GLOBANT S.A. (GLOB) 2026 Q2 法說會逐字稿

Good afternoon, and welcome to Globant's second-quarter 2026 earnings conference call. I am Arturo Langa, Investor Relations Officer at Globant. (Event Instructions) Please note this event is being recorded and streamed live on YouTube.

各位下午好，歡迎參加 Globant 2026 年第二季財報電話會議。我是 Globant 投資人關係主管 Arturo Langa。(活動說明) 請注意，本活動將被錄音，並於 YouTube 進行直播。

By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globent.com. We will begin with remarks by our Chief Executive Officer, Martin Migoya; our Chief Technology Officer, Diego Tartara; and our Chief Financial Officer, Juan Urthiague, followed by a Q&A, where they will be joined by our Chief Revenue Officer, Fernando Matzkin.

此時，您應已收到一份財報新聞稿。若尚未收到，我們的網站 investors.globent.com 提供下載。接下來將由我們的執行長 Martin Migoya、技術長 Diego Tartara，以及財務長 Juan Urthiague 發表談話，隨後進入問答環節；屆時我們的營收長 Fernando Matzkin 也將一同參與。

Before we begin, I would like to remind you that some of the comments on our call today may be deemed forward-looking statements. This includes our business and financial outlook, and the answers to some of your questions. Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC.

在開始之前，我想提醒各位，今天電話會議中的部分評論可能被視為前瞻性陳述。其中包括我們的業務與財務展望，以及對部分問題的回答。此類陳述受公司財報新聞稿及向美國證券交易委員會（SEC）提交之其他文件中所述風險與不確定性影響。

Please note that we follow IFRS accounting rules in our financial statements. During our call today, we will report non-IFRS or adjusted measures, which is how we track performance internally and the easiest way to compare Globent to our peers in the industry. You will find a reconciliation of IFRS and non-IFRS measures. At the end of the press release, we published on our Investor Relations website, announcing this quarter's results.

請注意，我們的財務報表遵循 IFRS 會計準則。在今天的電話會議中，我們將報告非 IFRS 或調整後指標，這是我們內部追蹤績效的方式，也是將 Globent 與同業進行比較最容易的方法。您將可看到 IFRS 與非 IFRS 指標之調節表。該調節表刊載於我們在投資人關係網站發布、用以公告本季業績的新聞稿末尾。

I will now turn the call over to Martin Migoya.

接下來我把電話交給 Martin Migoya。

Good afternoon, everyone, and thank you for joining us. Today, I want to talk about a change we are leading, a new way of creating value for our customers, delivering our work, a way of pricing it, which is already starting to compound.

各位下午好，感謝各位參與。今天我想談談我們正在引領的一項變革：一種為客戶創造價值、交付我們工作的全新方式，以及一種定價方式，而這一切已開始產生複利效應。

For more than 20 years, we have engineered the digital reinvention of the world's leading organizations, building the software, products, and platforms that run their businesses, delivered by dedicated, high-performing teams, and priced through on fixed-scope engagements or time and materials. That work remains the backbone of Globent. One year ago, I introduced you to AI Pods, a new AI-native revenue stream built on that foundation, but priced on the actual output and value we deliver or on consumption, rather than on the hours we bill.

二十多年來，我們為全球領先組織打造數位再造工程，建置支撐其業務運作的軟體、產品與平台；由專注且高績效的團隊交付，並以固定範圍專案或按工時與材料（time and materials）計價。這些工作仍是 Globent 的核心支柱。一年前，我向各位介紹 AI Pods：建立在該基礎之上的全新 AI 原生營收來源，但其定價依據是我們交付的實際產出與價值或依使用量計費，而非依我們開立帳單的工時。

As AI Pods deliver more work at higher margin for a similar price, our top line can understate the progress underneath it. As this grows, it will be relevant to assess annual recurring revenue, revenue per head, AI Pod margins, and client penetration alongside the total revenue line.

由於 AI Pods 能以相近價格交付更多工作、且毛利率更高，我們的營收表現可能低估了其背後的實質進展。隨著其規模擴大，除了總營收之外，評估年度經常性收入、每人營收、AI Pod 利潤率以及客戶滲透率也將變得重要。

Before I go further, let me be precise about two names you will hear all call. Glob.AI is the platform we opened to the market last week. AI Pods are the service units that live on it, run by AI agent workflows, and supervised by our experts. The revenue they create I will call Glob.AI ARR. Hold those three together. The platform, the pods, and the number. This quarter's revenues grew roughly 60% to $52.8 million, and we estimate that Glob.AI's ARR will surpass $110 million by year-end.

在我進一步說明之前，先精確界定本次電話會議中會反覆聽到的兩個名稱。Glob.AI 是我們上週向市場開放的平台。AI Pods 是在該平台上運作的服務單元，由 AI 代理工作流程驅動，並由我們的專家監督。它們所創造的營收，我將稱之為 Glob.AI ARR。請把這三者放在一起理解。平台、Pods，以及這個數字。本季該項營收約成長 60% 至 5,280 萬美元，我們估計 Glob.AI 的 ARR 將在年底前超過 1.10 億美元。

Let me walk you through it in that order. The model, the number that measures it, where the growth is coming from, how to read our reported revenue while both models run side-by-side, and where it already shows results. The technology services industry as a whole is growing at roughly flat rates right now. But flat is an average, and averages hide the real story. Inside that flat industry, we have found a growth runway, AI native services. And it is growing because it expresses what enterprises want from AI better than a traditional hours-based approach does.

我將依此順序帶各位了解。包括：這個模式、衡量它的數字、成長來自何處、在兩種模式並行時如何解讀我們所報告的營收，以及它已在哪些方面展現成果。整體科技服務產業目前的成長率大致持平。但持平只是平均值，而平均值會掩蓋真正的故事。在這個看似持平的產業中，我們找到了成長跑道：AI 原生服務。它之所以成長，是因為相較於傳統以工時計價的方法，它更能表達企業對 AI 的需求。

Clients can tell the difference, and a growing number are moving budgets accordingly, and more are choosing to work with us with this new model. As enterprises abstract away layer after layer of complexity, infrastructure, platform, software, some are now beginning to abstract away business services themselves.

客戶能分辨其中差異，且越來越多客戶正相應調整預算，也有更多客戶選擇以這個新模式與我們合作。隨著企業一層又一層地抽象化複雜度——從基礎設施、平台到軟體——其中一些企業如今也開始抽象化商業服務本身。

We think of this as service as software. Just like how the cloud transformed software infrastructure and provided predictable and recurring revenue, Glob.AI does for professional services. You turn on the outcome and pay for what you consume, with Globant's experts built in. It opens budgets we have not had access to before.

我們將其視為「服務即軟體」（service as software）。正如雲端改變了軟體基礎設施並帶來可預測且可重複的經常性收入，Glob.AI 也正在為專業服務做到同樣的事。您啟用成果並按使用量付費，同時內建 Globant 的專家能力。這讓我們得以觸及過去無法取得的預算。

Annual spending of the global professional services industry is estimated at more than $6 trillion, roughly 4 times the size of the IT services market, that Globant has been evaluated in. We are taking this deliberate decision to respect our current market, while expanding our offering to a larger total addressable market. We are steering clients toward the new model.

全球專業服務產業的年度支出估計超過 6 兆美元，約為 Globant 所被評估之 IT 服務市場規模的 4 倍。我們做出這項審慎決策：在尊重現有市場的同時，將我們的產品與服務擴展至更大的整體可服務市場（TAM）。我們正引導客戶轉向新模式。

Our AI native delivery system of AI pods has now been adopted by 45 of our clients in many of their projects. Today, practically everything we deliver carries AI. We do not count that as Glob.AI ARR, which only captures the revenue that is delivered and charged differently on the output, value, or consumption our clients receive, not on the hours behind it. It is a strict measure, and that is deliberate. When this number grows, it is not AI being bolted onto existing work. It is the business model itself changing.

我們以 AI Pods 為核心的 AI 原生交付系統，現已被 45 家客戶採用於其多個專案中。如今，我們幾乎所有交付內容都帶有 AI。但我們不將其計入 Glob.AI ARR；Glob.AI ARR 僅涵蓋那些以不同方式交付並計費的收入——依客戶獲得的產出、價值或使用量計價，而非依其背後投入的工時。這是一個嚴格的衡量標準，而這是刻意為之。當這個數字成長時，代表的不是在既有工作上加裝 AI。而是商業模式本身正在改變。

Glob.AI ARR reached $52.8 million as of June, up from $32.8 million in March, roughly 60% growth in a single quarter. We have seen plus 30% more productivity than with a typical engineer plus AI approach. Pipeline stands at $436.8 million, up from $352 million in Q1.

截至 6 月，Glob.AI ARR 達到 5,280 萬美元，高於 3 月的 3,280 萬美元，單季約成長 60%。我們看到的生產力較「典型工程師加上 AI」的方法高出 30% 以上。商機管線（pipeline）為 4.368 億美元，高於第一季的 3.52 億美元。

Adoption has reached 45% of our top 20 accounts. Gross margins on this model run close to 10 percentage points above our traditional delivery. We now expect to exit 2026 at no less than $110 million in Glob.AI ARR. That is the yardstick. AI native revenue becoming core to how we believe the market should value Globant, measured quarter after quarter.

採用率已達我們前 20 大客戶中的 45%。此模式的毛利率較我們傳統交付高出接近 10 個百分點。我們目前預期 2026 年底 Glob.AI ARR 不低於 1.10 億美元。這就是衡量標尺。AI 原生營收將成為我們認為市場應如何評價 Globant 的核心，並將逐季衡量。

These changes have affected Globant as a whole as well. Globant's revenue per head reached $95,800 on a run rate basis, up 9.7% year-over-year. We are delivering more value with the same talent and capturing it. Glob.AI ARR captures three of the biggest waves of demand in our industry. They are core modernization, experienced debt, and agentic process transformation. We have shared them with you on previous earnings calls. What changed is that all three now convert increasingly through AI pods.

這些變化也影響了整體 Globant。以年化運行率（run rate）計算，Globant 的每人營收達到 95,800 美元，年增 9.7%。我們以相同的人才交付更多價值並將其變現。Glob.AI ARR 捕捉了本產業三大需求浪潮。分別是核心現代化、經驗債（experienced debt），以及代理式（agentic）流程轉型。我們在先前的財報電話會議中已與各位分享過。改變之處在於，這三者如今愈來愈多透過 AI Pods 轉化落地。

Let me go through each one with you. One, core modernization. There is a technical debt backlog between $1.5 trillion and $2 trillion across the world's 2,000 largest public companies. It used to mean a large team billing hours over months. We can now deliver it as an outcome in less time. That is why clients are moving to the new model here first.

讓我逐一為各位說明。第一，核心現代化。在全球前 2,000 大上市公司中，技術債待辦量介於 1.5 兆至 2 兆美元。過去這通常意味著一個大型團隊按工時計費、耗時數月。如今我們可以在更短時間內以「成果」交付。這就是為什麼客戶會優先在此轉向新模式。

Two, experienced debt. Every customer-facing surface that has to be rebuilt for an AI-first world. Our Vercel and Claude-powered AI pods are turning multi-month rebuilds into same-week releases. Three, agentic process transformation. The largest opportunity, redesigning how a business runs around agents. The value is in the transformed process, not the hours, so this is where outcome pricing fits best.

第二，體驗債。所有面向客戶、必須為 AI 優先世界而重建的接觸面。我們由 Vercel 與 Claude 驅動的 AI pods，正把原本需要數月的重建，縮短為同一週即可上線。第三，代理式流程轉型。這是最大的機會：重新設計企業如何圍繞代理（agents）運作。價值在於被轉型後的流程，而非工時，因此這最適合採用成果定價。

Now, a word on our current position and how to interpret the top line while this shift is underway. For Q2, revenue was $614.4 million within our guided range, up 1.2% sequentially, and back to slight year-over-year growth. AI pod revenue makes up roughly 2% of our total revenue today, and we expect it to reach 4% by the end of the year. We keep seeing the pocket of growth I mentioned earlier, demand for AI pods.

接下來談談我們目前的狀況，以及在這項轉型進行期間，該如何解讀營收表現。第二季營收為 6.144 億美元，落在我們指引區間內，較前一季成長 1.2%，並回到小幅年增。AI pod 營收目前約占我們總營收的 2%，我們預期年底可達 4%。我們持續看到我先前提到的那個成長口袋：對 AI pods 的需求。

We are choosing to accelerate these migrations, even if it means a short-term impact on revenue, because over time, it creates more value for the client with predictable outcome-based consumption and more value for Globant with higher margins and access to more sophisticated projects. This quarter, 96% of our revenue came from repeat customers, and we grew our top 20 and top 50 clients by 6.6% and 6.9% year-over-year, respectively.

我們選擇加速這些遷移，即使短期可能對營收造成影響，因為長期而言，這能以可預測、以成果為基礎的消費模式為客戶創造更大價值，也能為 Globant 帶來更高毛利並取得更高階的專案機會。本季我們 96% 的營收來自回頭客；我們前 20 大與前 50 大客戶的營收分別年增 6.6% 與 6.9%。

This is concentrated where Glob.AI and AI pod penetration is highest. Our data and AI studio is now our second-largest studio by revenue, close to 11% of sales and growing close to 35% year-over-year. Our AI studios are increasingly selling AI native services alongside traditional staff augmentation and providing their depth.

這些成長集中在 Glob.AI 與 AI pod 滲透率最高的領域。我們的資料與 AI 工作室目前已成為營收第二大的工作室，銷售占比接近 11%，年增接近 35%。我們的 AI 工作室愈來愈常在傳統人力增補服務之外，同步銷售 AI 原生服務，並提供其專業深度。

Since that top 50 growth is a sign they understand these clients' industries well. Our core business is acting as the distribution engine that carries Glob.AI and the AI pods that run on it into large enterprises on relationships built over two decades. Pipeline and bookings are at a healthy level. Its composition is shifting toward AI, data, cloud, and integration work. Having said all this, we are operating in a tougher environment this quarter. Geopolitical pressure in our new markets, volatile oil prices, weighing on travel, and longer decision cycles in North America. Juan will take you through a revised outlook for the full year.

前 50 大客戶的成長，顯示我們對這些客戶所處產業有深刻理解。我們的核心業務，是作為分銷引擎，透過二十年建立的關係，將 Glob.AI 以及其上運行的 AI pods 帶入大型企業。商機管線與接單維持在健康水準。其組合正轉向 AI、資料、雲端與整合相關工作。儘管如此，本季我們所處的環境更具挑戰。新市場的地緣政治壓力、油價波動對旅遊的影響，以及北美更長的決策週期。Juan 將為各位說明我們對全年修訂後的展望。

Last week, we launched Glob.AI, and with that, we are opening this same model to any enterprise through a single self-service platform, so AI native services priced on output and value or on consumption become available to more of the market, not just our largest accounts.

上週我們推出了 Glob.AI；藉此，我們透過單一自助式平台，將同樣的模式開放給任何企業，使以產出與價值或以用量計價的 AI 原生服務，能觸及更廣泛的市場，而不僅限於我們最大的客戶。

Here is what that looks like in practice. Glob.AI is a single destination where an enterprise can find, deploy, and start consuming an AI pod without a months-long discovery process and a long ramp-up time. A client can log in, explain their technological opportunity and plan language, and the platform draws on Globant's entire network of technological solutions, partnerships, recommends AI pods, and enables clients to start building the same day.

以下是實際運作的樣貌。Glob.AI 是一個單一入口，企業無需經歷長達數月的探索流程與漫長的啟動期，就能找到、部署並開始使用 AI pod。客戶可以登入，說明其技術機會與以自然語言描述的計畫；平台會調用 Globant 全部的技術解決方案與合作夥伴網路，推薦 AI pods，並讓客戶當天即可開始建置。

It bridges the gap between mental throughput and making sound business decisions. Clients keep sovereignty over which models they use and where they run. These pods are built in cooperation with the companies defining this technology. Specific AI pods are engineered with name partners, secure code review with Anthropic, digital twin engineering on Nvidia Omniverse, prototype to product with Vercel, and enterprise integration with Salesforce and MuleSoft. The platform runs across the broader model ecosystem as well, Anthropic, OpenAI, Google, Azure, AWS, Nvidia, Meta, among others.

它彌合了「思考吞吐量」與做出健全商業決策之間的落差。客戶可保有主權，自行決定使用哪些模型以及在哪裡運行。這些 pods 是與定義此技術的公司共同打造。特定 AI pods 由具名合作夥伴共同工程化：與 Anthropic 進行安全程式碼審查、在 Nvidia Omniverse 上進行數位孿生工程、透過 Vercel 將原型推進到產品，以及與 Salesforce 與 MuleSoft 進行企業整合。該平台也可運行於更廣泛的模型生態系，包括 Anthropic、OpenAI、Google、Azure、AWS、Nvidia、Meta 等。

I am glad to announce that Sarab Narang is joining us as Glob.AI's CEO. Sarab is an accomplished AI and technology executive with more than 23 years of experience. He joins us from ServiceNow, where he led the commercialization of its AI business, and previously held senior AI leadership roles at AWS, where he helped build and scale AI platforms, including Amazon SageMaker and Amazon Bedrock. Earlier in his career, he built KPMG's AI and machine learning practice.

我很高興宣布 Sarab Narang 將加入我們，擔任 Glob.AI 的執行長。Sarab 是一位卓越的 AI 與科技高階主管，擁有超過 23 年經驗。他加入我們之前任職於 ServiceNow，負責其 AI 業務的商業化；更早之前在 AWS 擔任 AI 領導職務，協助打造並擴展 AI 平台，包括 Amazon SageMaker 與 Amazon Bedrock。在職涯早期，他也建立了 KPMG 的 AI 與機器學習業務。

None of what I have discussed so far works without the right partners. In June, we announced a multi-year alliance with Anthropic, becoming a preferred services partner in the Claude Partner Network. Since signing, we have moved quickly. Several Claude powered AI pods are already in production, and were showcased at our Globant Tech Summit in July. We are training thousands of Globers on Anthropic tools, and we have an active joint pipeline with several large financial institutions, airlines, and e-commerce companies.

我至今所談的一切，若沒有合適的合作夥伴都無法實現。6 月，我們宣布與 Anthropic 建立多年期策略聯盟，成為 Claude Partner Network 中的優先服務合作夥伴。簽約後我們迅速推進。多個由 Claude 驅動的 AI pods 已在生產環境上線，並於 7 月的 Globant Tech Summit 中展示。我們正在訓練數千名 Glober 使用 Anthropic 工具，並與多家大型金融機構、航空公司與電商公司建立活躍的聯合商機管線。

One year after our initial partnership, OpenAI has named Globant a selected partner in its new partner network. And with Vercel, clients can ship AI-built applications natively in a single click, turning multi-month projects into same-week deliveries. Together, we launched Vercel-powered AI pods, agentic units that design, develop, and modernize enterprise digital products on Next.js.

在我們最初合作一年後，OpenAI 已將 Globant 指定為其新合作夥伴網路中的入選合作夥伴。而透過 Vercel，客戶可一鍵原生交付由 AI 建置的應用程式，將原本數月的專案縮短為同一週交付。我們共同推出由 Vercel 驅動的 AI pods——能設計、開發並現代化企業數位產品的代理式單元，建構於 Next.js 之上。

FIFA is using AI pods powered by Glob.AI to scale its digital ecosystem into a continuous, personalized experience for football fans worldwide. Its key platforms recognize fan preferences across competitions, and, powered by AI pods, use real-time data to generate new experiences year-round. This quarter marked three years since the foundation of our partnership with British Airways, delivering a platform built for speed and continuous innovation.

FIFA 正使用由 Glob.AI 驅動的 AI pods，將其數位生態系擴展為面向全球足球迷的持續、個人化體驗。其關鍵平台能跨賽事辨識球迷偏好，並在 AI pods 的驅動下，利用即時資料全年生成新的體驗。本季也標誌著我們與英國航空（British Airways）合作滿三年，交付一個為速度與持續創新而打造的平台。

In June, British Airways reached an important milestone on this transformation journey with the launch of their new mobile app, following extensive testing to make every stage of the customer journey simpler and more intuitive, acting as a real-time travel companion. Positive customer feedback has highlighted the improved user experience, particularly the live flight notifications feature. And this is just the start.

6 月，英國航空在這段轉型旅程中達成重要里程碑，推出全新行動 App；在上線前經過廣泛測試，使客戶旅程的每個階段更簡單、更直覺，並作為即時的旅行夥伴。正面的客戶回饋凸顯了使用者體驗的提升，尤其是即時航班通知功能。而這只是開始。

We're extending the partnership with new features powered by our AI pods model, accelerating what we can deliver next. In the Gulf region, we are working with one of its largest financial institutions by building its first agentic bank. Powered by our AI pods model, intelligent agents will act across acquisition, onboarding, servicing, and risk, reshaping how the bank operates and how customers experience it.

我們正以由 AI pods 模式驅動的新功能延伸合作，加速我們下一步可交付的內容。在海灣地區，我們正與當地最大型的金融機構之一合作，打造其第一家代理式銀行。在我們 AI pods 模式的驅動下，智慧代理將橫跨獲客、開戶導入、服務與風險管理，重塑銀行的營運方式以及客戶的體驗。

GUT delivered a solid Q2 2026, culminating in another standout performance at the Cannes Lions International Festival of Creativity in June. The network earned 22 Lions, including a third consecutive Grand Prix for long-standing client Mercado Libre, the first agency-client partnership to achieve this milestone at the festival.

GUT 在 2026 年第二季交出穩健成績，並於 6 月坎城國際創意節（Cannes Lions International Festival of Creativity）再度以亮眼表現畫下句點。該網絡共獲得 22 座獅獎，其中包括為長期客戶 Mercado Libre 連續第三年奪得大獎（Grand Prix），成為該影展史上首個達成此里程碑的代理商—客戶合作夥伴關係。

GUT also launched new work for Google Chrome and Ray-Ban Meta, created the world's first clay bar for Stella Artois at Roland Garros during the French Open, and introduced Rimowa's For a Lifetime of Lives platform, celebrating craftsmanship through stories of longevity and evolution. We are building a meaningfully different services business, deliberately, with a growing base of revenue underneath it, and with a number I have asked you to hold us to every quarter.

GUT 亦為 Google Chrome 與 Ray-Ban Meta 推出新作品，並在法國網球公開賽（French Open）羅蘭加洛斯（Roland Garros）期間為 Stella Artois 打造全球首款黏土香皂，同時推出 Rimowa 的「For a Lifetime of Lives」平台，透過關於長久使用與演進的故事，致敬工藝精神。我們正有意識、循序漸進地打造一個真正與眾不同的服務型業務，在其下方建立日益成長的營收基礎，並且有一個我希望各位每一季都用來檢視我們的數字。

This next chapter also means disciplined choices today, including decisions on our cost base to fund the transition and protect our margins. I do not take those lightly, and I am grateful to our teams for the resolve they are showing. Thank you to our clients, our partners, and our Globers around the world, building this alongside us every day.

這個下一篇章也意味著我們今天必須做出自律的選擇，包括就成本結構作出決策，以資助轉型並保護我們的利潤率。我不會輕率看待這些決定，也感謝我們的團隊所展現的決心。感謝我們的客戶、合作夥伴，以及全球各地的 Globers，每天與我們一起打造這一切。

With that, Diego will show you the machine underneath. Thank you.

接下來，Diego 將向各位展示其背後的運作引擎。謝謝。

Thank you, Martin, and hello, everyone. Martin just laid out our strategic vision for Glob.AI and how it fundamentally transforms the way clients acquire our services. My focus today is on the underlying engine: the technology architecture, the operational mechanics and the first-mover advantage that makes this delivery model form at scale.

謝謝你，Martin，各位好。Martin 剛才闡述了我們對 Glob.AI 的策略願景，以及它如何從根本上改變客戶取得我們服務的方式。我今天的重點在於底層引擎：技術架構、營運機制，以及使這種交付模式能夠規模化落地的先行者優勢。

The legacy professional services model trades human hours or custom solutions, forcing engineers to solve the same foundational problems repeatedly. Glob.AI breaks that cycle by operating as an asset-based engine. Within the platform, we codified over two decades of enterprise engineering and industry domain knowledge into curated battle-tested playbooks. These are deterministic documented agentic workflows designed for production-grade reliability.

傳統的專業服務模式以人力工時或客製化解決方案進行交易，迫使工程師一再解決相同的基礎問題。Glob.AI 以資產化引擎運作，打破這個循環。在平台內，我們將超過二十年的企業工程與產業領域知識，編碼為經過精選且久經實戰驗證的作戰手冊（playbooks）。這些是具決定性、文件化的代理式工作流程（agentic workflows），以生產級可靠性為設計目標。

Because these agentic assets are modular and validated, we achieve extraordinary cross-industry compounding value. an IT root cause analysis workflow built for an airline client, for example, can be replatformed into a pharma supply chain or media distribution pipeline in a matter of weeks rather than months.

由於這些代理式資產具模組化且已驗證，我們得以在跨產業中累積出非凡的複利價值。舉例而言，為航空客戶打造的 IT 根因分析工作流程，可以在數週內重新平台化（replatform）到製藥供應鏈或媒體發行管線，而非以往需要數月。

AI Pods serve as our direct vehicle for monetizing this compounding IP, taking clients from a natural language challenge to production-ready deployment without the traditional friction. As we set out in introducing Glob.AI, raw LLM prompting produces significant token waste, hallucinated logic and expensive retry loops that includes additional time for human supervision. Glob.AI solves this through structured deterministic process optimization.

AI Pods 是我們將這種可複利的智慧財產（IP）變現的直接載體，讓客戶從自然語言提出的挑戰，無需傳統摩擦即可走到可上線的生產部署。正如我們在介紹 Glob.AI 時所指出，單純的 LLM 提示（prompting）會造成大量 token 浪費、產生幻覺式邏輯（hallucinated logic），以及昂貴的重試迴圈，並需要額外的人力監督時間。Glob.AI 透過結構化、具決定性的流程最佳化來解決這些問題。

Before an AI agent executes work, our platform automates context assembly, architecture mapping and data preparation, enforcing automated quality gates at every step. By optimizing the orchestration layer, we ensure that every token consumed yields verifiable production-ready output.

在 AI 代理執行工作之前，我們的平台會自動完成情境彙整、架構映射與資料準備，並在每一步強制執行自動化品質關卡。透過最佳化編排層（orchestration layer），我們確保每一個被消耗的 token 都能產出可驗證、可直接投入生產的成果。

At the same time, enterprise adoption hinges on control. Glob.AI's architecture routes intelligently across more than 140 LLMs, providing complete model independence, so clients are never locked into a single provider. Crucially, every transaction is locked within the client's dedicated token vault. This guarantees absolute token sovereignty. No client data is ever exposed or used to train third-party models, allowing organizations to compound their own institutional intelligence safely over time.

同時，企業採用的關鍵在於可控性。Glob.AI 的架構可在超過 140 個 LLM 之間進行智慧路由，提供完整的模型獨立性，讓客戶永遠不會被鎖定在單一供應商。更重要的是，每一筆交易都被鎖定在客戶專屬的 token 金庫中。這可確保絕對的 token 主權。任何客戶資料都不會被暴露或用於訓練第三方模型，使組織能隨時間安全地累積自身的制度性智慧。

We are seeing the impact of this platform model directly in our operational performance. By integrating specialized AI agents into continuous delivery workflows supervised by our experts, we are restructuring the software engineering life cycle. This leverage enables us to decouple enhancements in output, velocity and delivery from headcount growth. Furthermore, this enables us to layer on nonlinear and recurring revenue to the mix, with structurally better unit economics that will, over time, transform the business. This is the structural signature of a business moving up the value chain.

我們正從營運表現中直接看到這種平台模式的影響。透過將專門化的 AI 代理整合進由我們專家監督的持續交付工作流程，我們正在重塑軟體工程生命週期。這種槓桿效應使我們能將產出、速度與交付的提升，與人頭成長脫鉤。此外，這也讓我們能在營收組合中疊加非線性與經常性收入，並以結構性更佳的單位經濟（unit economics）在時間推進下改造整個業務。這正是企業向價值鏈上游移動的結構性特徵。

Now I would rather show than tell. Let me take you on a short Glob.AI tour. It starts simply. Once you have selected the plan and the AI Pods from the catalog or through chat with the Glob.AI agent, you would be able to access the project's module. From that moment on, you are ready to begin.

現在我更想用展示取代說明。讓我帶各位快速導覽一下 Glob.AI。一切從簡開始。當你從目錄中選擇方案與 AI Pods，或透過與 Glob.AI 代理聊天完成選擇後，你就能進入專案模組。從那一刻起，你就準備好開始了。

Glob.AI works at two levels: your organization and your projects. Your organization is the foundation where you can figure the tools and settings that apply to all your projects. Your projects are where the work happens, each with its own goals and one or more AI pods running simultaneously at different prices, which always include not only the tokens consumed, but also the human supervision required for the project.

Glob.AI 在兩個層級運作：你的組織與你的專案。組織層是基礎，你可以在此設定適用於所有專案的工具與設定。專案層則是實際工作的地方；每個專案都有其目標，並可同時運行一個或多個 AI Pods，價格各不相同，而費用始終不僅包含所消耗的 tokens，也包含專案所需的人力監督。

Let's start at the organization level. The first thing your organization needs is context, and you can give it directly from the tools your organization already uses. Connect your GitHub to read, write and open poll request directly on your repositories; Google Workspace to pull signals from Gmail, calendar and drive; Atlassian to sync with your Jira tickets and Confluence pages. You can also provide context through a document or a description.

我們先從組織層開始。你的組織首先需要的是情境（context），而你可以直接從組織既有使用的工具提供。連接你的 GitHub，以便直接在你的儲存庫中讀取、寫入並開啟拉取請求（pull request）；連接 Google Workspace，以從 Gmail、行事曆與雲端硬碟擷取訊號；連接 Atlassian，以與你的 Jira 工單與 Confluence 頁面同步。你也可以透過文件或描述來提供情境。

Once you're inside your project, everything is in one place. At the top, you see your project at a glance, resuming the totals of your project, how many AI Pods are active, your goals, your token consumption, your current spend with your limit and the start button that sets everything in motion.

一旦進入你的專案，所有內容都集中在同一處。在最上方，你可以一眼掌握專案概況：專案總覽、啟用中的 AI Pods 數量、你的目標、token 消耗量、目前支出與你的上限，以及啟動按鈕（start button），按下後即可讓一切開始運作。

Right below, your customized dashboard also gives you four key metrics. Selecting the period, you can see the spend, tokens used, tasks total and artifacts produced. Beneath that, a quick summary, your active goals, the units of work in progress, always visible at a glance. And finally, your AI Pod fleet, the specialized teams running your delivery.

在其下方，你的客製化儀表板也提供四個關鍵指標。選擇期間後，你可以看到支出、已使用 tokens、任務總數與產出工件（artifacts）數量。再往下，是快速摘要、你目前啟用的目標，以及進行中的工作單元，皆可一眼可見。最後是你的 AI Pod 艦隊，也就是負責交付的專業化團隊。

On the right is your communication channel, the Glob.AI agent. Just describe what you need in plain language or start with one of the suggestions below. You can also mention your forward deployed engineer, the Globant expert assigned to your project and your direct line to the human overseeing every step. Whenever you need to communicate, you're one message away from your expert.

右側是你的溝通管道：Glob.AI 代理。你只要用白話描述需求，或從下方的建議之一開始。你也可以提及你的前線派駐工程師（forward deployed engineer），也就是指派到你專案的 Globant 專家，並作為你與全程人力監督者之間的直接聯繫窗口。只要你需要溝通，傳一則訊息就能聯繫到你的專家。

Goals are the units of work your AI Pods will execute. And you create them by simply telling the agent what you want to achieve. You can connect the repository and let the agent analyze your code base directly. You can describe your needs in plain language or you can attach a document and let the agent extract the requirements from there.

目標（Goals）是你的 AI Pods 將要執行的工作單元。你只要告訴代理你想達成什麼，就能建立目標。你可以連接儲存庫，讓代理直接分析你的程式碼基底（code base）。你可以用白話描述需求，或附上一份文件，讓代理從中擷取需求。

Either way, the agent proposes the goals, you review them, you approve them. And if something needs to change, you tell it directly or bring in your expert, always available in the chat with full context on your project. When you're ready, you say start. That single action locks in your project and hands it to the forward deployed engineer who supervises every step of what comes next.

無論哪種方式，代理會提出目標，你進行審閱，然後核准。如果需要調整，你可以直接告訴它，或把你的專家拉進來；專家會在聊天中隨時待命，並對你的專案具備完整情境。當你準備好時，你只要說開始（start）。這個單一動作會鎖定你的專案，並將其交給前線派駐工程師，由其監督接下來每一步的執行。

Artifacts is your shared workspace for project files. Here, you'll find every document, spec, ABR or implementation summary produced by your AI Pods, ready to preview with a single click. You and your FDE can all upload files here, keeping everything in one place. Some artifacts will also be delivered directly to your GitHub repository as commits or pull requests. Clicking on your name gives you access to your notification settings. You choose how Glob.AI reaches you: e-mail, WhatsApp or Telegram. And you decide which events trigger each channel, approvals waiting on you, actions required, new deliverables or run updates.

Artifacts 是您用於專案檔案的共享工作區。在這裡，您可以找到由您的 AI Pods 產出的每一份文件、規格、ABR 或實作摘要，皆可一鍵預覽。您與您的 FDE 都可以在此上傳檔案，將所有內容集中於同一處。部分 artifacts 也會以提交（commit）或拉取請求（pull request）的形式，直接交付到您的 GitHub 儲存庫。點擊您的姓名即可進入通知設定。您可選擇 Glob.AI 與您聯繫的方式：電子郵件、WhatsApp 或 Telegram。並由您決定哪些事件會觸發各通道，例如等待您核准的事項、需要採取的行動、新的交付物或執行更新。

Clicking on your organization gives you a complete control panel with four tabs: Overview, with all the general information; Members, where you manage your team; Billing, your full financial picture; and last, Usage, a breakdown of consumption for the current cycle. The capability behind Glob.AI is not built on theory. It reflects what we have been proving on the ground.

點擊您的組織即可進入包含四個分頁的完整控制面板：Overview（總覽），提供所有一般資訊；Members（成員），用於管理您的團隊；Billing（帳務），呈現完整財務概況；最後是 Usage（使用量），提供當前週期的消耗明細。Glob.AI 背後的能力並非建立在理論之上。它反映了我們在第一線持續驗證的成果。

In our previous calls, we shared how early AI Pods deployments drove milestone efficiency gains whether accelerating drug discovery research at PharmaMar 15-fold, compressing supply chain contract cycles by 40% at YPF or reducing legacy migration timelines from 14 months down to two.

在先前的電話會議中，我們分享了早期 AI Pods 的部署如何帶來里程碑效率提升：例如在 PharmaMar 將藥物探索研究加速 15 倍、在 YPF 將供應鏈合約週期縮短 40%，或將既有系統遷移時程從 14 個月縮短至 2 個月。

What makes Glob.AI so significant today is that those custom high-impact successes are no longer bespoke projects. We have productized those learnings into our standard catalog. Backed by our deep co-engineering alliances with hyperscalers and model providers, Glob.AI turns those proven enterprise outcomes into an on-demand, repeatable capability accessible to every client from day 1.

使 Glob.AI 在今日格外重要的是，這些客製化的高影響成功案例不再是量身打造的專案。我們已將這些經驗產品化，納入我們的標準型錄。在與超大規模雲端業者（hyperscalers）及模型供應商的深度共同工程聯盟支持下，Glob.AI 將這些已驗證的企業成果轉化為可隨需取得、可重複的能力，讓每位客戶自第 1 天起即可使用。

We have built the underlying platform, secured the governance framework and proven the economics at scale. Everything I just described is what compounds behind one number: Glob.AI ARR. We look forward to driving this next chapter together. Thank you very much.

我們已建置底層平台、確立治理框架，並在規模化下驗證其經濟效益。我剛才描述的一切，最終都匯聚並體現在一個數字之中：Glob.AI ARR。我們期待與各位共同推動下一個篇章。非常感謝。

Hello, and good afternoon, everyone. During Q2, we delivered on our revenue guidance, accelerated our AI Pods adoption, launched Glob.AI, grew our top line sequentially and maintained a prudent balance sheet position. We grew on a quarter-over-quarter basis in 5 out of our 8 verticals. And importantly, we grew markedly above company average in our top 50 and top 20 cohorts. Also, in response to observed market volatility, we took actions on our cost structure. I will review our results and then walk you through our updated outlook.

各位好，下午好。在第二季，我們達成營收指引、加速 AI Pods 的採用、推出 Glob.AI、營收較前一季成長，並維持審慎的資產負債表狀況。我們在 8 個垂直領域中的 5 個，實現了季對季成長。更重要的是，我們在前 50 與前 20 客戶群的成長顯著高於公司平均。此外，因應觀察到的市場波動，我們也對成本結構採取了行動。我將回顧本季結果，並帶各位了解我們更新後的展望。

Revenue was $614.4 million, within our guided range, slightly up year-over-year, up 1.2% sequentially. On a year-over-year basis, Q2 revenues included 80 basis points of FX tailwind. From a geographical standpoint, compared to the prior year period, Europe and Latin America expanded by 6.8% and 5.9%, respectively. Conversely, North America experienced a 2.4% contraction and new markets saw a 17.7% decrease.

營收為 6.144 億美元，落在我們指引區間內，年對年小幅成長，季對季成長 1.2%。以年對年來看，第二季營收包含 80 個基點的匯率順風。從地理區域來看，與去年同期相比，歐洲與拉丁美洲分別成長 6.8% 與 5.9%。相對地，北美下滑 2.4%，新市場則下降 17.7%。

The new market segment represented a consolidated drag of roughly 115 basis points to the year-over-year revenue growth figure. Due to the ongoing conflict, this specific geography suffered unexpected project delays over the course of the second quarter.

新市場部門對年對年營收成長率造成約 115 個基點的合併拖累。由於持續的衝突，該特定地理區域在第二季期間出現了非預期的專案延遲。

Our cohort performance remains the highlight. Top 50 clients grew 6.9% on a year-over-year basis, top 20 at 6.6%, and top 10 at 4.4%, all well above company average, in line with our 100 Squared strategy. 16 out of our top 20 relationships are showing positive year-over-year growth, and we continue to scale recently signed large deals.

我們的客戶群（cohort）表現仍是亮點。前 50 大客戶年對年成長 6.9%，前 20 大成長 6.6%，前 10 大成長 4.4%，皆明顯高於公司平均，並符合我們的 100 Squared 策略。前 20 大關係中有 16 個呈現年對年正成長，我們也持續擴大近期簽署的大型交易規模。

Adjusted gross margin was 36.5%, slightly down as USD weakness accelerated, primarily impacting our largest delivery center, Colombia. And our utilization remained below our targets. Adjusted SG&A accounted for 18.6% of sales, while adjusted operating margin was 30.2%, below our guided range and driven by the impact on margins.

調整後毛利率為 36.5%，略為下降，原因是美元走弱加速，主要影響我們最大的交付中心——哥倫比亞。而我們的稼動率仍低於目標。調整後 SG&A 佔銷售額 18.6%，調整後營業利益率為 30.2%，低於我們的指引區間，主要受毛利率影響所致。

In response to these conditions and to optimally align for subsequent expansion, we initiated a business optimization initiative in Q2. Through this initiative, we ensure the acquisition and retention of the capabilities required for our AI-focused strategy while simultaneously rightsizing our cost baseline to the prevailing market landscape.

為因應上述情況並最佳化對後續擴張的配置，我們在第二季啟動了一項業務優化計畫。透過此計畫，我們在確保取得並留任 AI 聚焦策略所需能力的同時，也將成本基礎調整至符合當前市場環境的適當規模。

The main actions under this plan included a comprehensive review of our workforce to align skills and size with our strategic priorities, a consolidation of our global office footprint based on an analysis of our facilities and lease contracts, a strategic prioritization of our delivery centers to support future expansion.

此計畫下的主要行動包括：全面檢視人力，以使技能與規模符合我們的策略優先事項；根據對設施與租賃合約的分析，整併全球辦公據點；以及策略性地優先配置交付中心，以支援未來擴張。

In connection with these actions, we recorded a onetime charge of $32.3 million in the second quarter. And we expect some actions to flow into Q3, which will be critical in protecting our profitability in the short term given the current FX headwinds we are facing, and will be reinvested to fuel our growth engines, specifically our AI platform development and our people.

配合這些行動，我們在第二季認列了一次性費用 3,230 萬美元。我們預期部分行動將延續至第三季；在我們面臨當前匯率逆風的情況下，這對於短期內保護獲利能力至關重要，並將再投資以驅動我們的成長引擎，特別是 AI 平台開發與人才。

Despite FX headwinds, we plan to improve margins with the additional efficiencies planned for Q3 and increasing our AI Pods in the mix, which operate with margins above company average. Adjusted net income came in at $60.3 million with a 9.8% adjusted net income margin. Adjusted diluted EPS ended at $1.40.

儘管存在匯率逆風，我們仍計畫透過第三季規劃的額外效率提升，以及提高 AI Pods 在組合中的占比來改善利潤率；AI Pods 的利潤率高於公司平均。調整後淨利為 6,030 萬美元，調整後淨利率為 9.8%。調整後稀釋每股盈餘（EPS）為 1.40 美元。

Our balance sheet remains a source of strength. We ended the quarter with $168.8 million in cash and short-term investments and $253.1 million in net debt. Free cash flow for the quarter was $12.6 million, and free cash flow for the first half of 2026 reached $48.7 million, a record for the company.

我們的資產負債表仍是強項。本季末現金與短期投資為 1.688 億美元，淨負債為 2.531 億美元。本季自由現金流為 1,260 萬美元，2026 年上半年自由現金流達 4,870 萬美元，創公司紀錄。

On capital allocation, the share repurchase program our Board authorized in May, up to $125 million over six quarters, is active. At today's valuation, buying Globant remains one of the highest return investments available to us as the market is pricing Globant as a legacy services company in a soft cycle when what we are is the fastest-scaling AI-native delivery platform in our industry. At the current valuation, the company is trading at double-digit free cash flow yield on a normalized free cash flow basis.

在資本配置方面，董事會於 5 月核准的庫藏股回購計畫（六個季度內最多 1.25 億美元）已啟動。以目前估值來看，回購 Globant 仍是我們可選擇的最高報酬投資之一；因為市場在景氣偏弱的週期中，將 Globant 以傳統服務公司定價，但我們實際上是本產業擴張最快的 AI 原生交付平台。以目前估值計算，在常態化自由現金流基礎上，公司正以兩位數的自由現金流殖利率交易。

Now let me turn to our outlook. Three external factors have primarily impacted our May expectations, and our revised guidance incorporates all three. In May, the lower end of our guidance contemplated a significant deterioration in our new markets region that, at the time, was not reflected in our forecast. That scenario materialized, and our expectations for the second half of the year have now changed in the region. Our commitment to the region is long term and important relationships there continue to grow. But the prudent assumption today is that this environment persists in the short term.

接下來談談我們的展望。有三項外部因素主要影響了我們 5 月的預期，而我們修訂後的指引已將三者全數納入。在 5 月時，我們指引區間的下緣已考量新市場區域可能出現顯著惡化，而當時該情境尚未反映在我們的預測中。該情境已成真，因此我們對該區域下半年的預期已經改變。我們對該區域的承諾是長期且重要的，當地的重要客戶關係仍在成長。但在當下較為審慎的假設是，短期內此環境仍將持續。

Second, we have seen some of the knock-on effects from oil prices, pressuring the travel ecosystem. Some of our travel clients have slowed the pace of their transformation programs to protect their own P&Ls, even as others in the same industry accelerate with us. We believe this is a deferral of ramps, and we expect this revenue to return as industry volatility dissipates.

第二，我們已看到油價帶來的一些連鎖效應，對旅遊生態系造成壓力。我們的一些旅遊客戶為了保護自身的損益表（P&L），已放緩其轉型計畫的推進速度，即便同一產業中的其他客戶正與我們加速推進。我們認為這只是延後擴量（ramp）的時點，並預期隨著產業波動消退，這部分營收將回流。

Finally, we continue to observe protracted cycles in discretionary decision-making. As a result of the above, we are revising our expectations for the second half of the year. For the third quarter of 2026. We now expect revenue to be between $607 million and $615 million. We expect a non-IFRS adjusted operating margin between 13.5% and 14.5%, and the IFRS effective income tax rate in the 21% to 23% range. Adjusted diluted EPS is expected to be between $1.43 and $1.53 per share, assuming an average of 43.2 million diluted shares outstanding.

最後，我們持續觀察到在可自由裁量的決策上，決策週期拉長。基於上述因素，我們正在修正對今年下半年的預期。就2026年第三季而言。我們目前預期營收將介於6.07億美元至6.15億美元之間。我們預期非IFRS調整後營業利益率介於13.5%至14.5%，且IFRS有效所得稅率落在21%至23%的區間。在假設平均稀釋流通股數為4,320萬股的情況下，調整後稀釋每股盈餘（EPS）預期介於每股1.43美元至1.53美元。

With respect to the full year, we are revising our revenue guidance to a range of $2.428 billion to $2.462 billion, from $2.462 billion to $2.508 billion previously. In terms of profitability, we now expect our adjusted operating margin for the full year to be between 13.5% and 14.5%, driven by the increasing USD weakness. The IFRS effective income tax rate is expected in the 21% to 23% range. We now expect adjusted diluted EPS of $5.75 to $6.15, assuming 43.6 million average diluted shares.

就全年而言，我們將營收指引修正為24.28億美元至24.62億美元的區間，先前為24.62億美元至25.08億美元。在獲利能力方面，我們目前預期全年調整後營業利益率介於13.5%至14.5%，主要受美元走弱幅度加大所帶動。IFRS有效所得稅率預期落在21%至23%的區間。在假設平均稀釋股數為4,360萬股的情況下，我們目前預期調整後稀釋每股盈餘為5.75美元至6.15美元。

We expect strong free cash flow generation in the second half, consistent with our seasonality. And our capital allocation priorities are unchanged: the repurchase program and the continued build-out of AI Pods. The business optimization initiative we carried out this quarter will be visible in our margins as we exit the year, positioning us to enter 2027 with a leaner cost base, record revenue per Glober and the highest margin delivery model, AI Pods, approaching by year-end close to 4% of revenue on a run rate basis.

我們預期下半年將有強勁的自由現金流產生，符合我們的季節性。我們的資本配置優先順序維持不變：股票回購計畫，以及持續擴建AI Pods。我們本季推動的業務優化計畫，將在我們年底退出時反映於利潤率上，使我們能以更精實的成本基礎、每位Glober創下的營收新高，以及最高毛利的交付模式（AI Pods）進入2027；按年末的運行率（run rate）計算，AI Pods接近占營收的4%。

To conclude, the transition to AI Pods accelerated, we achieved record productivity, and we performed strongly within our top clients. The strong demand we see in AI Pods validates our industry view, one we feel will transform in a positive way. We will be laser-focused on this transition of our delivery model in order. Thank you for your continued support.

總結來說，向AI Pods的轉型加速，我們達成了創紀錄的生產力，並在我們的主要客戶中表現強勁。我們在AI Pods看到的強勁需求，驗證了我們對產業的看法，我們認為這將以正向方式帶來轉變。我們將高度聚焦於推動交付模式的這項轉型，以便。感謝各位持續的支持。

Thank you, Juan, and hi, everyone. (Operator Instructions)

謝謝你，Juan，大家好。(接線員指示)

Bryan Bergin, TD Cowen.

Bryan Bergin，TD Cowen。

I wanted to ask on the business transition. So you're showing strong sequential growth in pods, now target of $110 million. I think that's up from $60 million to $100 million before. Based on what you're seeing here, just how long are you anticipating this transition period to be as Glob.AI and the pod model scales whereby it can drive a reacceleration in the overall company trajectory?

我想就業務轉型提問。你們展示了Pods的連續季成長強勁，目前目標為1.10億美元。我認為這是從先前的6,000萬美元到1.00億美元上調而來。根據你們目前看到的情況，隨著Glob.AI與Pod模式擴張並能推動公司整體成長軌跡再加速，你們預期這段轉型期大概會持續多久？

And I guess, as it relates to your revised revenue outlook for '26, I think the midpoint of the constant currency forecast is down just under 2%. How much of that is intentional impact as you move under this engagement model versus macro headwinds on the business?

另外，關於你們修正後的2026年營收展望，我認為以固定匯率（constant currency）計算的預測中位數下調了略低於2%。其中有多少是你們轉向這種合作／接案模式所刻意帶來的影響，而非宏觀逆風對業務造成的影響？

Okay. Let me tackle the first one, a very important question. I think that the transition to the new model is something that we are doing it in a deliberate way, and it's something that we will keep on executing quarter-over-quarter. Honestly, the demand that we have seen and the acceptance of the model and the positive signs we are seeing from the market are very encouraging. Still is a small percentage, but we think that we will keep on accelerating this.

好的。我先回答第一個，這是非常重要的問題。我認為向新模式的轉型是我們以審慎、有計畫的方式在做的，而且我們會一季接一季持續執行。坦白說，我們看到的需求、對該模式的接受度，以及市場釋出的正面訊號，都非常令人鼓舞。目前占比仍小，但我們認為會持續加速。

Now if you ask me, I mean, if the revenue from the new markets wouldn't be affected, we'll be already in the positive growth side without the need of reviewing the whole forecast for the year. So I think it's, overall, it's a very positive movement, and it will accelerate a lot of the growth. Probably by the end of next year, we will see a pretty strong effect of that kicking in.

如果你問我，我的意思是，如果新市場的營收沒有受到影響，我們其實已經會回到正成長的一側，而不需要重新檢視全年預測。所以我認為整體而言這是一個非常正向的動向，並將大幅加速成長。大概到明年年底，我們會看到相當明顯的效果開始顯現。

Now I cannot say right now. I don't think it's a piece of information we can describe now in a very exact way. So with that caveat, I will let the second part to Juan.

不過我現在無法下定論。我不認為這是我們目前能非常精確描述的資訊。在此前提下，我把第二部分交給Juan。

Bryan, so the guidance for the year stands now at 2,445 at the midpoint. That is minus 0.4% -- minus -- sorry, minus 0.4%. And the FX tailwind there is about 70 basis points. So on any constant currency, you would be talking about 1.1.

Bryan，今年的指引中位數目前是24.45億美元。這是-0.4%——-——抱歉，是-0.4%。而匯率（FX）順風約為70個基點。因此以固定匯率計算，你談的是約1.1。

Now when we look at the guidance change, the majority of it is explained by a reduction in the forecast for the new market business. The week after we reported back in May, there was all this news from Saudi, reducing budgets, delaying projects and things like that. And as you know, it's a market that we have been expanding quite nicely over the last few years. And we will continue to do so. We see a lot of deals that are just getting postponed or getting slowed down, but not canceled at all. I mean we keep on having very interesting conversations. So we are confident about the recovery of that market in the near future.

現在，當我們看指引變動時，其中大部分可由新市場業務預測下修來解釋。我們在5月回報後的那一週，沙烏地那邊出現了各種消息，包括縮減預算、延後專案等等。如你所知，這是我們過去幾年擴張得相當不錯的市場。我們也會持續這麼做。我們看到很多交易只是被延後或放慢，但完全沒有被取消。我的意思是，我們仍持續進行非常有意思的洽談。因此我們對該市場在不久的將來復甦有信心。

So half of the guidance revision is driven by that. About $10 million is also somehow related to what is happening there because the increase in oil prices impacted some of our businesses in travel and hospitality, and that implied a reduction in the second part of the year forecast for some of those customers.

因此，指引修正有一半是由此所驅動。另外約1,000萬美元也在某種程度上與那邊正在發生的事情相關，因為油價上漲影響了我們在旅遊與餐旅（hospitality）的一些業務，這也意味著我們對部分客戶下半年預測有所下調。

And then the rest is a little bit of a mix between some assumptions we are doing on certain migrations plus the overall business environment and where we are right now. But again, I think -- and it's important to also look at how the new business and the part of the business that we are pushing very, very hard is evolving. Yes, it is still small. But when you start to compound at 40%, 50% quarter-over-quarter rates, very quick it starts to become more relevant.

其餘部分則是一些混合因素，包括我們對某些遷移（migration）的假設，以及整體商業環境與我們目前所處的位置。但再次強調，我認為同樣重要的是要看我們正在非常、非常用力推動的新業務與那部分業務的演進情況。是的，目前仍然很小。但當你開始以每季40%、50%的速度複利成長時，很快就會變得更具重要性。

And as you pointed out, we had been talking about $60 million to $100 million for this year. Now we are already over $52 million and with very good visibility of the second half of the year. Because we are kind of passing through the first initial stage of trying and testing and understanding what it means to work with an AI Pod. And many of our top customers, actually 45% of the top 20, are already using it. And what that means is that those customers are starting to scale. So we feel confident about the ability to scale this business to over $110 million by the end of the year.

如你所指出的，我們先前談的是今年6,000萬美元到1.00億美元。現在我們已超過5,200萬美元，且對下半年有非常好的能見度。因為我們正逐步走過最初的嘗試、測試與理解與AI Pod合作意味著什麼的階段。而我們的主要客戶中，前20大客戶有45%已在使用。這代表這些客戶正開始擴大規模。因此，我們對在年底前將這項業務擴大到超過1.10億美元的能力充滿信心。

Okay. Just a follow-up here. On the optimization you took, can you just talk about the savings you anticipate from those programs?

好的。這裡再追問一下。關於你們採取的優化措施，能否談談你們預期這些計畫將帶來多少節省？

Yes. Basically, what we are doing here is we have been reviewing our workforce and aligning that to the current level of demand and also to the current needs of the business with the new models that we have in front of us, and also with the skill sets that are required with a new way of delivering services that we have established. And because of that, we had to make some changes in the organization. Also in terms of delivery centers, we optimized, again, our delivery centers. The impact in the second quarter of that was roughly $32 million. We're expecting around $20 million to $25 million for the third quarter, and that will finalize the program for the year.

是的。基本上，我們正在做的是檢視我們的人力配置，並使其與目前的需求水準，以及在我們面前的新模式下業務的當前需求對齊，同時也與我們已建立的新服務交付方式所需的技能組合對齊。因此，我們必須在組織上做出一些調整。另外，在交付中心方面，我們也再次對交付中心進行了優化。這在第二季的影響約為3,200萬美元。我們預期第三季約為2,000萬至2,500萬美元，而這將完成今年的計畫。

We think that that is going to help us first save money, because, otherwise, we would have had part of that talent pool -- or part of that talent -- in the talent pool and without the possibility of allocating them to new projects maybe. And second, it's going to help us offset a massive FX headwind that we are seeing because of the US dollar weakness. I mean if you look at our largest development center, which is Colombia, since the election of the new President, it appreciated almost 15%. And that is a massive, massive impact on our numbers.

我們認為這首先會幫助我們省錢，因為否則，我們可能會有部分人才——或部分人力——留在人才庫中，卻可能無法分配到新的專案。其次，這將幫助我們抵消因美元走弱而面臨的巨大匯率逆風。我的意思是，如果你看我們最大的開發中心——哥倫比亞——自新總統當選以來，貨幣升值了將近15%。這對我們的數字造成非常、非常巨大的影響。

So we are going to offset that we are going to invest more. As we were discussing in the call, we just announced a new COO for our -- sorry, Glob.AI business, and we have to invest in that business just because we believe that's the future of the company. So we will be using the money for that, and that will save us costs that we would have had otherwise.

所以我們會一方面去抵消，另一方面也會加大投資。正如我們在電話會議中討論的，我們剛宣布為我們的——抱歉，Glob.AI 業務——任命了一位新的營運長（COO），而我們必須投資這項業務，因為我們相信那是公司的未來。因此，我們會把資金用在那裡，而這也會為我們節省原本可能會發生的成本。

Tien-Tsin Huang, JPMorgan.

黃天賜（Tien-Tsin Huang），摩根大通。

I think -- I want to ask on the optimization. I just want to make sure I understand just what -- like you said, Martin, you're taking this decision very seriously. What areas were impacted exactly? How much of it was influenced by what you saw in surprising you in May versus the shift to the new model? Or is it really more about the delivery centers and better aligning yourself with some of the FX and inflation trends like you talked to with Colombia. I just want to better understand that.

我想——我想問一下關於優化。我只是想確認我理解正確——就像你說的，Martin，你非常嚴肅地看待這個決定。具體哪些領域受到影響？其中有多少是受到你們在5月看到、讓你們意外的情況所影響，相較於轉向新模式的因素？或者其實更多是關於交付中心，以及如你提到哥倫比亞那樣，讓自己更好地與匯率與通膨趨勢對齊？我想更清楚地理解這點。

The whole program has like different reasons, right? And you see that on one side, we are migrating to this new model that requires a certain type of Forward Deployed Engineers and certain type of AI engineers that are slightly different from what we used to have, so there's a transition on the talent that we are seeing that is causing one of the reasons of the optimization.

整個計畫有不同的原因，對吧？你會看到，一方面，我們正在遷移到這個新模式，它需要某種類型的前線部署工程師（Forward Deployed Engineers）以及某種類型的AI工程師，這些與我們過去擁有的人才略有不同，所以我們正在經歷人才的轉換，這是造成優化的原因之一。

Also, we are seeing like also a transition on the demand of the traditional business. The demand of the traditional business is moving away from web testing into more data and more cloud and implementation. And that transition also created some demand of new profiles that we didn't have that much before and we needed to start training and retraining. So the effect has that.

另外，我們也看到傳統業務需求正在轉變。傳統業務的需求正從網頁測試轉向更多資料、更多雲端以及導入實施。而這種轉變也帶來了對新型人才輪廓的需求——我們以前沒有那麼多——因此我們需要開始培訓與再培訓。所以會有這樣的影響。

Also, it has been -- the impact of several programs and things to run more efficiently the company, as you saw, the increase on the revenue ahead has a lot of -- has a big message inside that as we're becoming more efficient to deliver our revenue. So it's an effort that has like many different components inside of it. I don't know, Juan, if you want to add anything to that?

此外，這也包含了多個計畫與措施的影響，目的是讓公司運作更有效率；如你所見，人均營收的提升背後有很多——其中傳達了一個很重要的訊息：我們在交付營收方面變得更有效率。所以這是一項包含許多不同組成部分的努力。我不知道，Juan，你是否想補充什麼？

No. I think -- I mean, it's basically -- it's a real kind of -- not really reshuffle. Maybe reskilling our workforce to the new type of demand, also to the new type of services that we are seeing -- that we are providing to our customers through the airports. You definitely require different skill set.

沒有。我想——我的意思是，基本上——這是一種真正的——不完全算是重新洗牌。也許是讓我們的員工重新培訓（reskilling），以符合新的需求類型，也符合我們看到的——我們透過機場為客戶提供的——新型服務。你確實需要不同的技能組合。

And also, we need to protect our margins. We need to make sure that we've set all the US dollar weakness that impacts our Latin America business and also make space from the investments that will be required in Glob.AI.

而且，我們需要保護我們的利潤率。我們需要確保能抵消美元走弱對我們拉丁美洲業務的影響，同時也要為在 Glob.AI 所需的投資騰出空間。

How much was the FX impact in the last year?

過去一年匯率（FX）的影響有多大？

If we were to look at all the currencies in Latin America for the last 1.5 years to 2 years, we are talking an overall impact just for the FX of about 4-percentage-points. Now we have -- of course, we have been able to increase our revenue per head that help us offset part of that. And we also made some efficiencies last year that also helped us. But the magnitude of the headwind that we have suffered in Latin America has been very, very significant and impacting our margins.

如果我們看過去1.5年至2年拉丁美洲所有貨幣的情況，僅就匯率而言，整體影響大約是4個百分點。當然，我們也能提高人均營收，這有助於抵消其中一部分。我們去年也做了一些效率提升，同樣有所幫助。但我們在拉丁美洲承受的逆風幅度非常、非常顯著，並且正在影響我們的利潤率。

Yes. I appreciate that. And it's out of your control, so it's good to get in front of it. Just on the -- just quickly thinking about the model and Glob.AI, I enjoyed hearing from everybody and Diego. Looking back over Globant's history, I always look at 50 Squared account approach as being really, really important. So thinking about Glob.AI and how this ramps, can you just give us an idea of what the revenue per could be from a client perspective as you penetrate your top 10, 20, 30, as you learn? Is there any analogy or parallel that we can draw back to how Globant under the prior model and assign that to the new model? Just trying to better understand how this can ramp beyond some of the metrics you gave for this year?

是的。我很感謝這些說明。而且這不在你們的控制範圍內，所以提前因應是好的。再快速談一下——關於這個模式與 Glob.AI，我很享受聽到大家以及Diego的分享。回顧 Globant 的歷史，我一直認為 50 Squared 的客戶策略非常、非常重要。所以在思考 Glob.AI 以及它如何爬坡時，你們能否從客戶滲透前10、20、30名的角度，給我們一個概念：單一客戶的人均營收可能會是多少，隨著你們學習與深化？是否有任何類比或對照，可以回溯到 Globant 在先前模式下的做法，並把它對應到新模式？我只是想更好地理解，這如何能在你們今年給出的某些指標之外繼續加速成長？

Yes. We're seeing very good traction on the 100 Squared program. Indeed, it grew -- that group of customers grew -- the top 50 grew like 7%, something like that. It's extremely encouraging, right? And it is where we're delivering these new things and the first experiences during these last nine months of execution or a year of execution of our AI Pod. So this is very encouraging by itself.

是的。我們在 100 Squared 計畫上看到非常好的進展。確實，它成長了——那一群客戶成長了——前50名大約成長了7%，差不多是這樣。這非常令人鼓舞，對吧？而這正是我們在交付這些新事物的地方，也是我們在過去九個月的執行、或一年的執行中，AI Pod 的第一批經驗所在。所以這本身就非常令人鼓舞。

In terms of amount of revenue, I would say, let's say that we maintain the gross margin as we have a much higher gross margin on the AI bots and we have maybe, let's say, $1.2 to $1 on the new service line. So overall -- but not in all accounts. I mean it depends a lot on every single account. And remember, this is not -- it cannot be traced back to the original model because the original model was headcount, either fixed price or time of materials. This model carries tokens plus token supervision in a single price, either per million token or per output. And that creates a whole -- a totally whole different math, right?

就營收金額而言，我會說，假設我們維持目前的毛利率，因為AI機器人（AI bots）的毛利率高得多，而在新的服務線上，我們可能——比如說——是1.2美元對1美元。所以整體而言——但並非適用於所有客戶。我的意思是，這很大程度取決於每一個客戶。而且請記住，這無法回溯到原本的模式，因為原本的模式是以人頭計費，不論是固定價格或按工時與材料（time and materials）。這個模式是以token加上token監督（supervision）打包成單一價格，可能是每百萬token計價或按輸出計價。而這會形成一套——完全不同的數學計算方式，對吧？

And these two models is a place in which you can optimize margins, you can improve supervision. You can do it more with less. Or maybe in some accounts, we need to put more supervision for certain specific projects, but it's managing a totally different manner from before.

而這兩種模式是一個你可以優化利潤率、提升監督管理的場域。你可以用更少的資源做到更多。或者也許在某些客戶帳戶中，我們需要針對特定專案投入更多監督，但其管理方式與以往完全不同。

And that's why I'd like to say that this transition is not just like a playground that we started. I think it's the future of a company, Moving to output to consumption to value from a totally different model of before. I'm not saying that this old model or traditional model will disappear but I'm saying this is a transition step-by-step, you are seeing us gaining momentum on this new way of delivering, on this new way of charging our customers that is absolutely decoupled from the traditional way.

這也是為什麼我想說，這個轉型不只是我們開始的一個遊樂場。我認為這是公司的未來——從產出走向消耗、再走向價值，完全不同於以往的模式。我不是說舊模式或傳統模式會消失，但我是在說這是一個循序漸進的轉型；你正在看到我們在這種新的交付方式、以及這種與傳統方式完全解耦的全新向客戶收費方式上，正在累積動能。

So making a parallel between those two things, sometimes it can seem difficult. And honestly, we have not much story. I mean we have one year implementing this. We already have some signals. It's enough for us to put a pricing on those million tokens or this output that we are charging. But we need to see many more things happening to be able to take the kind of conclusion you want.

所以把這兩件事做平行比較，有時候看起來會很困難。坦白說，我們還沒有太多可講的故事。我的意思是，我們實施這個才一年。我們已經看到一些訊號。這些訊號足以讓我們對這些百萬 tokens 或我們所收費的這些產出訂出價格。但我們還需要看到更多事情發生，才能得出你想要的那種結論。

But what I can say is, listen, we are evolving in a very nice way, growing in a very nice way. It surpasses my own expectations. I said it 60 to 100, now it's at least 110. And I think it will keep on compounding because it makes a lot of sense for our customers. And many of the new projects that I referred to in past earnings calls, about changing interfaces, automating processes, making sense out of massive amount of information, all these things requires a totally different way of delivering.

但我能說的是，聽著，我們正以非常好的方式演進、以非常好的方式成長。它超出我自己的預期。我之前說是 60 到 100，現在至少是 110。而且我認為它會持續複利成長，因為這對我們的客戶非常有意義。而我在過去幾次財報電話會議提到的許多新專案——例如改變介面、自動化流程、從海量資訊中萃取意義——所有這些都需要一種完全不同的交付方式。

And this new service is not just for those 100 Squared customers. And this is a beautiful part because this is also to serve other segments which may be smaller, and we are still learning how to do it, but we will keep on expanding on this as we progress. I don't know, Juan or Fer, if you want to add something?

而這項新服務不只是提供給那 100 Squared 的客戶。這是很美的一點，因為它也能服務其他可能規模較小的客群；我們仍在學習如何做到，但我們會隨著進展持續擴張。我不知道 Juan 或 Fer 你們是否想補充？

No. Like the last thing you said, it's quite important with Glob.AI, we're also thinking of how to widen our base of clients, how to serve clients with different kind of scale that we couldn't do it before in different segments to accelerate our revenues. We've proven the success of the 100 Squared model, like you said, and it is very well reflected on the growth of at least our 50 top customers. And now the challenges like sustaining the growth of a segment. Our clients have different dynamics, right, and needs to be so different. And we believe that with Glob.AI, we also have a way to reach a much wider base of customers with a simpler way and a more sustainable way.

沒有。就像你最後說的那點，這非常重要：透過 Glob.AI，我們也在思考如何擴大客戶基礎，如何以不同的規模去服務我們以前在不同細分市場無法服務的客戶，從而加速營收。我們已經證明了 100 Squared 模式的成功，如你所說，這也非常清楚地反映在至少我們前 50 大客戶的成長上。而現在的挑戰是如何維持某個細分市場的成長。我們的客戶有不同的動態，對吧？需求也非常不同。我們相信，透過 Glob.AI，我們也有一種方式能以更簡單、也更可持續的方式觸及更廣泛的客戶群。

Maggie Nolan, William Blair.

Maggie Nolan，William Blair。

Maybe I wanted to build on one of those past questions. You -- let's see. Okay. Yes. So you had talked about in the comments that you thought that Globant AI and having a focus on outcomes was opening up new budgets to you that you hadn't had access to before. So maybe can you elaborate on where that growth is coming from, who are the new buyers? Is that growing? Or do you view a total addressable market as growing? And kind of what's changing your ability maybe to go deeper in clients?

也許我想延伸一下先前其中一個問題。你——讓我看看。好。是的。所以你在評論中提到，你認為 Globant AI 以及聚焦於成果，正在為你打開以前你無法觸及的新預算。那麼你能否更詳細說明這個成長來自哪裡、有哪些新的採購決策者？這是在成長嗎？或者你認為整體可服務市場（TAM）正在擴大？以及大致上，是什麼在改變你深入客戶的能力？

Well, look, that paragraph that you mentioned refers to the following. For years, as I described at the very beginning of the earnings call, we have been meeting experiences and software products and we have been very close to using technology to create experiences that engage in an emotional way with our customers. And that is the core. That's what's -- define us.

嗯，你看，你提到的那段話指的是以下內容。多年來，正如我在這次財報電話會議一開始所描述的，我們一直在打造體驗與軟體產品，而且我們一直非常貼近地運用科技來創造能以情感方式與客戶互動的體驗。而那就是核心。那就是——定義我們的東西。

Now as AI came, there are many other places in which it's not just creating those experience, but also operating part of those back-ends and processes that before were not an opportunity for us. So as I described that the process automation and the change on the landscape of how do you use AI for pretty much everything, including automating process, creating new or charts that reflect that automation, we believe that our AI Pods, which are now the AI Pod software that what you see in Glob.AI if you go will evolve into operations and will include that same concept of having an agent operating something for you and having humans being able to analyze the edge cases and charging in a way that is per unit of that specific business case, let's say, travel.

現在隨著 AI 的到來，有許多領域不只是創造那些體驗，還包括運作其中一部分後端與流程，而這些在以前對我們而言並不是機會。所以如我所描述的，流程自動化，以及你如何把 AI 用在幾乎所有事情上的版圖變化——包括自動化流程、建立反映該自動化的新流程或圖表——我們相信，我們的 AI Pods（現在在 Glob.AI 上你看到的 AI Pod 軟體）將會演進到營運（operations）領域，並納入同樣的概念：讓一個代理（agent）替你操作某些事情，同時讓人類能分析邊緣案例，並以該特定業務情境的單位來計費，例如旅遊。

Well, it will be per trip or Know Your Customer, per Know Your Customer. So that agentic work that this Glob.AI concept is opening up is much larger than the software development life cycle that we have right now on the Glob.AI. So what I'm saying is, with this new idea with this new concept, with this new definition of how services and AI native services will be rendered, we are able to tackle much more than just the original software development life cycle, and we can expand our presence into AI Pods for operations, right? So that's what I'm referring about when tackling new budgets.

嗯，那就會是按每趟旅程計費，或是 KYC（認識你的客戶）就按每一次 KYC 計費。因此，這個 Glob.AI 概念所開啟的代理式工作（agentic work），其規模遠大於我們目前在 Glob.AI 上所涵蓋的軟體開發生命週期。我的意思是，透過這個新想法、新概念、以及對服務與 AI 原生服務如何交付的新定義，我們能處理的不僅僅是原本的軟體開發生命週期，我們也能把我們的觸角擴展到用於營運的 AI Pods，對吧？所以這就是我在談「切入新預算」時所指的內容。

And also there's a market share gain too, because when you present this new way of doing things and new way of charging things, for every dollar you sell on this new model, you are able to capture maybe another do, right, of that same budget because you are doing things that other vendors we are doing. So we're extremely excited about those two things happening at the same time, expanding into other places and capturing more dollars for that work that we used to do.

而且也有市占率提升，因為當你提出這種做事的新方式與新的收費方式時，你在這個新模式下每賣出 1 美元，你可能就能再多捕捉同一筆預算中的另一美元，對吧？因為你正在做的是其他供應商原本在做的事情。所以我們對這兩件事同時發生感到非常興奮：一方面擴展到其他領域，另一方面在我們過去做的那類工作上捕捉更多美元。

And in many cases, it was the reason why we win and we won. I have many examples, several examples otherwise we would have lost. And I think that this new definition of how to do things and how to charge for things is a really new approach to our customers. And we launched it last Thursday. And the impact, the amount of people that call us, the amount of people that are interested in understanding more about how this Glob.AI model works, in essence, it's a huge effort and a huge intellectual effort in creating something that didn't exist. And we are the first providing it.

而在很多情況下，這就是我們為什麼能贏、以及我們贏下來的原因。我有很多例子、好幾個例子，否則我們本來會輸。而我認為，這種對「如何做事」以及「如何收費」的新定義，對我們的客戶而言是一種全新的方法。我們在上週四推出了它。而其影響——打電話給我們的人數、對了解這個 Glob.AI 模式如何運作感興趣的人數——本質上，這是一項巨大的努力，也是一項巨大的智力投入，去創造一個原本不存在的東西。而我們是第一個提供它的人。

So I'm extremely proud about the whole team that is developing this. I'm extremely proud that we have been able to take it to the market, and we are being able to convince our customers. And not just a couple of cases, now it will be more than $100 million in ARR. That is an absolute success. And I think that this is something that you will see us insisting more and more. And deliberately, enter into -- asking our customers to change the model. And that will be a process. That will be a process itself. It reminds me to some other companies changing how they do business. But I think overall, it will be very exciting to see that transition and to run it.

所以我對整個正在開發這個的團隊感到非常自豪。我也非常自豪我們能把它推向市場，而且我們正在說服我們的客戶。而且不只是少數幾個案例，現在它將會超過 1 億美元的 ARR（年度經常性收入）。那是絕對的成功。我認為你會看到我們在這件事上越來越堅持。並且有意識地進入——要求我們的客戶改變模式。而那將會是一個過程。那本身就會是一個過程。這讓我想起一些其他公司改變其商業運作方式。但我認為整體而言，看到並推動那個轉型會非常令人振奮。

Martin, that's super helpful. Maybe then obviously, AI Pods is the growth driver here and Globant AI. But EMEA was expected to be kind of a future growth driver for the company and has been an important region in the past couple of years. So you were pretty clear that you were conservative or prudent in your outlook for that region as the dynamics there have changed.

Martin，這非常有幫助。那麼很明顯，AI Pods 是這裡的成長驅動因素，以及 Globant AI。但 EMEA 原本被預期會是公司未來的成長驅動之一，而且在過去幾年一直是重要區域。所以你很清楚地表示，鑑於那裡的動態已經改變，你對該區域的展望採取較保守或審慎的態度。

I'm wondering where, from an end market perspective, whether it be vertical or geography, you're turning your attention to as a potential growth driver over the next kind of 12 to 18 months, and what we should look for, for success metrics there.

我想知道，從終端市場的角度來看，不論是產業別（vertical）或地理區域，你接下來 12 到 18 個月會把注意力轉向哪裡作為潛在的成長驅動因素？以及我們應該觀察哪些成功衡量指標？

Excellent question, Maggie. Listen, the ocean of our industry is pretty flat. I mean you see other companies, they are pretty much all of us in the same kind of level of growth. What we found is that is not just the old model with new tools, the success, but a totally different delivery system. When I see that we found a place that is growing fast, and we want to build our company around it, is exactly what we want to do.

很好的問題，Maggie。聽著，我們這個產業的海面其實相當平坦。我的意思是，你看到其他公司，基本上大家都處在差不多的成長水準。我們發現，成功的關鍵不只是用新工具套在舊模式上，而是一套完全不同的交付系統。當我看到我們找到一個成長很快的領域，並且想圍繞它來打造公司時，這正是我們想做的事。

Now there are some industries that are taking this faster than others. We are seeing a lot of success in financial services, in media and entertainment. We're seeing a lot of success in airlines. This thing make things more efficiently and faster, 30% faster. So as we see the game evolving from cost reduction that has been the main focus of everybody with AI today to revenue generation, which is what I believe is the smart way of using AI, then we will see a lot of industries coming into this space.

現在有些產業採用這套做法的速度比其他產業更快。我們在金融服務、媒體與娛樂看到很多成功案例。我們在航空業也看到很多成功。這套方法讓事情更有效率、更快，快了 30%。所以當我們看到這場遊戲從「成本降低」（這一直是目前大家使用 AI 的主要焦點）演進到「營收創造」（我認為這才是更聰明的 AI 用法）時，我們會看到更多產業進入這個領域。

So the message I want to convey is not just a region or an industry, but it's a new way of delivering what you should pay attention to. And that's why I ask you to hold us accountable to that number of transition as we evolve this company. This is where we are putting our energy, on how to deliver in a much more efficient way. It's not just adding people plus AI. People plus AI means a lot of slop, a lot of time used to supervise that slop, a lot of rework over and over and over. And when you put order in that process like what we do with our Glob.AI way of delivering, then things become much more efficient and things become independent on the model that you want to use and things become scalable.

所以我想傳達的訊息不只是某個區域或某個產業，而是一種新的交付方式，這才是你們應該關注的重點。也因此我才請你們用那個轉型數字來要求我們負責，隨著我們推動公司演進。我們把精力放在如何以更高效率來交付。這不只是「增加人力再加上 AI」。人加 AI 代表很多雜亂（slop）、需要花很多時間去監督那些雜亂，還有一再一再的返工。而當你像我們用 Glob.AI 的交付方式那樣，把流程建立秩序後，事情就會變得更有效率，也會不再依賴你想用的模型，並且能夠擴展（scalable）。

And then Glob.AI is just -- this is just the beginning of Glob.AI. Glob.AI is much broader than that. Glob.AI is -- the initiative we will use to transform Globant into an AI-native company, the whole Globant into an AI-native company. And it is our AI native services arm. So let's see, it's not just -- I cannot answer with just space, a region or an industry. This is wide; this is very wide.

而 Glob.AI 只是——這只是 Glob.AI 的開始。Glob.AI 的範疇遠不止於此。Glob.AI 是——我們將用來把 Globant 轉型為 AI 原生公司（AI-native company）的倡議，讓整個 Globant 都成為 AI 原生公司。而它也是我們的 AI 原生服務事業部門。所以你看，這不只是——我無法只用某個領域、某個區域或某個產業來回答。這很廣；非常廣。

Bryan Keane, Citi.

Bryan Keane，花旗（Citi）。

Just wanted to ask, Martin, when you talked about you're making a choice to push more work to AI Pods, and that seems like it's costing your existing business or hurts the core revenue of that business, can you just talk about that deflationary pressure and why that doesn't last long as we go for this transition over the next couple of years? Are we going to have to kind of run in this negative revenue territory due to the deflationary pressure that may be pushing work to the AI Pod model is going to cause?

我想問一下，Martin，當你談到你們正在做出選擇，把更多工作推向 AI Pods，而這似乎會讓你們既有業務付出代價或傷害該業務的核心營收時，你能否談談那種通縮式壓力，以及為什麼在未來幾年我們進行這個轉型時，那種壓力不會持續太久？我們是否會因為把工作推向 AI Pod 模式所造成的通縮壓力，而不得不在某種「負營收」區間運行？

Well, look, I mean, in essence, a lot of our customers have been spending the same amount of money getting more productivity, right? And that has been the case in the vast majority of the things. I think in the future, that could evolve to, first, we need to convince procurement, we need to convince more people, and that process could be slower than just running the traditional game. But we're ready to play that. And I think that the margin overall will be much better. And the capabilities for us to improve the margins even further from where we are today is still better.

嗯，你看，基本上，我們很多客戶一直都是用同樣的金額買到更高的生產力，對吧？而這在絕大多數情況下都是如此。我認為未來這可能會演變成：首先，我們需要說服採購部門，需要說服更多人，而這個流程可能會比照著傳統玩法直接跑要慢。但我們已準備好要這樣打。而且我認為整體毛利率會好得多。我們把毛利率在目前水準之上再進一步提升的能力，仍然更強。

So I think that that deflationary scenario is something that we're not seeing right now. If we need to pay for it, we will pay it, I want to do that transition. And that's why I said, listen, we are migrating this even understanding that in some accounts, this will be some demand -- softness in demand -- soften demand, but I believe that overall, the picture will be totally different. I don't know...

所以我認為，那種通縮情境是我們現在還沒有看到的。如果我們需要為此付出代價，我們也會付，我想完成這個轉型。這也是為什麼我說，聽著，我們正在推動遷移，即使我們理解在某些客戶帳戶上，需求會有一些——疲軟——需求轉弱，但我相信整體圖景會完全不同。我不知道……

I was going to say, Bryan, that sometimes what we've seen is that it may take longer, a lot longer, to convince to persuade the procurement teams and our customer to transition and keeping the same level of revenues with more productivity. So sometimes, we're seeing that -- we know -- we want to migrate, okay? And sometimes, we can do it faster if we're willing to provide some efficiencies immediately to the customer in terms of price.

我本來想說，Bryan，有時候我們看到的是，說服、促使採購團隊與客戶完成轉型，並在更高生產力下維持同等營收水準，可能需要更久、久很多。所以有時候，我們看到——我們知道——我們想要遷移，好嗎？而有時候，如果我們願意在價格上立即給客戶一些效率讓利，我們就能更快完成。

But we believe that because the model is so much more efficient and so it makes so much more sense for them, that we should be able either to expand on other areas of the organization, to win market share from other vendors because we -- I mean what we believe is that this is a model in which we need to deliver services. Now if we can do it faster, we will do it. And I think that's a key message that we are giving here.

但我們相信，因為這個模式效率高得多，對他們而言也更合理，所以我們應該能夠要嘛在客戶組織的其他領域擴張，要嘛從其他供應商那裡贏得市占，因為我們——我的意思是，我們相信這就是我們需要用來交付服務的模式。現在如果我們能更快做到，我們就會去做。我認為這是我們在這裡傳達的一個關鍵訊息。

No, that's really helpful. And then just as a follow-up, Juan, the revenue per head, it jumped to almost double digits. How much of that is like-for-like pricing? Or are you guys getting a little better pricing right now in the market? Just trying to understand that number.

不，這真的很有幫助。接著追問一下，Juan，人均營收跳升到接近雙位數。其中有多少是同質同價（like-for-like pricing）？或者你們現在在市場上是否拿到稍微更好的定價？只是想理解那個數字。

It's a combination of different things. The market is competitive, right? There are some occasions where we are being able to deliver with less headcount because we are being more efficient with our delivery model right now. And if you look at the total headcount, it's down roughly almost 10% year-over-year with revenue per head going up almost 10% year-over-year. So we are being more efficient.

這是多種因素的組合。市場競爭激烈，對吧？有些情況下，我們能用更少的人力交付，因為我們目前的交付模式更有效率。如果你看總人數，年對年大約下降接近 10%，而人均營收年對年上升接近 10%。所以我們變得更有效率。

In some cases, we have been able to get some additional pricing. But it's -- I mean, I wouldn't take that as the norm because the market is very competitive right now. But we have been able to increase our revenue per employee because we are delivering in a more efficient manner.

在某些案例中，我們確實能取得一些額外的定價。但——我的意思是，我不會把那當作常態，因為目前市場競爭非常激烈。但我們能提高每位員工的營收，是因為我們以更有效率的方式在交付。

In some cases, we are charging that with the new model, with the AI Pod revenue or the Glob.AI revenue model. In other cases, it may be a fixed price where we are able to deliver more efficiently and, hence, increasing the revenue per car. So it's not that we are charging like Glob.AI, because it may be a fixed price, but we are still getting more revenue per employee because we are delivering more efficiently.

在某些情況下，我們會以新模式來收費，採用 AI Pod 的營收模式或 Glob.AI 的營收模式。在其他情況下，可能是固定價格；在這種情況下，我們能更有效率地交付，因此提高每輛車的營收。所以並不是說我們都像 Glob.AI 那樣收費，因為它可能是固定價格，但我們仍然因為交付更有效率，而讓每位員工帶來更多營收。

And I think that explains the sharp increase. If you look at the revenue per head, three, four, five years ago, it was around $60,000, $65,000 per employee. Now we're getting close to over $90,000 and getting close to $100,000.

我想這就解釋了為什麼會出現如此明顯的提升。如果你看每人營收，三、四、五年前大約是每位員工 60,000 到 65,000 美元。現在我們已經接近超過 90,000 美元，並且快要接近 100,000 美元。

Arvind Ramnani, Truist Securities.

Arvind Ramnani，Truist Securities。

Just had a couple of questions on Glob.AI. Martin, you said that's kind of where you're focused your efforts on. So just a couple of questions out there, right? Like how does the workload split across these OpenAI and Anthropic and open weight models today? And how do you expect that to shift over the next like 18 months?

我有幾個關於 Glob.AI 的問題。Martin，你提到那算是你們目前聚焦投入的方向。所以我這邊有幾個問題。例如，今天在 OpenAI、Anthropic 以及開放權重（open weight）模型之間，工作負載大概是如何分配的？你們預期在接下來大約 18 個月會如何變化？

And then second question around that is you also mentioned a lot of those clients who are leveraging Glob.AI is existing clients. But how many clients -- or what percentage are like kind of new clients, right? Like who are not using that? And just last question on that is that what's kind of Globant's kind of unique value proposition, right? Is it around enterprise context? Is it around routing logic? Like what's proprietary to you?

第二個相關問題是，你也提到很多使用 Glob.AI 的客戶是既有客戶。但有多少客戶——或比例上有多少——算是新客戶？也就是之前沒有使用的那些客戶？最後一個問題是，Globant 的獨特價值主張是什麼？是企業情境（enterprise context）嗎？是路由邏輯（routing logic）嗎？有哪些是你們的專有能力？

Okay. Let me -- I will start with the first and then -- the last, and I will let Diego to complete. I see that we just announced a partnership with Anthropic. We are extremely excited with the things we can do together. We are already seeing some impact on -- from that pipeline coming into our scope of work, which is very, very exciting. I see models have -- models will be evolving. And our customers will decide kind of what to use. When we see Glob.AI, we see something that it could use pretty much any model on the core when developing the software or creating the software, including open weight models, if that's the case.

好的。我先回答第一個，然後再回答最後一個，接著我會讓 Diego 補充完成。我看到我們剛宣布與 Anthropic 的合作夥伴關係。我們對於能一起做的事情感到非常興奮。我們已經看到那條管線（pipeline）進入我們工作範疇所帶來的一些影響，這非常、非常令人振奮。我認為模型已經——模型也將持續演進。而我們的客戶會決定要使用哪一種。就 Glob.AI 而言，我們認為它在開發或打造軟體時，核心幾乎可以使用任何模型，包括開放權重模型（open weight models），如果需要的話。

We're processing a big chunk of our tokens with our own infrastructure and our own models, using open weight models in many occasions. And some of our customers are requesting that. Some of our customers are saying, we'll go full-fledged with Anthropic or with OpenAI. So we have pretty much full independence on that specific thing. And of course, tools will keep on evolving and keep on becoming more and more sophisticated.

我們用自有的基礎設施與自有模型處理了相當大一部分的 tokens，且在許多情況下會使用開放權重模型。而有些客戶會要求這樣做。也有些客戶會說，我們要全面採用 Anthropic 或 OpenAI。因此在這件事上，我們基本上具有完全的獨立性。當然，工具也會持續演進，並且變得越來越成熟、越來越精密。

Two, the specific moat that I would like to describe about Glob.AI, Glob.AI is a play of services. Basically, we are mixing in an absolute frictionless way. The creation of the experience and the creation of the software and the definitions that you need with AI and with humans and putting -- and packing everything into a single price and a single price per consumption or per output.

第二點，我想描述 Glob.AI 的特定護城河（moat）：Glob.AI 是一個以服務為核心的打法。基本上，我們以完全無摩擦的方式把幾件事混合在一起。也就是體驗的打造、軟體的打造，以及你所需要的各種定義，結合 AI 與人類，並且把——把所有東西打包成單一價格，採單一的按用量或按產出計價。

So basically, what you saw, the demo, the video that Diego showed to us, it's a video that makes it very clear that Glob.AI helps you with the definition, helps you with the creation of the specification, and then a set of agents get triggered, a set of loops get triggered or workflow gets triggered Depending on what you need to do, those things are different, and these playlists have been graded and evolve with time. And depending on which player you are using they were required like different levels of supervision for humans that are watching what those patients are creating, but we charge you in an extremely transparent way, either per million token or per output in case of a user story or in case of -- so what I'm saying is that this coordination, that elimination of the friction to buy services is the real thing that we are providing. And that's independent on any model that you may choose, right?

所以基本上，你看到的那個 demo、Diego 給我們看的影片，非常清楚地呈現 Glob.AI 會協助你做定義、協助你建立規格，然後會觸發一組代理（agents）、觸發一組迴圈（loops）或觸發工作流程（workflow）。視你需要做什麼而定，這些東西會不同，而這些播放清單（playlists）會被評分並隨時間演進。而且取決於你使用的是哪個「玩家」（player），它們會需要不同程度的人類監督，來看那些「患者」（patients）正在產出什麼；但我們的收費方式極其透明，可能是按每百萬 token 計價，或在使用者故事（user story）等情境下按產出計價——我的意思是，這種協調、這種消除購買服務摩擦的能力，才是我們真正提供的價值。而且這與你可能選擇的任何模型無關，對吧？

So that's what we are saying. This is real AI-native service. Because it's playing the same role that in the past when cloud didn't exist and we needed to create compute, you buy the servers, you buy the connectivity, you used to buy the -- or to hire the people to manage those servers. And then suddenly someone coordinated everything in a beautiful way and it was so easy to ramp up infrastructure, right?

所以這就是我們在說的。這是真正 AI-native 的服務。因為它扮演的角色就像過去在雲端不存在、我們需要建立運算能力時一樣：你要買伺服器、買連線，你還得買——或雇用人來管理那些伺服器。然後突然有人把一切以很漂亮的方式協調起來，擴充基礎設施就變得非常容易，對吧？

Well, professional services is in that old era. And with Glob.AI, we're creating the AWS of the services, right? So it's extremely easy to go explain your project, create the context, connect with your JIRA or with your GitHub or with your -- whatever repository you want, and then execute the mission and that mission will be played in an extremely professional manner, supervised by the best people that can lead you to the right enterprise results you are looking for.

嗯，專業服務現在還停留在那個舊時代。而透過 Glob.AI，我們正在打造服務界的 AWS，對吧？所以你只要很容易地去說明你的專案、建立情境、連接你的 JIRA 或 GitHub 或——任何你想要的儲存庫（repository），然後執行任務；而那個任務會以極其專業的方式被完成，並由最優秀的人才監督與帶領，協助你達成你所追求的企業成果。

That concept, it seems too easy, but it's extremely sophisticated. It's the evolution of services. And it's not just a platform. And it can play with Codex, with our own CODA. It can play with Claude. It can play with pretty much any of the AI tools that are out there. And then it can be played into any type of infrastructure. But the thing is it always gets coordinated in a pretty efficient manner with a human. So no more ramp-up of teams, no more long time of procurement for something. No more not understanding how much something will cost. It's a totally different thing. And that's why Diego showed the video. But I don't want to screw your speech.

這個概念看起來很簡單，但其實非常精密。這是服務的演進。而且它不只是個平台。它可以搭配 Codex、搭配我們自己的 CODA。它可以搭配 Claude。它幾乎可以搭配市面上任何 AI 工具。然後它也可以部署在任何類型的基礎設施上。但重點是，它總是能以相當有效率的方式，在人類的協調下運作。所以不再需要團隊的長時間 ramp-up，不再需要冗長的採購流程。也不再會搞不清楚成本會是多少。這是完全不同的東西。這也是 Diego 為什麼要展示那支影片。但我不想搶走你的發言。

Sorry, I think it's good and it's a totally valid question. One of the things that we do find every single enterprice project has a ton to do with accountability and repeatability. You will not get accountability from a frontier model. You use it, you get a result. Is it good? Is it bad? It's up to you, you implement? That's what you get. Globant brings you accountability. That's why we have humans.

抱歉，我覺得這很好，而且是個完全合理的問題。我們發現每一個企業（enterprise）專案都與問責（accountability）與可重複性（repeatability）高度相關。你不會從前沿模型（frontier model）得到問責。你使用它，得到一個結果。它好嗎？它不好嗎？由你決定，你要不要實作？你拿到的就是那樣。Globant 帶給你問責。這就是為什麼我們有人類。

And the second most important aspect is that the model is not repeatable. When you go to a frontier model, it does -- I mean, generating out is super good. It's amazing. And we are capturing 100% of the value there. But when it comes to planning, how do I execute something, it's a combination of how you prompted, how much information you gave it, what's the decision and thought process on the model. It consumes a ton of tokens for solving sometimes easy tasks that could have been solved with probably 10% of the spend, as an example and we actually moved away from that. And what you see there as battle cards are actually the formula of how the proper -- what's the proper way of delivering this type of value. What's the proper way of doing a migration, a replatforming, SAP4HANA migration, as an example?

第二個最重要的面向是：模型並不可重複。當你使用前沿模型時，它——我的意思是，生成（generating out）非常好。真的很驚人。而我們在那裡捕捉了 100% 的價值。但當談到規劃——我要如何執行某件事——它取決於你怎麼下提示（prompt）、你給了多少資訊、以及模型的決策與思考過程是什麼。它會消耗大量 tokens 來解決有時其實很簡單的任務；舉例來說，那些任務可能用大概 10% 的花費就能解決，而我們其實已經從那種做法移開了。而你在那裡看到的 battle cards，其實就是一套公式：如何才是交付這類價值的正確方式。例如，如何才是做遷移（migration）、重新平台化（replatforming）、SAP4HANA 遷移的正確方式？

The blueprint, it has a ton of very well-defined steps. Every step it has a required input, not less, not more than that, in a required output, and a supervision for that, which is called a quality gate. So you get a repeatable system, a system that you can feed over and over and you get the same. This is something you don't get out of AI and drives enterprises crazy.

這份藍圖包含大量定義非常清楚的步驟。每一步都有必須的輸入（不多不少）、必須的輸出，以及對應的監督機制，稱為品質關卡（quality gate）。因此你會得到一個可重複的系統，一個你可以一再投入並得到相同結果的系統。這是你無法從 AI 得到的東西，而這會讓企業抓狂。

So you don't have control on the spend in many occasions. Models are actually working with both ends, the definition and the testing. And what happens in the middle kind of looks like brute force, like trial and error, and that's how graph engineering in many occasions work. So we totally changed this, and we use what we know, where the humans can actually add value, make sure things are completely right, and you provide the accountability for that.

所以在很多情況下，你無法控制支出。模型其實同時在兩端運作：定義端與測試端。而中間發生的事情看起來有點像蠻力法、像反覆試錯；而在很多情況下，圖譜工程就是這樣運作的。所以我們徹底改變了這點：我們運用我們所知道的、在人類確實能增值的地方，確保事情完全正確，並且為此提供可追責性。

So coming back to your original question, I think that every single company we talk to actually finds a lot of comfort and feel a lot more comfortable with this model. This is the type of services we've been providing for over 20 years. It's not about the output. It's not the source code. It's not the executable. It's about the process, capturing what the client actually needs, providing value on top of that, and holding yourself accountable for that output, for that business impact.

回到你最初的問題，我認為我們談到的每一家公司其實都從這個模型中獲得很大的安心感，也覺得更踏實。這正是我們 20 多年來一直在提供的服務類型。重點不在輸出。不在原始碼。不在可執行檔。而在於流程：捕捉客戶真正需要什麼，在其上提供價值，並對該輸出、對該商業影響承擔責任。

And let me illustrate this with one example, which is from a few days ago. And what happened was one of our customers at Glob.AI to some kind of architecture definition for a pretty complex project around ERPs and APIs and connections. And he dropped it on Glob.AI, our guys guided, I mean, the agents start to do the work. Supervision happens across that work. We interact with the customer 2 or 3 times. And we finished that in a record 48 hours.

我用一個幾天前的例子來說明。當時我們在 Glob.AI 的一位客戶，需要為一個相當複雜、涉及 ERP、API 與各種連線的專案做某種架構定義。他把需求丟到 Glob.AI 上，我們的人員引導之後，也就是代理開始進行工作。整個工作過程都有監督。我們與客戶互動了 2 到 3 次。我們在破紀錄的 48 小時內完成了。

Now to do that same thing, even with Globant in a traditional way, would have taken at least two or three weeks, because of the meetings and the things and the scope gathering, all those things, all that process that was extremely inefficient before has been concentrated in a very simple way of doing it now.

如果用傳統方式，即使在 Globant 內做同樣的事，至少也要兩到三週，因為要開會、處理各種事項、蒐集範疇等；以前那套極度低效率的流程，現在被濃縮成一種非常簡單的做法。

So that value that is created by understanding the customer faster and getting to the accountable result, as Diego was describing, is the main thing that we are talking about today. And that's the transformation I want to make for the whole company, for the whole Globant and for our whole customers. And I think that yields much better margins, much more predictable revenue, much more consistent and recurring revenue. It yields, I believe, results for our customers that are way beyond just using AI with a set of engineers. And I think it's the answer that many will follow. And it's not just us. I mean, we are starters and we are innovators in this mission. But it won't stop here. So it will be fun.

因此，如 Diego 所描述的那樣，透過更快理解客戶並達到可追責的結果所創造的價值，就是我們今天在談的核心。而這正是我想為整個公司、整個 Globant，以及我們所有客戶帶來的轉型。我認為這會帶來更好的利潤率、更可預測的營收、更一致且可重複的經常性營收。我相信，這也會為客戶帶來遠超過「用一群工程師搭配 AI」的成果。我認為這是許多人接下來會採用的答案。而且不只我們。我們是這項使命的先行者與創新者。但不會止步於此。所以會很有趣。

Jonathan Lee, Guggenheim.

Jonathan Lee，Guggenheim。

Great. Good to see you guys. Martin, I appreciate the vision, and I understand you're not seeing deflationary pressure today around AI Pod work. But how are you thinking about combating it and when it does emerge, particularly when clients come back on renewal and demand a larger share of productivity gains? What are the structural defenses in the pod model that led you hold pricing when procurement inevitably pushes back?

很好。很高興見到各位。Martin，我很欣賞這個願景，也理解你們目前在 AI Pod 的工作上還沒有看到通縮壓力。但你們如何思考在未來一旦出現時要如何因應，特別是當客戶在續約時回頭要求分走更大比例的生產力提升收益？在採購部門不可避免地對價格提出反對時，Pod 模型有哪些結構性的防禦機制，讓你們能夠維持定價？

I didn't get the question exactly, please. Can you repeat it again?

我沒有完全理解這個問題，請問可以再重複一次嗎？

So as you think about the deflationary pressure that you're not seeing today, what happens when you need to combat it going forward if it does emerge? And is there anything structural in the pod model that lets you hold pricing when procurement pushes back on pricing?

也就是說，針對你們目前尚未看到的通縮壓力，如果未來真的出現，你們要如何因應？另外，Pod 模型是否有任何結構性的設計，能在採購端對價格施壓時，讓你們仍能維持定價？

Well, okay. Listen, I think that if procurement comes back, that's always a negotiation, but that happens in every single model, not just in the AI Pod. But the thing is I believe that we can be much more efficient. If the customer wants to do the same, it will cost less money. If the customer wants to do more, which is most of the cases that we are finding, they will spend the same amount of money. And the thing is that the customers will want to do a lot more. So I think there will be an up-spending in this new model, more money to produce much more as we have been describing in the past.

好。聽著，我認為如果採購端回來談，那永遠都是一場談判；但這在任何模式都會發生，不只是在 AI Pod。不過我相信我們可以更有效率。如果客戶想做同樣的事情，成本會更低。如果客戶想做更多——而這是我們多數情況下看到的——他們會花同樣的錢。而關鍵是，客戶會想做更多。所以我認為在這個新模式下，支出會上升：用更多的錢產出更多，正如我們先前所描述的。

So again, this is a game about the amount of software and the amount of solutions and processes that must be created or used in this new era. So I think the game cannot be predicted that simple saying -- putting like a constant value on the amount of things and that can be do -- or that are needed, sorry. So as this amount of things moves everywhere, and in many occasions, moves up as the new needs, as described before, the new needs happen, then where you land with the AI Pods there, I think, in my opinion, will be increasing. Now that's demonstrated on the top accounts that are growing at 6% and 6.9%.

再說一次，這是一場關於在這個新時代必須被建立或被使用的軟體、解決方案與流程數量的競賽。所以我認為不能用那麼簡單的方式去預測——例如把要做的事情數量視為一個常數；或說那些需要的事情可以被做——抱歉，是「需要的事情」。當這些事情的數量到處變動，而且在很多情況下，隨著新需求（如前所述）出現而上升時，我認為 AI Pods 最終落點會是增加的。這也反映在我們前幾大客戶的成長上：成長 6% 與 6.9%。

And also even in that scenario, potentially, when a customer wants to do the same and there is a potential saving for the customer there, the model runs at higher margins than the traditional models. And maybe we will be making the same dollar amount with a little bit less revenue on some accounts. But at the end of the day, the way we look at this is, look, this is the way services need to be delivered going forward.

而且即使在那種情境下，當客戶想做同樣的事情、並可能因此節省成本時，這個模式的利潤率也比傳統模式更高。也許在某些客戶上，我們會用稍微少一點的營收，賺到同樣的美元金額。但歸根結底，我們看待這件事的方式是：服務在未來就必須以這種方式交付。

If we do it better and faster than others, even if we lose some money in some projects where we need to reduce a little bit of the revenue, we will earn more projects, we will win market share and we will eventually grow faster again. So that's how we are looking at it. And we are willing to take some of those cases. Again, it's not in every case. We've seen many cases so far where it just keeps adding more work. But there are some occasions that we are seeing that if we take a haircut, we can accelerate the migration.

如果我們做得比別人更好、更快，即使在一些專案上我們必須稍微降低一點營收、少賺一些錢，我們也會拿到更多專案、贏得市占，並且最終再次更快成長。這就是我們的看法。而且我們願意接受其中一些案例。當然，不是每一個案例都如此。到目前為止，我們看到很多案例是工作量持續增加。但也有一些情況是，如果我們稍微讓利，就能加速遷移。

And this is what we are saying today. We are willing to accelerate because it gives us a better position in front of the customer. It protects us from the competition. And we believe that it's going to drive more business into Globant going forward. And at the same time, because we can be more efficient, especially as we scale, there is more margin to be along the way.

這就是我們今天所說的。我們願意加速，因為這能讓我們在客戶面前取得更好的位置。它能保護我們免於競爭。而且我們相信，這將在未來推動更多業務流向 Globant。同時，因為我們能更有效率，尤其在規模化之後，沿途也會有更高的利潤空間。

So there are multiple things happening at the same time. It's still hard to model for us. We are building models every day. But we are seeing at least that there is clear traction, that there is a clear improvement in margins, and the customers are enjoying and are coming back to scale the model. So that's what we are looking at this.

所以同時有多件事情在發生。對我們來說仍然很難建模。我們每天都在建立模型。但我們至少看到有明確的進展動能、毛利率有明顯改善，而且客戶用得很滿意，並且會回來擴大規模以推進這個模式。所以這就是我們目前在觀察的重點。

Yes. And the game and the play for us is we found that space that is growing fast. We want to expand that transformation and do it faster. This is a very simple way of putting it.

是的。而對我們來說，這場仗、這個打法是：我們找到了那個正在快速成長的空間。我們希望擴大那個轉型，並且更快地推進。用很簡單的方式來說就是這樣。

And I think one additional thing is that, as we all know, the market as it is today has been concentrating on the cost saving machine and operational side of things. And it's a lot more difficult, I think it's a worse scenario because it's a lot more difficult when you're part of the cost equation, right? And we -- and that's the type of pressure and companies may want to reclaim part of those efficiencies.

我想另外補充一點是，正如大家所知，如今的市場一直把重心放在節省成本的機器與營運層面的事情上。而我認為這更困難、情境也更糟，因為當你是成本方程式的一部分時，事情就會變得更難，對吧？而我們——這就是那種壓力，企業可能想要收回一部分這些效率。

Once the markets start recovering and moving to a revenue-generating engine and stop neglecting products, as an example, things will definitely change. We've seen this over and over. When the target -- the product, you want to squeeze in new features, additional content, et cetera, so it's not about saving the money, it's about making your product better and stand out in front of others. So hopefully, we will see that happening soon.

一旦市場開始復甦、轉向以創造營收為引擎，並停止忽視產品（例如），情況肯定會改變。我們一再看到這種情況。當目標——也就是產品——你會想塞入新功能、更多內容等等，因此重點不在省錢，而在讓你的產品變得更好、並在競爭者面前脫穎而出。所以希望我們很快就能看到這種情況發生。

And just as a follow-up, what macro backdrop is assumed in the revised '26 outlook? I mean does that range assume conditions persist maybe some stabilization in North American decision cycles or continued deterioration? And how much cushion is built into the low end for further softening?

再追問一下，修訂後的「26 年展望」假設了什麼樣的總體環境背景？我的意思是，這個區間是否假設情況持續、北美決策週期可能出現一些穩定，或是持續惡化？而在區間下緣為進一步走弱預留了多少緩衝？

No, I think that the most likely scenario is the midpoint, but it basically assumes already a significant impact from the Middle East and our travel customers. Of course, I mean, again, if things get a little bit better on the macro side, especially in the US, we can probably be a little bit above that range. And again, if things get worse, we are not seeing that now, but the cushion is there just to make sure that the range is something we will achieve no matter what.

不，我認為最可能的情境是中位數，但它基本上已經假設中東局勢以及我們旅遊客戶受到顯著影響。當然，我是說，再次強調，如果總體面稍微好轉一些，特別是在美國，我們可能會略高於那個區間。同樣地，如果情況變得更糟——我們目前沒有看到——但我們在下緣保留了緩衝，只是為了確保無論如何，這個區間都是我們一定能達成的。

But the most likely scenario for us, as always, is the midpoint. And unfortunately, we have seen some factors that impacted our previous guidance that we could not control. But the midpoint is our most likely scenario. We have plans to get higher than that. We will try to execute on those. There are some things that we don't control.

但對我們而言，一如既往，最可能的情境是中位數。不幸的是，我們看到一些影響先前指引的因素，而那些是我們無法控制的。但中位數是我們最可能的情境。我們有計畫把結果做到高於那個水準。我們會努力去執行這些計畫。也有一些事情不是我們能控制的。

And to add to that, 90% of our revenues throughout the year are already contracted. And in some of the markets that have been affected, like particularly in new markets, we have pivoted the pipeline towards banking, towards public sector, areas that are less affected as like entertainment and travel and hospitality, which was where our focus was put in new markets so far. So we are rebuilding the pipeline. We are closing some of those new opportunities. So we also expect that new market suffered quite a lot. This quarter, we also expect a quick recovery towards the end of the year.

再補充一點，我們全年 90% 的營收都已經簽約。而在一些受到影響的市場，特別是在新市場，我們已將商機管線轉向銀行業、公共部門等受影響較小的領域；相較之下，娛樂、旅遊與餐旅業受影響較大，而那原本是我們迄今在新市場的重點。所以我們正在重建商機管線。我們也正在成交其中一些新的機會。因此我們也預期新市場受到的衝擊相當大。本季我們也預期在年底前會快速復甦。

So that will be off for the Q&A section today. Thank you all for your time. And now I will ask Martin to provide some closing comments.

那麼今天的問答環節就到這裡。感謝各位撥冗。接下來我會請 Martin 做一些結語。

Thank you, Arturo. Thank you, everybody, for being here today. I'm looking forward -- and thank you for your continued support. I'm looking forward to see you on our next quarter call. Thank you. Goodbye.

謝謝你，Arturo。謝謝各位今天到場。我很期待——也感謝各位持續的支持。我期待在下一季的電話會議上再與各位見面。謝謝。再見。