 4% to 6%.

現在談談我們的前瞻性指引。我們預計第四季營收以固定匯率計算將年增 2.5% 至 3.5%，全部為內生成長。因此，我們現在預計全年營收按固定匯率計算將成長 6% 至 6.3%，高於我們先前 4% 至 6% 的預期範圍。

We continue to expect full year inorganic contribution of approximately 250 basis points. We are increasing our adjusted operating margin guidance to approximately 15.7%, which is the upper end of our prior guidance and represents 40 basis points of expansion.

我們仍然預計全年非有機成長貢獻約為 250 個基點。我們將調整後的營業利潤率預期上調至約 15.7%，這是我們先前預期的上限，相當於提高了 40 個基點。

We continue to expect margin performance will be driven by cost discipline and SG&A leverage. This year, the fourth quarter will include the impact from a merit cycle compared to its Q3 timing last year. This will be partially offset by year-end seasonal margin strength.

我們仍預期利潤率表現將受到成本控制和銷售、管理及行政費用槓桿作用的驅動。今年第四季將受到績效考核週期的影響，而去年則發生在第三季。年底季節性利潤率的強勁成長將部分抵銷此影響。

We continue to expect free cash flow conversion to be approximately 100% of adjusted net income. This includes the benefit from lower cash taxes as a result of the US budget bill discussed earlier. We expect our adjusted tax rate, which excludes the one-time tax charge to be in 24% to 25% range. Based on our current visibility, we now expect full year tax rate to be closer to the midpoint versus the lower end that we indicated last quarter.

我們仍預期自由現金流轉換率將達到調整後淨收入的 100% 左右。這包括先前討論過的美國預算案帶來的現金稅收降低的好處。我們預計調整後的稅率（不含一次性稅費）將在 24% 至 25% 之間。根據我們目前的了解，我們現在預計全年稅率將更接近中間值，而不是我們上季預測的下限。

We are increasing our EPS guidance to $5.22 to $5.26 compared to our prior range of $5.08 to $5.22. This represents 10% to 11% year-over-year growth. Our expected weighted average diluted share count is unchanged at approximately 489 million. In closing, we are very proud that our guidance puts us on track to meet or exceed the high end of the initial guidance range we provided back in February despite a dynamically changing market compared to the beginning of the year.

我們將每股收益預期從先前的 5.08 美元至 5.22 美元上調至 5.22 美元至 5.26 美元。這相當於年增 10% 至 11%。我們預期的加權平均稀釋股份數量保持不變，約為 4.89 億股。最後，我們非常自豪地宣布，儘管市場與年初相比發生了動態變化，但我們的業績指引仍將使我們有望達到或超過我們在 2 月給出的初始指引範圍的高端。

While we are not commenting on financial expectations for 2026, we feel well-positioned to carry this momentum as we look ahead and remain committed to the long-term financial framework we provided at the Investor Day earlier this year. With that, we will open the call for your questions.

雖然我們不對 2026 年的財務預期發表評論，但我們感覺自己已做好充分準備，保持這一勢頭，展望未來，並將繼續致力於我們在今年早些時候的投資者日上提出的長期財務框架。接下來，我們將開放提問環節。

(Operator Instructions)

（操作說明）

Jim Schneider, Goldman Sachs.

吉姆‧施耐德，高盛集團。

Ravi, I wonder if you could speak to the new business pipeline you're seeing for smaller deals at this stage and whether you're seeing any kind of significant uptick there or not? And then relative to larger deals, are you seeing any pull-in or extension in terms of the commencement date for those large deal new bookings?

Ravi，我想請你談談目前小額交易的新業務拓展情況，以及你是否看到這方面有任何明顯的增長？那麼，對於金額較大的交易，您是否看到這些大額交易的新預訂的生效日期有任何提前或延遲的情況？

Thank you, Jim, for that question. Look, large deals have nicely balanced between the two swim lanes I've been talking about. Early on in 2024 and early 2025, a lot of it was consolidation productivity led. Now we are seeing a new swim lane evolve, which is AI innovation led, which is primarily agentic cycles, deploying AI into enterprise landscapes.

謝謝你，吉姆，問了這個問題。你看，大宗交易在我一直提到的兩個領域之間已經達到了很好的平衡。2024年初和2025年初，許多成長都是由整合和生產力提升所驅動的。現在我們看到一條新的泳道正在形成，那就是由人工智慧創新驅動的泳道，它主要由智慧體循環構成，將人工智慧部署到企業環境中。

And therefore, if you've noticed, our digital engineering business has grown at 8% in the last few quarters. Our infrastructure-led AI has grown by 10% in the last few quarters.

因此，如果您注意到了，我們的數位工程業務在過去幾個季度增長了 8%。在過去的幾個季度裡，我們以基礎設施為主導的人工智慧成長了 10%。

And our BPO business is rocking. It's actually growing at 10% again. And that we are starting to see. So it's a combination of productivity-led, innovation-led. I mean, I've always been saying that this is a double engine transformation.

我們的業務流程外包業務發展勢頭強勁。實際上，它又以10%的速度成長了。而我們現在開始看到這一點了。所以它是生產力驅動型和創新驅動型結合的產物。我的意思是，我一直都說這是雙重引擎的改變。

While you can apply it on software cycles, get productivity and transfer the lower cost of deployment for higher spend of software.

雖然你可以將其應用於軟體開發週期，提高生產力，並將較低的部署成本轉移到較高的軟體支出。

On the other end, you can apply it on -- you can apply agentic capital on enterprises. There's so much of infrastructure spend, which has happened. It has to create a build opportunity. And that's why I keep saying we are an AI builder. So we are seeing discretionary small projects starting to come back in financial services and healthcare.

另一方面，你可以將其應用於——你可以將代理資本應用於企業。基礎建設方面的投入非常巨大，而且已經發生了。它必須創造建設機會。所以我一直說我們是人工智慧建構者。因此，我們看到金融服務和醫療保健領域的一些非必要的小項目開始回歸。

And that's all related to AI-led spend. So as you save on one side from software cycles, you transfer that money to innovation, so very healthy pipeline.

而這一切都與人工智慧驅動的支出有關。因此，一方面，你節省了軟體開發週期的成本，另一方面，你把這筆錢轉移到了創新上，從而形成了一個非常健康的創新體系。

I'm excited about the large deals. I'm excited about the discretionary coming back on small deals, which is AI led. I mean so much infrastructure has been spent that it has to trickle down to services. And there's always been a lag between when hardware was spent, then the software and then the services. That cycle has shrunk now, and we'll be breaking that cycle.

我對這些大宗交易感到興奮。我對人工智慧主導的小額交易中可自由支配資金的回歸感到興奮。我的意思是，基礎建設投入龐大，這些投入最終必然會惠及服務業。硬體投入、軟體投入和服務投入之間總是存在滯後。這種循環現在已經縮小了，我們將打破這個循環。

So the services spend is going to catch up because of the extraordinary spend on compute and AI infrastructure.

因此，由於在運算和人工智慧基礎設施方面投入了巨額資金，服務支出將會迎頭趕上。

Tien-Tsin Huang, JPMorgan.

黃天心，摩根大通。

Nice results. Well done. I want to ask on the revenue per employee. It looked like up 8%, operating income also better than that, up 10%. So just understanding the lift there and if it's sustainable or even structural given some of the AI returns that you talked about.

結果不錯。做得好。我想諮詢一下每位員工的收入狀況。看起來成長了 8%，營業收入也比這更好，成長了 10%。所以，我只是想了解這種成長動能是否可持續，以及考慮到你提到的AI帶來的一些回報，這種成長是否具有結構性意義。

Thank you so much for that question. In fact, just a follow-up on the previous question. We're also seeing mega deals. Last quarter, we did two. The quarter before, we did one. So mega deals are also starting to line up because that savings can be underwritten for innovation.

非常感謝你的提問。事實上，這只是前一個問題的後續。我們也看到了一些巨額交易。上個季度我們做了兩個。上個季度，我們做了一次。因此，巨額交易也開始陸續出現，因為節省的資金可以用來支持創新。

Now coming to your question, this is an interesting lead indicator, revenue per person and margin per person. Revenue per person went up by 8%, margin per person went up by 10%. It's indicative of how we are becoming an AI builder company with platforms, intellectual property, software and services all bundled together. So we're excited about that. It's a combination of things.

現在回到你的問題，這是一個很有趣的領先指標，即人均收入和人均利潤。人均收入成長了 8%，人均利潤成長了 10%。這顯示我們正在轉型成為一家集平台、智慧財產權、軟體和服務於一體的人工智慧建構公司。所以我們對此感到很興奮。這是多種因素的綜合作用。

Our fixed price managed services business is going up. It has gone up from 43% in 2024 to right now almost close to 47%. That gives us a chance to deliver work for outcomes and therefore, create more revenue per person and margin per person.

我們的固定價格管理服務業務正在成長。2024 年的比例為 43%，而目前已接近 47%。這讓我們有機會交付成果，從而創造更高的人均收入和人均利潤。

It is actually going to transition, and Jatin has been talking about it, that we are a fixed price time and material and a transaction-based business. We are going to go from more fixed price, more outcome-based, more transaction-based, less time and material in the future.

實際上，公司將會轉型，Jatin 也一直在談論這一點，我們將成為一家以固定價格、按工時和材料計費、以交易為基礎的企業。未來我們將從更固定的價格模式、更注重結果的模式、更注重交易的模式，減少對時間和材料的投入。

So productivity has gone up 30%, which means there is more throughput you can actually create more throughput, share the savings, lower cost of deployment with our clients. So effectively, putting all this together, this is a very good proxy for AI services. And that's why we thought -- we've been tracking this, but we thought we should let analysts and investors know about it.

因此，生產力提高了 30%，這意味著吞吐量更大，您可以創造更大的吞吐量，與我們的客戶分享節省的成本，降低部署成本。因此，綜合以上所有因素，這可以很好地代表人工智慧服務。正因如此，我們才想——我們一直在關注此事，但我們認為應該讓分析師和投資者了解此事。

Yeah. That's good proxy, good data point for us to have. Just on the -- my follow-up, then I'll ask on gross margin probably like I usually do. Just thinking about near-term gross margin performance potentially given the expected deal ramps and the mega deals and what have you. Any specific callouts on gross margin in the next couple of quarters?

是的。這是一個很好的參考指標，對我們來說是一個很好的數據點。就在我的後續跟進中，然後我可能會像往常一樣詢問毛利率。考慮到預期中的交易成長、巨額交易等等，我只能考慮近期毛利率表現。未來幾季毛利率有什麼特別需要關注的地方嗎？

Sure. Thank you for that question, Tien-Tsin. I would start by saying how we have executed for first nine months, while you see the headline number a little soft, but on gross margin, we have been able to largely maintain the gross margins on an organic basis. The reduction that you see on a year over year basis is coming through on account of the consolidation of Belcan, which was expected when we did the deal.

當然。謝謝你的提問，田進。首先我想說說我們前九個月的執行情況，雖然你們可以看到整體業績數據略顯疲軟，但就毛利率而言，我們基本上實現了毛利率的自然增長。你們看到的同比下降是由於 Belcan 的合併造成的，這是我們在進行交易時預料到的。

So overall, we are quite happy that despite the ramp-up of large deals and investments that we are making, we are able to maintain gross margin in a very narrow range of last year in an organic basis. Going forward also, our endeavor would be to continue to look at three or four operational levers. And the top of that is AI-led productivity that Ravi spoke about.

總的來說，儘管我們正在加大交易和投資力度，但我們仍然能夠以有機成長的方式將毛利率維持在去年非常窄的範圍內，我們對此感到非常滿意。展望未來，我們將繼續努力，著眼於三到四個營運槓桿。而其中最重要的就是拉維所提到的AI驅動的生產力。

The second is pyramid. You know we have invested 15,000 to 20,000 in recent college graduates and it's more than most. And it's significantly higher than last year. So we continue to improve the pyramid. And third is utilization, which you can see we have kept it at 85% now third quarter in a row.

第二種是金字塔。你知道我們已經在應屆大學畢業生身上投資了 15,000 到 20,000 美元，這比大多數公司都多。而且比去年同期高出很多。因此，我們會繼續改進金字塔模型。第三點是利用率，可以看到我們已經連續三個季度將其保持在 85%。

It is higher by 1 percentage point compared to quarter three of last year. So we feel we are making good progress on gross margin, and hopefully, that will continue to reflect in the numbers.

與去年第三季相比，上升了1個百分點。因此，我們感覺在毛利率方面取得了良好進展，希望這能繼續體現在各項數據中。

Maggie Nolan, William Blair.

瑪吉諾蘭，威廉布萊爾。

Can you shed some insight on how you're tracking the success of upskilling your employees with those AI-related skill sets?

您能否分享一下您是如何追蹤員工在人工智慧相關技能提升方面的成效的？

Thank you for that question. I mean we are pioneering this effort. Early on, we were the first company and probably the only company which -- in our peer group, which speaks about percentage of code and software development cycles assisted by machines. That's at 30%, and we are constantly tracking to stay ahead of the curve. We are the number one company on GitHub Copilot.

謝謝你的提問。我的意思是，我們是這項工作的先驅。在早期，我們是第一家，也可能是唯一一家——在我們同行中——談到機器輔助的程式碼和軟體開發週期百分比的公司。目前佔 30%，我們正在不斷追蹤進展，以保持領先地位。我們是GitHub Copilot上排名第一的公司。

In fact, we are the GitHub Copilot AI Partner of the Year. We have been the launch partner for Gemini -- Google Gemini Enterprise. We just signed a deal with Anthropic on cloud.

事實上，我們是 GitHub Copilot 年度人工智慧合作夥伴。我們一直是 Gemini（Google Gemini Enterprise）的啟動合作夥伴。我們剛剛與 Anthropic 公司簽署了雲端服務協議。

We have created a hustle inside the company that the only way you should write and the only way you should be assisted in software development is through machines. And that has become the way of doing work at Cognizant.

我們在公司內部營造了一種風氣，那就是編寫程式碼和獲得軟體開發協助的唯一方法就是透過機器。這已成為 Cognizant 的工作方式。

In fact, we are on the Guinness book of records for the highest number of people on an hackathon concurrently. In fact, we ran that to create culture and create a permanency in the way we write software. We are the only company which is actually saying we are going to hire more school graduates than ever before.

事實上，我們因同時參與黑客馬拉鬆的人數最多而載入金氏世界紀錄。事實上，我們推行這項計劃是為了創造一種文化，並使我們編寫軟體的方式更加規範化。我們是唯一一家明確表示將比以往任何時候都招募更多應屆畢業生的公司。

We are doubling those numbers from last year because we think we can actually create a significant productivity leap with our extraordinary training infrastructure.

我們之所以將去年的數字翻一番，是因為我們認為憑藉我們卓越的培訓基礎設施，我們確實可以實現生產力的顯著飛躍。

So all of this put together, we seem to be on a pioneering opportunity. This is on one swim lane, which is software development. Of course, there is a ton of work on the agentic development, which is much more surface area, much more spend, more expensive.

綜上所述，我們似乎正處於一個開創性的機會之中。這是其中一個泳道，即軟體開發。當然，代理開發方面還有很多工作要做，這涉及的範圍更廣，花費更多，成本也更高。

So our double engine, both on productivity and on innovation is deeply embedded with skilling, reskilling, hiring from schools, building productivity alongside machines, and that is the only way we want to create throughput.

因此，我們在生產力和創新方面的雙重引擎深深植根於技能培訓、再培訓、從學校招募員工、與機器協同提高生產力，而這正是我們想要創造產量的唯一途徑。

And if we do this well, software has elasticity to be spent more. If we do this well, that money is going to be transitioned to agentic capital and working alongside agents for human workforce, I think, is going to be an amplifying potential of humans. So we have pretty much trained almost all our employees, more than 250,000-plus employees on AI-led skills.

如果我們能做好這一點，軟體就具有足夠的彈性，可以投入更多資金。如果我們能做好這件事，這些資金將會轉化為代理資本，與人力資源代理人一起工作，我認為，這將放大人類的潛力。因此，我們已經對幾乎所有員工（超過 25 萬名員工）進行了人工智慧技能培訓。

That's helpful. And then should we expect large deal and mega deal signings to impact the quarterly cadence of revenue and margins in 2026? Can you help us think about the ramp over the course of the year from a modeling perspective?

這很有幫助。那麼，我們是否應該預期大型交易和超級交易的簽署會對 2026 年的季度收入和利潤率產生影響？您能否從建模的角度幫助我們思考這一年的成長趨勢？

That's a great question. In fact, if you notice, in 2023, our trailing 12 months range of bookings was in the range of $24 billion. And it's now actually at $27 billion-plus. So we've had tailwind from '24 into '25. Our annual contract value is very nicely stacking up to the total contract value.

這是一個很好的問題。事實上，如果你留意一下，你會發現，2023 年我們過去 12 個月的預訂量在 240 億美元左右。現在實際數字已經超過 270 億美元。所以從 2024 年到 2025 年，我們一直順風順水。我們的年度合約金額與合約總金額的差距非常小。

In fact, our total contract value from large and mega deals has gone up by 40%, while the number of deals is 16 and so far, and we have another quarter to go. Just the TCV value has just significantly gone up. It's gone up by 40%.

事實上，我們來自大型和特大交易的總合約價值增加了 40%，而交易數量目前為 16 筆，我們還有最後一個季度要完成。TCV值顯著上升。上漲了40%。

So we think we have tail velocity going into quarter four as well as going into the next year on large and mega deals. I don't see any shift on that. And on the contrary, I actually see that on two swim lanes. In '23 and '24, the swim lane was productivity.

因此，我們認為在第四季以及明年，大型和特大交易都將保持強勁的成長勢頭。我沒看到這方面有任何改變。相反，我實際上在兩條泳道上看到了這種情況。2023 年和 2024 年，泳道的重點是生產力。

And in '25, we are starting to see we are starting to see innovation-led, agentic capital-led, much more expansive. I've always been saying one swim lane is software, another swim lane is Agentic. The Agentic is more expansive, more elastic and more immersive. We are seeing large deals on it. And in '23 and '24, a lot of it was Americas based.

到了 2025 年，我們開始看到創新驅動、行動資本驅動的局面更加廣闊。我一直說，一個泳道代表軟體，另一個泳道代表智能體。智能體更具擴展性、更靈活、更沉浸。我們看到這方面有很多大宗交易。2023 年和 2024 年，很多案件都發生在美洲。

Now we are seeing Europe and Asia Pacific starting to be a part of it, and we are excited about the momentum we have created in Europe on large deals.

現在我們看到歐洲和亞太地區也開始參與其中，我們對在歐洲大型交易中取得的進展感到興奮。

Surinder Thind, Jefferies.

蘇林德‧辛德，傑富瑞。

Ravi, can you maybe talk about the partnership strategy here and how important it is to maybe partner with each of the major providers versus maybe being a bit more selective and becoming more of a partner of choice with maybe some of the individual providers, whether it's GCS versus Anthropic or OpenAI or however you're thinking about that strategy?

Ravi，您能否談談這裡的合作策略，以及與各大供應商合作的重要性，還是應該更加挑剔，成為某些特定供應商的首選合作夥伴，無論是 GCS 與 Anthropic 還是 OpenAI，或者您是如何考慮這種策略的？

Surinder, thank you for that question. Partnerships traditionally were SaaS companies and classical software companies, of course, cloud-based hyperscalers as well. Now I would add more things to the mix. I mean, look, SaaS companies and classical software companies will transition the business logic to the agentic layer, which they build on it. I mentioned this in my remarks that the machine was always with the software companies, and we were a system integrator.

蘇林德，謝謝你的提問。傳統上，合作夥伴包括 SaaS 公司和傳統軟體公司，當然也包括基於雲端的超大規模雲端服務供應商。現在我想再增加一些其他元素。我的意思是，你看，SaaS 公司和傳統軟體公司都會將業務邏輯轉移到他們所建構的代理層。我在發言中提到過，這台機器一直都在軟體公司那裡，而我們是系統整合商。

Now we are AI builder, which means we have intellectual property platforms built. It's a very heterogeneous and a fragmented AI market. Our clients are not saying, come in with your capability. They're saying, come in with your machine. which means you have to actually have the platforms. It could be partner-led, it could be our own. And we are actually, therefore, investing into platforms and intellectual property.

現在我們是人工智慧建構者，這意味著我們已經建立了智慧財產權平台。人工智慧市場非常多元化且分散。我們的客戶並不是說，帶著你的能力來吧。他們的意思是，帶著你的機器來。這意味著你必須實際擁有相應的平台。它可以是由夥伴主導，也可以是我們自己主導。因此，我們實際上正在投資平台和知識產權。

In addition to that, we have this new thing because now the machine actually belongs to the frontier model companies, which is OpenAI, Anthropic kind of firms. In fact, that's one of the reasons why we partnered with Anthropic.

除此之外，我們還有這樣一件新事，因為現在這台機器其實屬於前沿模式的公司，像是 OpenAI 和 Anthropico 這類公司。事實上，這也是我們與 Anthropic 合作的原因之一。

So we are activating multiple swim lanes, our own custom platforms built on enterprise software companies where we have long-term partnerships, SaaS companies, but we also are partnering with frontier model companies because we could create custom AI agentic capital directly. And the Anthropic partnership is an indication of the particular swim lane. So it's a much broader partnership lens, including start-ups.

因此，我們正在啟動多個泳道，包括我們基於企業軟體公司（我們與這些公司建立了長期合作關係）、SaaS 公司構建的我們自己的客製化平台，但我們也與前沿模式公司合作，因為我們可以直接創建客製化的 AI 代理資本。而與 Anthropic 的合作則顯示了其所處的特定泳道。所以，這是一種更廣泛的合作視角，包括與新創企業的合作。

I mean I work with WRITER, I work with Workfabric AI. These are layers of value on top of the LLM. And some of those layers are owned by us, built by us, some of them are partnered. And of course, the frontier model companies allow us to create a swim lane on -- with the engine actually belonging to them, but we build the layers of service around it. So we think it's more expansive and more broad-based.

我的意思是，我使用 WRITER，我使用 Workfabric AI。這些是在法學碩士學位之上增加的價值層。其中一些層是我們自己的，由我們建構的；其他層是與合作夥伴共同建構的。當然，這些前沿模式的公司允許我們開闢一條新的道路——引擎實際上屬於他們，但我們圍繞著它來建立服務層。所以我們認為它更具擴展性和更廣泛的基礎。

That's helpful. And then as a follow-up, can you maybe talk about the IP that you're building? And more specifically, you mentioned having upwards of 1,500 agents in production. How does that impact the revenue model at this point? Are you able to charge for some of that? Do you keep some of that IP? Or is it more of a core base and then you kind of custom build agents then.

這很有幫助。那麼，作為後續問題，您能否談談您正在開發的智慧財產權？更具體地說，您提到有超過 1500 個代理商正在生產中。這會對目前的收入模式產生什麼影響？你能對其中一部分收費嗎？你會保留一些IP位址嗎？或者說，它更像是一個核心基礎，然後你可以根據需要自訂建立代理程式。

I think it's a combination, Surinder. It's a combination. Look, on Flowsource, which is a platform which sits on top of Code Assist platforms, it gives us the opportunity to get better productivity and that productivity passes on to our revenue per person and margin per person metrics. Our other IP and platforms we are building are the ability to take the raw power of AI and make it enterprise grade, which means it could be the accuracy of the models.

我認為這是多種因素共同作用的結果，蘇林德。這是兩者的結合。你看，Flowsource 是一個建立在 Code Assist 平台之上的平台，它讓我們有機會提高生產力，而這種生產力會提升我們的人均收入和人均利潤率。我們正在建構的其他智慧財產權和平台能夠將人工智慧的原始能力提升到企業級水平，這意味著模型的準確性可能會更高。

Yesterday, we got a patent on changing the -- on a new way of pretraining a model, not based on reinforcement learning, but based on evolution strategies, which our labs got in. So we are building a platform around it. We have a platform around multi-agent systems, which means you could have agents talking to each other.

昨天，我們獲得了一項關於改變——關於一種新的模型預訓練方法的專利，這種方法不是基於強化學習，而是基於演化策略，這是我們的實驗室所取得的成果。所以我們正在圍繞它建立一個平台。我們有一個圍繞多智能體系統的平台，這意味著你可以讓智能體之間相互對話。

One example is in TriZetto, our TriZetto agents talk to Salesforce agents and Genesys and the ServiceNow agents, and they actually deliver outcomes like ID cards and status of a claim automatically and auto adjudication of claims and stuff like that.

一個例子是 TriZetto，我們的 TriZetto 代理與 Salesforce 代理、Genesys 和 ServiceNow 代理進行通信，他們實際上會自動提供諸如 ID 卡、索賠狀態、自動裁決索賠等結果。

So the platforms are all about taking the raw power of AI and making it enterprise grade. It could be on accuracy, on responsible AI. It could be on new ways of pretraining the model, a variety of things which are needed to make it enterprise grade. There is so much infrastructure spend, which has happened. That value has to trickle down. And the use cases, which are now coming out, production grade, we are able to generate more of it because of the intellectual property we have built.

因此，這些平台的目標都是將人工智慧的原始力量轉化為企業級應用。這可能關乎準確性，也可能關乎負責任的人工智慧。這可能涉及模型預訓練的新方法，以及使其達到企業級水平所需的各種因素。基礎建設方面的投入非常巨大，而且已經實現。這種價值必須層層傳遞下去。而現在湧現的、生產等級的應用案例，由於我們擁有知識產權，我們能夠產生更多這樣的案例。

We are also closely monitoring partnerships. I mean the context engineering piece is a unique pioneering opportunity for us. This is a contextual computing era, which means you need to feed the context, could be the tribal knowledge, the workflows, the data flows, the hassle of a company and you have to feed it into the LLM and create a contextual agent who is much more productive than a generic agent.

我們也密切關注合作夥伴關係。我的意思是，情境工程部分對我們來說是一個獨特的開創性機會。這是一個情境計算時代，這意味著你需要輸入情境信息，例如經驗知識、工作流程、資料流、公司的各種麻煩等等，你需要將這些資訊輸入到 LLM 中，創建一個比通用代理更有效率的情境代理。

That actually needs -- it's a science which is evolving. So we're building intellectual property along with a partner of ours.

這實際上需要——這是一門不斷發展的科學。所以我們正在與合作夥伴共同打造智慧財產權。

So I think this is going to be a platforms plus capability kind of a model. And therefore, I call myself an AI builder company, and we are pioneering that effort of transitioning from just a capability firm to a platforms plus capability. And historically, we had that culture with our healthcare business where a lot of it is platform plus services with TriZetto.

所以我認為這將是一種平台加能力的模式。因此，我稱自己為人工智慧建立公司，我們正在率先從一家單純的能力公司轉型為平台加能力的公司。從歷史上看，我們的醫療保健業務一直秉持著這樣的文化，以 TriZetto 為核心的平台加服務模式。

Darrin Peller, Wolfe Research.

Darrin Peller，Wolfe Research。

Just a financial question. Just when I look at the guide of 2.5% to 3.5% constant currency for fourth quarter, just what are the puts and takes there? Any early insights into how budgets are shaping up also into '26 would be helpful.

只是一個財務方面的問題。當我看到第四季以固定匯率計算的2.5%至3.5%的指導價時，這其中究竟有哪些利弊？任何關於2026年預算編制情況的早期見解都將有所幫助。

So as you can imagine, difficult to talk about '26 at this juncture. We will come back in January and speak about it. But overall, there is no major change in the demand environment. We continue to win share, and that is reflected in the superior execution of the quarter that went by. Quarter four seems to be a customary quarter four with its lower number of bill days and furlough.

所以你可以想像，在這個時候談論 2026 年的事情很困難。我們將在1月回來討論此事。但整體而言，需求環境並沒有重大變化。我們持續贏得市場份額，這體現在上一季出色的業績表現。第四季似乎與往常一樣，帳單日較短，員工休假也較少。

Nothing out of ordinary. Our guidance range reflects essentially, if things could go a little worse, then it's the bottom end. And if we can get some additional momentum in revenue and bookings, then it's the upper end. So that's how we have worked through quarter four, and that's the full year guidance.

一切正常。我們的指導範圍基本上反映的是，如果情況可能會更糟，那麼那就是下限。如果我們能在收入和預訂量方面再取得一些成長勢頭，那麼就能達到更高的目標。這就是我們第四季的工作狀況，也是全年的業績預期。

Just one quick addition there. I would say, look, the activation of AI-led innovation use cases, we've gone from 2,500 to 3,500 this quarter. So literally 40% jump. So the money you save on the software cycles on productivity is going to be underwritten to innovation cycles. That is triggering off very well.

再補充一點。我想說，你看，人工智慧驅動的創新用例的激活數量，本季已經從 2500 個增加到 3500 個。所以，實際漲幅高達 40%。因此，你在軟體開發週期中節省下來的提高生產力的資金，將用於創新週期。觸發效果非常好。

And I don't think CIOs are saying they're going to cut their budgets. Nobody has told me that. They're all going to -- they're all saying, how can you give me more value? And that's why we are benefiting out of this.

而且我認為資訊長們並沒有表示要削減預算。沒人跟我說過這件事。他們都會說──他們都在問，怎樣才能帶給我更多價值？這就是我們從中受益的原因。

Okay. That's helpful. And then maybe just one quick follow-up would be if you could just discuss -- just you're obviously doing well with larger deals. Maybe just discuss the competitive dynamics for some of the large deals you're seeing and what's allowing you guys to continue winning them? And then how important is price in the discussion and maybe build into that what AI can do for you on pricing if you could pass through some of your savings into?

好的。這很有幫助。然後，或許可以快速跟進一下，您能否談談——顯然，您在大額交易方面做得很好。或許可以討論一下你們看到的一些大宗交易的競爭格局，以及是什麼讓你們能夠持續贏得這些交易？那麼，價格在討論中有多重要？或許還可以探討一下，如果能將節省下來的部分成本投入到人工智慧的定價中，人工智慧能為你做些什麼？

Yeah. Look, price was always a linear thing in the past because it was labor related and productivity of tooling was not in the mix. I would say it was a minority. Right now, pricing is productivity led, and it depends on how much you can use your platforms and how much you can use your AI tooling and the culture we have established now. So pricing is kind of linked to how fast we can keep that runway on productivity.

是的。你看，過去價格一直是個線性關係，因為它與勞動力有關，而工具的生產力並沒有被考慮。我認為這只是少數情況。目前，定價以生產力為導向，取決於您能在多大程度上使用您的平台、您的 AI 工具以及我們現在已經建立的文化。所以定價在某種程度上與我們保持生產力提升的速度有關。

Large deals on consolidation and productivity will always be price sensitive because they're done for savings and creating more velocity.

大型整合和提高生產力的交易總是對價格敏感，因為它們是為了節省成本和提高效率而進行的。

The innovation side of it, I mean, that's going to be much more -- that's going to be less sensitive to price because you are actually delivering new products and new services using AI. I don't see much of a change in the pricing. I would actually say if the other swim lane gets activated, which is innovation-led, you will get strength behind the pricing.

創新方面，我的意思是，那將更加——對價格的敏感度會更低，因為你實際上是在使用人工智慧來提供新產品和新服務。我認為價格方面不會有太大變動。我其實想說，如果另一條泳道（即創新驅動的泳道）被激活，那麼定價就會更有力。

(Operator Instructions)

（操作說明）

Yogesh Aggarwal, HSBC Bank.

Yogesh Aggarwal，匯豐銀行。

Just have a question actually totally disconnected to the quarter and demand, et cetera. Just in the past few quarters, Cognizant performance has consistently improved and now you're growing almost at the top end of the peer range.

我有個問題，其實跟季度、需求等等完全無關。在過去的幾個季度裡，Cognizant 的業績持續提升，現在其成長速度幾乎達到了同業中的頂尖水準。

But I'm sure you would have noticed as well the stock still is at a significant discount to the peer group. So I was just curious, any thoughts on secondary listing in India? I mean, is it something on the table and any puts and takes for the same? Just curious to know your thoughts, please.

但我相信您也已經注意到，該股票的價格仍然比同行低很多。我只是好奇，大家對在印度進行二次上市有什麼看法？我的意思是，這是否是一個可以討論的話題，以及對此是否有任何報價或報價？只是好奇想聽聽你們的想法。

Yeah. So Yogesh, thank you. That is an interesting question. Cognizant's Board and management team regularly assess opportunities to enhance the shareholder value. Towards this end, we have been assessing a potential primary offering and a secondary listing in India with our legal and financial advisers.

是的。約格甚，謝謝你。這是一個有趣的問題。Cognizant 的董事會和管理團隊會定期評估提升股東價值的機會。為此，我們一直在與我們的法律和財務顧問一起評估在印度進行首次公開發行和二次上市的可能性。

As part of this comprehensive review, which is still in its early phase, we are engaging various stakeholders from both India and US to evaluate the implications of such a potential offering and listing. The process of a primary offering and a secondary listing in India by an overseas company is complex and involves multiple steps.

作為這項仍處於早期階段的全面審查的一部分，我們正在與印度和美國的各個利益相關者進行溝通，以評估這種潛在的發行和上市的影響。海外公司在印度進行首次公開募股和二次上市的過程十分複雜，涉及多個步驟。

We view this as a long-term project. While no decision has been made and any offering and secondary listing would be subject to market and other factors, we continue to assess and review the idea and are committed to acting in the best interest of our shareholders. So that's our response, Yogesh.

我們將其視為一個長期項目。雖然尚未做出任何決定，任何發行和二次上市都將取決於市場和其他因素，但我們將繼續評估和審查這個想法，並致力於維護股東的最大利益。這就是我們的答复，Yogesh。

Rod Bourgeois, DeepDive Equity Research.

Rod Bourgeois，DeepDive Equity Research。

So I want to talk for a second about financial services vertical. You mentioned improved spending there, and we are seeing some of that across the broader sector. Can you speak to what form that improved spending is taking in the financial services vertical? And in particular, are you now seeing those clients moving beyond AI for cost savings and into more AI-based reinvention at those clients?

所以我想簡單談談金融服務領域。您提到了這方面的支出有所增加，我們也看到這種情況在更廣泛的領域內有所改善。能否談談金融服務領域支出增加的具體形式？特別是，您是否看到這些客戶不再僅僅為了節省成本而使用人工智慧，而是轉向基於人工智慧的更多創新？

Thank you, Rod, for that question. Absolutely. I think this is probably my fourth or fifth quarter where we have done year-over-year growth as well as from the start of the year, we have been sequentially growing in financial services. It's been one of our best-performing industry groups. I think the spend has gradually transitioned from cost takeout consolidation to more innovation.

謝謝你，羅德，提出這個問題。絕對地。我認為這可能是我們第四或第五個季度實現了同比增長，而且從年初開始，我們在金融服務領域也一直保持著持續增長。它一直是我們表現最好的行業群體之一。我認為支出已經逐漸從降低成本的整合轉向了更多的創新。

I would say if you take the 3,500 projects we are doing on AI-led innovation, a significant chunk are actually moving from experimentation to enterprise-grade AI. And all the platforms I'm speaking about in the call, a lot of them are getting implemented in financial services. In fact, insurance, which is a part of BFSI has also started to spend. It's a sector which kind of was lagging a little bit, but it has started to spend as well. So we are very, very excited about the future of financial services.

我認為，在我們進行的 3500 個人工智慧驅動創新專案中，相當一部分實際上正在從實驗階段過渡到企業級人工智慧階段。我在電話會議中提到的所有平台，很多都在金融服務領域得到應用。事實上，作為金融服務業一部分的保險業也開始支出。這個行業之前發展有些滯後，但現在也開始增加支出了。因此，我們對金融服務的未來感到非常非常興奮。

Over the last few years, Cognizant per se, we have had quarters where we haven't performed in the previous years. But the turnaround has started from the middle of, I would say, 2024. And here we are, it is actually one of -- it is actually our best-performing industry group. The spend cycles are great, and clients are actually innovating much more.

過去幾年，就 Cognizant 本身而言，我們有些季度的業績不如前幾年。但我認為，轉機大約從 2024 年中開始出現。而事實是，它實際上是我們表現最好的行業群體之一。消費週期很好，顧客也確實在不斷創新。

Every segment of financial services has accelerated in terms of spend and the discretionary is coming back because the value you get out of discretionary now is much higher because the cost of capital is high, but the deployment costs have gone down. So that is giving clients the confidence to experiment more and actually take it to production. So financial services will be one of our bellwether industries in 2026 as well.

金融服務的各個領域在支出方面都加速成長，可自由支配的支出正在回升，因為現在可自由支配的支出價值更高，這是因為資本成本很高，但部署成本卻下降了。這樣一來，客戶就有信心進行更多嘗試，並最終將其投入生產。因此，金融服務業在2026年仍將是我們的風向標產業之一。

Great. And then moving to healthcare. I mean, there's been some policy uncertainty in that vertical. You've also got the TriZetto asset. Just can you speak a little bit about the outlook for the healthcare vertical in general? And in particular, with TriZetto and all of the AI work that you're doing, are you seeing BPaaS as an increased opportunity there? Just any color on the healthcare outlook.

偉大的。然後轉向醫療保健領域。我的意思是，該領域一直存在一些政策上的不確定性。您還擁有 TriZetto 資產。您能否談談醫療保健產業的整體前景？特別是，鑑於 TriZetto 和你們正在進行的所有 AI 相關工作，你是否認為 BPaaS 在這方面蘊藏著更大的機會？任何關於醫療保健前景的看法。

Absolutely, absolutely. In fact, if you look at healthcare, I mean, if you take the last 20 years, the number of surgeons and the number of doctors has pretty much remained flat. But if you look at administrative costs, they've probably got up like 600% to 700%, number of administrators in that business. So transitioning that spend to predictive care, I think, is the future. We have 200 million-plus members on our TriZetto platform. We own the BPaaS cycle.

當然，當然。事實上，如果你看看醫療保健產業，我的意思是，如果你看看過去 20 年，外科醫生和醫生的數量基本上保持不變。但如果你看一下管理成本，你會發現該行業的管理人員數量可能已經增加了 600% 到 700%。我認為，將這部分支出轉移到預測性醫療才是未來。我們的TriZetto平台擁有超過2億位會員。我們掌控著BPaaS週期。

In fact, you have -- you answered my question. BPaaS is our hottest offering. It gives us the opportunity to not just share our platforms, but equally, the operational strength of running health care operations, I think, is an important consideration.

事實上，你已經回答我的問題了。BPaaS 是我們最熱門的產品。它不僅讓我們有機會共享平台，而且我認為，經營醫療保健業務的營運實力也是一個重要的考慮因素。

One of the reasons why our BPO business is 10%-plus growth this year is also because of BS -- so we are very, very excited about our BPaaS offering, AI-led instrumentation in our TriZetto business and our lead in health care. I mean we are probably the number one player in healthcare in the United States.

今年我們 BPO 業務成長超過 10% 的原因之一也是因為 BS——所以我們對我們的 BPaaS 產品、TriZetto 業務中的 AI 驅動的儀器以及我們在醫療保健領域的領先地位感到非常非常興奮。我的意思是，我們可能是美國醫療保健領域的第一大企業。

Jonathan Lee, Guggenheim Partners.

喬納森李，古根漢合夥公司。

Good to see the outperformance here. You called out last quarter that you were expecting the 4Q exit rate to be just under 4% at the high end of the outlook range. Given the outperformance this quarter, can you help bridge the gap between the 3.5% at the high end of your 4Q outlook today and the 4% exit rate you pointed to last quarter?

很高興看到它表現出色。上個季度你曾表示，預計第四季的退出率將略低於 4%，處於預期範圍的高端。鑑於本季業績表現優異，您能否幫助我們彌補您今天對第四季業績展望上限 3.5% 與上季您指出的 4% 退出率之間的差距？

Yeah. I think this is 2.5% to 3.5% is the view that we have of quarter four as we look at next few -- next couple of months. We have great momentum in terms of winning the large deals. We have been able to execute better in quarter three. And that will really decide -- I mean, continuing momentum on those factors will really decide where 2026 comes through. But overall, we are very happy with the way we have executed 2025.

是的。我認為，展望未來幾個月，我們對第四季的預期是 2.5% 到 3.5%。我們在贏得大單方面勢頭強勁。我們在第三季執行得更好了。而這將真正決定——我的意思是，這些因素的持續發展勢頭將真正決定 2026 年的走向。但總的來說，我們對 2025 年的執行情況非常滿意。

As I spoke in my opening remarks, when we gave guidance since then, the environment has been very, very dynamic and still to be able to come in the last quarter and guide above the original guidance range is very heartening. So we have executed well, and we hope we'll continue to do so as we move forward.

正如我在開場白中所說，自從我們給出業績指引以來，市場環境一直非常非常不穩定，但仍然能夠在最後一個季度給出高於最初指引範圍的業績指引，這令人非常鼓舞。所以我們執行得很好，希望我們能繼續保持這樣的狀態。

Can you help us also better understand your pyramid initiatives and how you're balancing the needs of clients while managing margins, particularly as you move into higher-value AI-related work in vectors two and three that may require higher skilled talent beyond that of freshers?

您能否幫助我們更了解您的金字塔計劃，以及您如何在滿足客戶需求的同時管理利潤，尤其是當您轉向更高價值的人工智慧相關工作（如第二和第三方向）時，這些工作可能需要比應屆畢業生更高技能的人才？

So we have been very vocal about the fact that we see actually freshers and AI a very complementary strategy. And we believe that expanding pyramid at the bottom in our industry really helps us accelerate the organization's journey on AI.

因此，我們一直非常明確地表示，我們認為應屆畢業生和人工智慧其實是一種非常互補的策略。我們相信，擴大我們產業底層金字塔的規模，確實有助於我們加速組織在人工智慧領域的發展。

So from that context, we more than doubled this year, the number of freshers we took last year to this year, and that journey will continue one from a cost management standpoint of pyramid, but even greater context is how we can accelerate the enterprise to become more AI-ready and AI builder, as Ravi spoke about. And also, we are now hiring freshers in the markets, which is primarily our principal market being the US. So we are doubling down on this with a broader pyramid and a shorter path to expertise.

因此，從這個角度來看，我們今年招收的新生人數比去年翻了一番還多，而且從金字塔式的成本管理角度來看，這一進程還將繼續，但更重要的背景是，正如 Ravi 所說，我們如何才能加速企業變得更加人工智能就緒，成為人工智能構建者。此外，我們現在正在招募應屆畢業生，主要市場是美國。因此，我們正在加倍努力，建造一個更廣闊的金字塔，並縮短通往專業技能的路徑。

Thank you. And that does conclude our question-and-answer session. I would like to turn the floor back over to Ravi Kumar for closing comments.

謝謝。我們的問答環節到此結束。現在我把發言權交還給拉維·庫馬爾，請他做總結發言。

Thank you so much for joining us today. We are very excited about our strategy of being an AI builder company. which is a combination of AI-led capability, platforms, intellectual property, and partnerships, which allow us to be on those two swim lanes, one on productivity, one on AI-led innovation with a much expansive, elastic and a more immersive opportunity to serve our clients. So we're very, very excited about our future, and thank you again for listening to us today.

非常感謝您今天加入我們。我們對自身作為人工智慧建立公司的策略感到非常興奮。該策略結合了人工智慧驅動的能力、平台、智慧財產權和合作夥伴關係，使我們能夠同時在兩個領域發展：一個領域是生產力，另一個領域是人工智慧驅動的創新，從而為客戶提供更廣泛、更靈活、更沉浸式的服務機會。所以我們對未來感到非常非常興奮，再次感謝大家今天收聽我們的節目。

Thank you. This concludes today's Cognizant Technology Solutions third quarter 2025 earnings conference call. You may now disconnect.

謝謝。本次 Cognizant Technology Solutions 2025 年第三季財報電話會議到此結束。您現在可以斷開連線。