Globant S.A. Q1 FY2026 Earnings Call

Good afternoon, and welcome to Globant's First Quarter 2026 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. Please note, this event is being recorded and streamed live on YouTube. By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globant.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. 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. 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 Globant 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. I will now turn the call over to Martin Migoya.

Good afternoon, everyone, and thank you for joining us. We are standing at the beginning of the most important transition the technology services industry has lived through. This nearly $2 trillion industry is being rewired in front of us and the signals coming from the AI ecosystem and from the largest software companies are all pointing in the same direction. The influx of capital, the need for the right talent and the need to deploy cost-effective AI solutions quickly has never been greater. We have been providing AI solutions to some of the world's most important companies for more than a decade. Globant was built for this moment. For 23 years, we have been building deep engineering capabilities and a profound understanding of our clients' businesses across more than 1,200 customers. We have built a strong AI-native services practice on top of that foundation. Enterprises do not need just models. They need AI-native services delivered by AI agents, supervised by humans driving their agentic transformation. That is exactly what Globant has been executing since 2025, and it is exactly what the market is now validating. This is our moment, and we are entering it from a position of strength. As I meet with our customers around the world, their need to deploy AI solutions that add value and transform their business has never been greater and strengthens my conviction in our innovative business model. This is further supported by the convergence of the most influential voices in technology. Sequoia Capital through Julian Bek is calling services the new software, noting that for every $1 spent on software, roughly $6 are spent on services, and that AI lets enterprises buy outcomes instead of tools with autopilots replacing copilots and meaningfully different unit economics. Satya Nadella is calling 2026 the year agentic systems start to reshape how enterprises consume software with the boundary between software and services gradually narrowing. And capital is following the thesis. This Monday, OpenAI launched a $4 billion deployment company, and one week earlier, Anthropic launched a $1.5 billion enterprise AI venture with a different group of private equity firms. The two most valuable AI companies in the world are putting capital behind delivery, not just behind models. We are proud to be an OpenAI partner since 2025, and every dollar of capital flowing into this layer expands the market for the model we have already built. Q1 2026 revenue came in at $607.1 million, above the high end of our guidance. We are reaffirming the midpoint of our full year revenue outlook while raising the lower end of the range, narrowing our guidance with greater confidence in our trajectory. Importantly, Q2 guidance returns to sequential growth with the upper end of our guided range translating into year-over-year growth. Q1 appears to mark the trough of this cycle, and we see Q2 as a meaningful step toward a healthier trajectory. Free cash flow was strong and operating margin held within our guided range. Our pipeline remains healthy and continues to build with strategic AI-native opportunities we expect to convert through the rest of 2026. On capital allocation, our original share repurchase program announced last September was completed during Q2, and our Board has now authorized a new share repurchase program of up to $125 million over the following six quarters, representing close to 7.5% of today's market cap and close to 15% of market cap in aggregate between the two plans. The program will be executed at management's discretion, balanced against our investment priorities, including the continued build-out of our AI Pods business. We are committed to returning capital to shareholders because we believe Globant is undervalued relative to the trajectory we see in our pipeline and in AI Pods. A year ago, we announced the shift toward AI-native technology services on top of two decades of engineering and industry expertise. Our core business remains the foundation of the company, and the AI-native layer is its natural evolution. Our AI studios are progressing nicely, layering on nonlinear revenue, incorporating talent, sophisticating our offering and getting closer to what our customers need. For each industry we serve, we are getting deeper. Our global delivery capabilities are helping our clients run the AI transformation they need with greater leverage, better unit economics and a more strategic seat at the table. Critical differentiators of our enterprise solutions are model independence and token sovereignty. Our clients are never locked to a single AI provider. Our platform routes intelligently across more than 140 models, giving enterprises the freedom to adopt the best available technology as the landscape evolves. And every token consumed stays within the enterprise's own governance. Their data does not train third-party models. Their institutional knowledge remains entirely their own. This is particularly beneficial for many of our innovative clients concerned with their intellectual property in highly competitive environments. Our answer to the agentic transformation is the combination of two things: our AI Pods and our forward-deployed engineers. The AI Pods are AI-native service units, each specialized by task and by industry that deliver outcomes instead of effort. The forward-deployed engineers are the human layer that lands inside our customers, embeds AI Pods into their reality and drives the agentic transformation from the inside. The annual recurring revenue of our AI Pods has reached $32.8 million as of March, with strong growth versus Q4. AI Pods is a young, fast compounding practice in our portfolio, and the percentage growth rates we are seeing at this stage reflect early base dynamics that will naturally moderate as scale builds. We have already incorporated the AI Pods business model in 40% of our top 20 revenue-generating accounts, up from 30% from last quarter. The AI Pods pipeline stands at $352 million, including a clear path to coverage in 70% of our top 20 clients. Gross margins on this model continue to run materially above our blended company gross margin. As AI Pods grow as a share of our revenue mix, their structurally higher margin can begin to contribute to our blended margin profile over time. AI Pods and AI-native services are an important evolution of how we deliver value and a meaningful growth lever going forward. Within our digital studios, data and AI, which includes core AI deployments such as NLP, analytics, facial recognition, machine learning and data science is now our second largest studio by revenue right after engineering. Both studios are growing markedly above the company average, with data and AI growing north of 25% year-over-year and engineering in the mid-single digits. This growth mix reflects the priorities shaping enterprise technology investment today. AI is present in 100% of our pipeline. Every project, without exception, incorporates it either as a core element or as a satellite component. Within that, 26% of opportunities are AI core, a figure that rises to 32% when looking only at deals originated in 2026, reflecting the accelerating shift in how clients are coming to us. We are particularly proud of the evolution of our revenue per Globant. As of Q1 2026, we are run-rating a level north of $90,000, representing 8% year-over-year growth. This has been supported by the steady expansion of our AI Pods business and the AI tooling we have embedded into our delivery. This is the structural signature of a company moving up the value chain. What we are seeing in the market reinforces every part of this picture. Our big deals with large customers continue to gain momentum and AI transformation programs are now the predominant pattern across our pipeline. Three large pools of demand are converging on AI-native delivery, technical debt and core modernization estimated at $1.5 trillion to $2 trillion across the world's 2,000 largest public companies; interface and experience debt across customer-facing surfaces; and agentic process transformation, the redesign of business processes and operating models around agents. Globant is positioned across all three. We are winning the modernization pool as an AI-native partner as the IGT relationship with Apollo demonstrates and private equity is becoming a structural channel for us. The largest prize, however, is agentic process transformation. AI is now adopted across the vast majority of our projects, and the real gains come not from layering AI on top of unchanged processes, but from reengineering the business around agents and rewiring the organizational chart itself. Across our studios, our 100 squared accounts continue to gain traction and maintain momentum. Our top 50 clients grew over 5% year-over-year in Q1 with our top 10 and our 2 to 5 cohort growing at similar rates, all meaningfully above the company average. AI Pods are now showing up in concrete ways across every studio. A quick tour. In financial services, our work with Banco Galicia is scaling. They have validated the productivity, speed and quality of our AI Pods, and we are now successfully deploying an operating model to manage the high use case backlog. We are now focused on implementing a new AI Pod dedicated to the definition and construction of data products with an initial use case targeting the reduction of the customer contact rate. We are also applying AI Pods in our work with a leading student loan company in the U.S. to modernize its loan management systems at scale and speed. In health care, Life Sciences and Private Equity Studio, we are migrating five clients to the AI Pods model. At EmployBridge, the first pilot was executed in Q1, and we expect the remaining scope to convert during Q2 into a fully AI Pod engagement. Johnson & Johnson continues to be the largest account in this studio with continued growth. In media, entertainment, sports and hospitality, our 15-year relationship with the Walt Disney Company continues to expand dialogue with several discussions for AI Pods. We are keen to grow with the company by delivering an interconnected experience anchored by Disney+ and across all core businesses. The LA Clippers, one of our most visible partnerships through our work on the Intuit Dome, is transitioning their full operation to AI Pods. Our partnership with FIFA is now in its fifth year. Diego Tartara will share how we are progressing our support across FIFA's business digital initiatives. At the same time, we have expanded our role as their technology partner for the 2026 and 2027 World Cups, enhancing their digital platforms, delivering a new fan engagement mobile application and bringing our AI-native capabilities to one of the world's most watched sporting events. The Mexican Football Federation has chosen sports and performance to build the most advanced football intelligence ecosystem, including new Physical AI applications to further improve sports performance. The agentic solution implemented in LaLiga exemplifies the characteristics of a modern sports organization and will serve as a lighthouse for the industry. We now work with all of the big three cruise lines and look forward to growing our work in this space based on our expertise in customer experience. In gaming, we continue to develop our AI project with Riot. Since booking the largest deal in this sector with them last year, we are now integrating our AI Pods model into quality assurance. In retail, we introduced AI Pods into our dialogue with one of the largest retailers in the United States, with whom we have worked for four years. The retailer was previously considering a global compatibility center, but exposure to AI Pods shifted the conversation toward an agentic-first solution by unlocking more value and efficiency to build a new mobile app and loyalty program. In the technology space, we are happy to announce that we are strengthening our strategic partnership and 360-degree relationship with Google, where we are projecting strong growth into new areas. In the energy space, we continue our three-year relationship with the U.S. Green Building Council, migrating our work on their primary certification, LEED version 5 to AI Pods. Although the change has been recent, we have already seen significant improvements in process efficiency, and we look forward to seeing this growth in the future. The aviation space has been going through some turbulence and volatility following the sudden rise in fuel prices. This has further reinforced the efficiency gains delivered through our AI Pods model. Two of our largest airline clients will be transitioning from a traditional delivery model to AI Pods as part of a multiyear commercial and digital transformation. This shift will allow them to increase throughput, reduce cycle times and operate with a more flexible cost structure, helping offset fuel-driven pressure while continuing to modernize core systems, improve direct channels and enable more dynamic retailing capabilities. In our new markets region, although our clients face many challenges due to the currently volatile situation in the Middle East, Globant continues steadfast in being a strong and stable partner, focusing on long-term growth. Our partnership with Qiddiya City has centered on major projects, including Six Flags Qiddiya City and Aquarabia, the largest water park in the Middle East, with Globant building the end-to-end digital backbone for the guest journey. We are also partnering with Saudi Arabia's local organizing committee to reinvent the football experience centered on the fan ID ecosystem, focusing on a unified AI-powered platform connecting identity, venue access, safety and fan engagement at scale. The Enterprise AI Studio anchors the platform layer that powers AI Pods with multi-cloud integration across Azure, AWS, Oracle and Google Cloud. Our partnerships with the major hyperscalers, AWS, Google, Microsoft and Oracle Cloud Infrastructure all expanded this quarter, and we were named Google Cloud Country Partner of the Year in Argentina for the fourth time. With AWS, this quarter, we surpassed the original KPIs from our strategic cooperation agreement signed last September, aimed at several ambitious indicators, including annual recurring revenue and new solution development. We also continued to deepen our relationship with NVIDIA, which is central to how we deliver AI-native services at the compute and infrastructure layer. Together, these alliances make Globant the AI-native orchestration partner that connects model providers, hyperscalers and the enterprise. And finally, our AI-powered network, which elevates advertising, marketing strategy and media. GUT kicked off the year with incredible momentum, adding 18 new client logos and delivering groundbreaking work, a surreal celebrity-driven music video, which became a full-blown cultural event for Cheetos, the Stella Artois FIFA World Cup 2026 campaign featuring David Beckham in the U.S., a special project for Bancolombia and Pura Magia, a new campaign in partnership with Disney, which reimagines the meaning of transformation at Walt Disney World. Q1 2026 delivered above the high end of our revenue guidance, advanced AI Pods into a clearly strategic position in our portfolio, and gave us additional evidence that the macro shift toward AI-native services is being underwritten by the most credible investors in the technology space. In summary, we are reaffirming the midpoint of our full year revenue outlook, which implies quarter-over-quarter improvement throughout the rest of the year and also a strong focus on capital allocation and returns and accelerating the highest-margin product in our portfolio. We are confident in 2026. I want to thank our clients for their trust, our partners for their collaboration and our Globers around the world for the work they do every day. With that, I will hand it over to Diego, our CTO, who will walk you through the technology and delivery layer. Thank you.

Hello. Globant is no longer preparing for the AI era. We are operating within it. We are systematically reinventing our delivery model so that every solution we deliver is secure, scalable and AI-native from day one. This is what's driving the $352 million pipeline in AI Pods and the technology layer underneath is what makes this work, and that is where I want to focus today. We have evolved our signature delivery framework built on hundreds of autonomous units to embed AI into every dimension of execution. The three pillars of our delivery model have been overhauled to meet this moment. Our Globers are not just using AI. They are augmenting their technical domains to become multidisciplinary orchestrators. We are also expanding to new roles such as our forward-deployed engineering team. We have redefined project management with AI-powered observability and agentic workflows that drive measurable efficiency gains. AI readiness and accountability are now mandatory across all offerings, evolving our agile DNA into a truly AI-native model. We are also building what we call our agentic economy, an inner source ecosystem of more than 20 validated cross-industry agentic solutions that we package as deployable assets directly into AI Pods engagements, whether it is an IT root cause analysis tool for airlines or a supply chain agent for oil and gas. These assets are now being replicated across media, pharma and tech in weeks rather than months. We put special focus on the major demand pools that Martin mentioned, AI delivery, modernization and technical debt. Our forward-deployed engineers are prototyping these solutions in 14 to 21 days. This is the practical mechanism that lets Globant participate in what Sequoia and others have called the services as the new software era. We are building compounding IP that generates recurring value and positions us as a long-term strategic partner. AI Pods are how that IP gets monetized. As we approach the 2026 World Cup, our work with FIFA is accelerating. AI agent networks with human supervision will power key FIFA platforms, enabling more consistent fan engagement across competitions, smarter activation of partnerships and faster deployment of new digital experiences. In Latin American football, Deportivo Toluca, the current Liga MX champion, has launched a new engagement platform developed by Globant and our sports products division, Sportian. The platform offers supporters live in-match services, ticketing, e-commerce, statistics and exclusive content, helping the club personalize the fan experience. In consumer goods, we are working with Grupo Mariposa, one of the region's leading CPG companies to transform their marketing model around the consumer. The initiative integrates data, AI, martech and agile methodologies to enable smarter, faster, more precise decisions. Marketing evolves into a continuously learning system in which creativity and technology adapt together to consumer behavior. Globant is supporting CMPC, a global leader in sustainable pulp and paper to deploy an AI-powered solution that enhances supply chain traceability and compliance, end-to-end visibility, regulatory adherence and a clear sustainability narrative. Our ecosystem continued to deepen in Q1. We announced a strategic partnership with Adyen for next-generation merchant payment experiences. We obtained the GenAI competency from AWS and achieved expert status for SAP Business Data Cloud specialization. Our collaboration with Adobe expanded as we became the first customer experience orchestration partner in Latin America. Our partnership with Autodesk now includes integration with Tandem digital twin technology, unlocking new efficiencies in design and operations. Combined with the partnership recognitions Martin shared earlier, this reinforces our position as the AI-native delivery layer. In Q1, we published two new reports through our research arm, one guiding financial institutions on adopting real-time AI-driven operations, and another helping airlines transition to modern retail models. Both are available at reports.globant.com. Our role in this market is straightforward. We turn AI from a tool into a delivery model, and we package the IP we generate into assets that our clients can deploy. The technology layer behind AI Pods is now compounding, and that is what gives us conviction in the trajectory Martin described today. With that in mind, I will now turn it over to Juan. Thank you very much.

Hello, and good afternoon, everyone. I am pleased to discuss our results for the first quarter of 2026. We have begun the year with a focus on stability and execution. We are operating in a discerning client environment, and we are seeing buyers concentrating on high-impact agentic AI projects and digital transformation, which is exactly where we are positioned. We are executing on the financial front, protecting the bottom line, improving working capital, increasing CapEx efficiency and repurchasing our shares. In the first quarter, our revenue stood at $607.1 million, representing a 0.7% decrease on a reported basis, coming in above the high end of our guidance and reflecting a 400 basis point improvement in year-over-year trajectory compared to last quarter. Q1 revenues included 200 basis points of FX tailwind. The improvement is most visible in our top accounts. Our top 50 clients grew 5.2% year-over-year. Our top 10 grew 4% and our 2 to 5 cohort grew 8.2%, all materially above the company average. Many of our top 20 clients returned to positive year-over-year growth this quarter. This is aligned with our 100 Squared strategy. Our revenue per employee also increased again this quarter, driven by our pivot into platform and AI-led delivery, which allows us to maintain our revenues with a slightly lower headcount. Our adjusted gross profit margin for the quarter was 37%. Gross margins continue to be impacted by the relative strength of Latin American currencies, primarily the Mexican peso, the Colombian peso and the Brazilian real compared to the prior year, alongside statutory cost increases in our delivery centers. Over time, as AI Pods grow as a share of our revenue mix, their structurally higher margin profile can begin to contribute to our blended company margins. This is the longer-term margin opportunity we are building toward. Our adjusted operating margin came in at 14.1% for the quarter, with SG&A at 18.5% of revenues. The effective tax rate for the quarter stood at 23.5% within our guided range. Our adjusted net income for the quarter was $65.2 million, representing an adjusted net income margin of 10.7%. Q1 adjusted diluted EPS came in at $1.50, above the midpoint of our guidance. This number absorbed meaningful FX headwinds, primarily from the Mexican peso, the Colombian peso and the Brazilian real. On an FX-neutral basis, adjusted EPS would have been higher. The underlying operating performance was consistent with our internal plan. Our balance sheet remains strong, ending the quarter with $200.5 million in cash and short-term investments or $161.2 million in net debt. During the first quarter, we invested $50 million to repurchase shares as per the plan announced in October 2025. Our original share repurchase program was completed during Q2. In Q1 2026, we generated $36.1 million of free cash flow, achieving a free cash flow to adjusted net income ratio exceeding 55% compared to negative $5.7 million of free cash flow in Q1 2025. This is the first time Globant has generated free cash flow in the first quarter since 2019. We expect to continue generating strong organic free cash flow for the full year 2026. We will continue to allocate capital with discipline across two priorities: returning capital to shareholders through the newly authorized repurchase program and investing in high-return growth initiatives, principally the continued build-out of our AI Pods business. Now let me move to our outlook for Q2 and for the remainder of the year. For the second quarter of 2026, based on current visibility, we expect revenue to be between $610 million and $616 million. The Q2 year-over-year guidance implies at the midpoint, a positive FX tailwind of 100 basis points. We expect a non-IFRS adjusted operating margin between 14% and 15% and the IFRS effective income tax rate is expected to be in the 22% to 24% range. Non-IFRS adjusted diluted EPS is expected to be between $1.45 and $1.55 per share, assuming an average of 43.6 million diluted shares outstanding during the second quarter. With respect to the full year, at the midpoint, we are maintaining our 2026 revenue guidance unchanged. We expect revenues in the range of $2.462 billion to $2.508 billion, implying 0.3% to 2.2% year-over-year growth, with approximately 100 basis points of FX tailwind. Both Q2 and subsequent quarters imply sequential growth and a healthy exit rate more aligned with industry growth averages. In terms of profitability, we continue to expect our adjusted operating margin for the full year to be between 14% and 15%. Our margins continue to be pressured by the strength of Latin American currencies relative to the dollar. The IFRS effective income tax rate is expected to be in the 21% to 23% range. For the full year, we are also reiterating an adjusted diluted EPS range of $6.10 to $6.50, assuming an average of 44.1 million diluted shares outstanding for the full year. To conclude, Q1 was a quarter of steady execution. We are seeing improvements across our top clients. We are executing on the things that we can control, and our balance sheet remains a source of strength. Our focus on embedding AI into the core of our value proposition is clearly resonating with our most strategic partners. Thank you for your continued support.

Please note operator instructions. So with that in mind, we will take the first question from the line of Bryan Bergin from TD Cowen.

Maybe my first one, just as it relates to demand conversion, can you just talk about what you've been seeing in the broader conversation? So it's good to hear the traction on the AI Pods. But when you just think about the broader conversation, have you seen anything shifting in more recent weeks, April and May? How is that compared to the first quarter as it relates to pipeline conversion?

Yes. The pipeline remains in a very healthy state. Conversion is quite good. We're seeing large deals that we started closing last year and some that closed during this first quarter that will gain traction moving forward. It is shaping up as a space in which several big deals will start to yield results, and we are very happy about that. Of course, there are some concerns around what's happening in the Middle East. However, we see the business healthy there. We have some concerns around airlines given the rise in fuel prices that is changing the landscape for some trips. But in general, we see a positive environment in terms of bookings and long-term deals, which are extremely important and are coming back and gaining traction. One remarkable thing I would like to mention is that growth in our main accounts is well above what we are seeing in the full company, which is the result of our focus on the 100 Squared accounts and the attention we are giving to large customers that need help more than ever. When we talk about AI Pods, we're talking about a way to deliver traditional services. We're not talking about a single specific offer, but a broader way of delivering in an AI-native manner. So I cannot separate the AI Pods conversation from the broader services conversation. In general terms, conversations are moving in the right direction.

Okay. That's clear. And then maybe on the margin, Juan, can you quantify just how much FX pressure there is within the gross margin in the first quarter and in your outlook for this year? And in the gross margin assumption for the year, are you including any tailwind from these AI Pods structures?

Sure. In the first quarter, compared to the last quarter, we saw about one percentage point of FX headwind coming mainly from Colombia and Brazil, and a little bit from Mexico. For the rest of the year, the assumption is the same, though we cannot predict FX moves precisely. We will work to be as efficient as possible to increase utilization levels and employ different ways to offset part of that headwind. We do have a small positive impact assumed toward the latter part of the year. As you may recall, last quarter we mentioned an expected run rate of $60 million to $100 million for AI Pods toward the end of the year. Even though AI Pods are growing very fast, they are still a small part of our business. What is more interesting is that the model is proving to deliver better margins overall relative to our more traditional delivery models, and that will help over time.

The next question comes from the line of Maggie Nolan from William Blair.

Maybe to follow up on what Bryan was just talking about. The AI Pod margin is obviously quite strong. Do you expect that to be sustainable into the future? Or what are your expectations for competitive pricing pressure there?

There is competition, as always, but as we scale projects with AI Pods we improve our agents, token usage, and efficiency. The agents we build learn and evolve in the project, becoming more efficient. That will help offset pricing pressure from competitors. Our expectation is that the AI Pods delivery model will overall deliver higher margins than more traditional delivery models.

We have been growing revenue per head for many years, and this trend reflects how we scale our business by innovating and moving up the value chain. Customers are reacting positively to that, as the numbers demonstrate.

Martin, maybe to build on that revenue per head comment, I would imagine that the forward-deployed engineers are contributing to that growth as well. Maybe you could comment on how those capabilities differ from your historical workforce and what additional changes you need to make to the workforce to continue to capture market share?

Yes. I'll address the first part and ask Diego to add to the second. Forward-deployed engineers is something we've been doing for many years, though we didn't always call them that. Our engineers have long worked at customer premises, understanding processes and proposing new ways of operating. Now they act as agents of transformation and can use multiple platforms rather than being tied to one. They are welcomed by customers. The next generation of capabilities involves changing full processes—processes that previously seemed impossible to change are now possible to automate or reimagine. That mindset is what we're embedding in our teams and in the forward-deployed engineers who work directly with customers. Diego, would you like to add?

Martin captured the idea well. To offer a practical comparison, this role is similar to the modern enterprise architect, but focused on deploying the platform and implementing it. They need to map a company's data structure, architecture and components, connect those elements and build the platform for solutions on top. These are top-tier, senior engineers, and they tend to contribute to revenue per head uplift.

Next up is Tien-Tsin Huang from JPMorgan.

Martin, I liked your comments in the prepared remarks about the rewiring of the industry. With these large language models and investments in services, how do you see the competitive landscape changing? I know we've seen this before in enterprise software. Do you see it differently here? It feels like a validation of services, but I'm not sure what the long-term intent will be from model providers without the domain knowledge that companies like Globant have. How do you see competitive dynamics evolving?

Tien-Tsin, great question. The change underway is so large that no single company will capture all the work. The value of being an independent services partner remains strong: we can advise customers without bias, reengineer processes and save tokens in ways that benefit them. Many model providers will rely on partner networks to capture and route the implementation work. Our relationships, trust, MSAs and years of experience matter a lot. This market is massive and expanding, and the need to deploy solutions—rather than just providing models—is the big prize. We are well positioned given our long-standing relationships and capabilities.

Yes. You are audible. Continuing, Tien-Tsin, I think Diego wanted to add something.

We are having active conversations with our hyperscaler partners. These major providers have long relied on partner networks to deliver large-scale work. The heavy lifting is typically done through partners. Many of the projects we do for AWS, for example, originate through AWS itself. If hyperscalers cannot capture services, they are not the natural go-to for delivering those outcomes. So partner networks are central to execution.

On the question about Q1 being the trough and Q2 showing sequential growth: yes. When we look at Q4 last year, we closed at negative 4.7% year-over-year. This quarter was negative 0.7%. From Q1 to Q2 we're forecasting sequential growth and depending on where we land in the range there is a chance of year-over-year growth. The combination of more working days in the second half of the year, plus several large contracts that have already been signed and that will start to generate revenue, should help us achieve sequential growth in Q3 and Q4 and likely a better year-over-year profile by the end of the year. On top of that, we expect acceleration in AI Pods, which will support both growth and margin expansion going forward.

The next question comes from the line of Bryan Keane from Citi.

Can you just talk a little bit about those larger clients? Your top clients are growing faster with you guys. Is that just a sales focus and can you comment about what those clients are doing in particular that could be the start of something bigger as we go forward this year and into next?

Yes. We're seeing very strong growth among our top 10 clients, around 4% quarter-over-quarter, largely due to the 100 Squared strategy where we've been investing significant focus. When you sample our top 20 clients, growth is much higher than for the broader client base. The work is largely AI-infused: migrating existing operations or starting new development with AI Pods across many top customers. The emphasis is on using AI to improve efficiency and speed to market, enabling faster development cycles and real-world, production testing in shorter iterations. A good example is Disney, where we see a recovery relative to 2025 and strong alignment with their new CEO's strategy of interconnecting the Disney guest experience with Disney+ at the center. He brings a parks-and-experiences perspective, understands our work, and positions us well to capitalize on his strategy. We're having many conversations about migrating Disney's operations to AI Pods.

To add, large clients focus on operational efficiency and maximizing return on spend. Many top accounts are in heavily regulated industries like airlines and banks that demand high security and standards. We have deployed AI Pods in 40% of the top 20 and more are on the way, which validates the AI Pods concept with top clients who are already advanced in their AI adoption. They have tested AI internally and still found significant value in our approach.

That's really helpful. Quick follow-up: what is your Middle East exposure, and how are you thinking about potential disruption there?

New markets represent about 6% of revenues, and the Middle East accounts for roughly two thirds of that. Our midpoint guidance assumes conditions remain roughly as they are today. We are seeing deals get closed and some deals starting or about to start. The lower end of our guidance range would imply a significant deterioration in that business, but so far we are not seeing such deterioration in our numbers.

The pipeline there is strong as well.

The next question comes from the line of Arvind Ramnani from Truist Securities.

Good set of results. I wanted to follow up on Tien-Tsin's question. Certainly these Anthropic and OpenAI investments validate the services model for last-mile delivery. Do you view those players as competition because they may grab resources or clients? How do you view the competitive environment? Also, can you comment on your relationship with Palantir?

Arvind, thanks. This is an extremely large market. Many new companies are entering, and while they have strong distribution, they also have structural limitations. For example, none of the recently formed deployment companies can offer true model independence or unbiased advice that optimizes outcomes for the client. We see them both as competitors and partners. Much of what they are building needs delivery partners, and our 23 years of experience and relationships are a major asset. The market is so large that it is not winner-takes-all; relationships, MSAs and deep customer trust matter a lot. We have many assets and long-term investments that position us well to compete and to partner.

Yes, I agree enterprises likely want multi-model approaches to avoid lock-in. That seems to make a lot of sense.

Not only that, but hybrid approaches also make sense: you can combine cloud models with locally run models for simple tasks. That flexibility is important.

Right. On Palantir, are you seeing them on deals? Do you view them as a partner or competitor?

We see Palantir as a partner. They are a great company with a strong product. In some situations we cooperate and in others we may use alternate solutions. Our priority is always to deliver the best solution for the customer. Palantir is a respected company and we see opportunities to cooperate and expand our relationship where appropriate.

One final quick follow-up on guidance: you reaffirmed guidance despite the beat. Was that a conservative stance?

Arvind, part of the reason is exposure to the Middle East, where the situation changes frequently. We preferred to be cautious and avoid taking unnecessary risk in our guidance at this point.

The next question comes from the line of James Friedman from Susquehanna.

I'll ask about GUT. Martin, could you share your perspective about Globant GUT? It seems like higher-end strategy consulting. How can you use GUT to generate incremental revenue downstream? And Juan, on Latin America macro, can you give a quick overview, macro for dummies, of what you're seeing?

GUT is a very good way for us to enter customers on marketing and technology themes, and AI is integrating deeper every day. The caliber of ideas coming from GUT is impressive and creates openings for our technology innovations to be sold into those customers. It's a strong vehicle to expand relationships where marketing, technology and operations are increasingly integrated and require bundled solutions.

I'll add that GUT helps create strategic direction that can be translated into AI-native delivery and packaged into assets and solutions that our engineering teams implement. It strengthens our end-to-end proposition from strategy to execution.

When we look at Latin America, we see a more stable scenario. Argentina is the country driving most of the growth in the region right now, followed by Brazil. Overall, the region is more stable relative to previous years.

The next question comes from the line of Guggenheim from Jonathan Lee.

I appreciate the commentary about the positive bookings environment. Is there any way to quantify what bookings were in the quarter, how that momentum trended from January through March and what you saw in April into May?

Do you mean bookings in the second quarter specifically?

No. When you look at the first quarter and April and the couple of weeks of May, the situation is similar. We are not seeing big changes. We had a very strong Q4, which helps a bit with what happened in Q1 where we slightly exceeded our initial guidance, and it also helps us reaffirm the full year guidance. The level of bookings we've seen in Q1 and so far in Q2 allows us to maintain guidance despite the new markets region being under some stress. So far, no big changes that would affect our outlook.

Got it. What in your customer conversations gives you confidence around that back-half ramp, particularly sequential growth in the fourth quarter? How much execution is required to achieve that?

There are two main drivers for the back half. One is a higher number of account days in the second half of the year. The other is several large customers with contracts already signed that will scale in the coming quarters. For example, one is a professional services company that was a drag last year and is coming back; another is a big tech company where we became a preferred vendor; a gaming company and a private equity-backed company. Those four contracts are scaling now and, combined with the longer account days in the second half, should drive the second-half improvement.

The next question comes from the line of Sean Kennedy from Mizuho.

Congrats on resilient results. Can you discuss early customer feedback from AI Pods? Specifically, what are customers saying are the greatest benefits and are certain industries seeing more traction currently?

Feedback has been very positive, particularly from top accounts where AI Pods are being adopted. Two main benefits stand out: efficiency gains and improved outcome quality. We consistently show that we can deliver faster and also maintain or improve quality compared to prior models. Our typical rollout includes an experimentation phase followed by scaling, so when revenue is reported it reflects tested and proven implementations. Important differentiators include that the process is baked into the tool, which makes it more resilient to personnel changes and helps retain institutional knowledge. Token consumption is also increasingly important: many companies using cloud copilots or code assistants are incurring high token costs due to inefficient prompting and reprompting. Well-executed tasks with refined agents can use a fraction of the tokens compared to ad hoc prompting. Token efficiency is a tangible cost and performance metric that customers care about. So far we've had no client revert from AI Pods implementations; the efficiencies and quality have made it a keeper.

I would add two points. First, AI Pods enable enterprise-grade processes that are secure, scalable and repeatable—unlike many ad hoc internal experiments that are not scalable or secure for enterprise use. Second, the model allows customers to pay by output or consumption rather than hours. We can instrument each artifact, connect it to token consumption, and deliver transparency on cost and performance. This is a fundamentally different value proposition versus traditional services.

The next question comes from the line of Gustavo Farias from UBS.

My question is on capital allocation. Buybacks suggest confidence in the stock, but they could limit strategic M&A. How do you see the need for M&A in the short to medium term to remain competitive?

We are always evaluating acquisition opportunities. The buyback program gives management discretion, and if we find an acquisition that meets strategic criteria we will pursue it. Our capital allocation decisions are disciplined and seek to maximize returns. We will balance buybacks with investments in AI Pods and select M&A opportunities as they arise.

We have the firepower for M&A if it makes strategic sense. Given today's stock valuation, repurchasing our shares can be an attractive use of capital because we're buying a business we know well. That said, any acquisition would have to meet clear strategic needs to justify the investment.

Following up: last quarter you seemed conservative on fixed-price contracts due to margin concerns. Fixed price as a percentage of revenue looks roughly stable. What's your current view on fixed-price engagements?

The market is pushing toward fixed-price engagements, and that's a reality across the industry. Importantly, we now have tools and the AI Pods delivery model that allow us to deliver more efficiently, making us more confident in taking on fixed-price work compared to one or two years ago. We believe we can manage fixed-price contracts effectively using AI-native delivery.

The last question we have time for today comes from the line of Surinder Thind from Jefferies.

Martin, you've been clear about the ambitions for AI Pods. Is 2026 effectively the year when you're gathering data points to push forward this strategy? How do you think about the longer-term ambition—what percentage of revenue could AI Pods reach? Also, what current frictions keep clients from adopting AI Pods faster given Diego's positive data points?

AI Pods is a fundamentally different delivery model—AI-native services combined with forward-deployed engineers driving agentic transformation. Our engineers help clients reimagine and automate processes across marketing, HR, finance and operations. Long-term, the ambition is for AI Pods to gain share and transform how we deliver services. I prefer not to provide a specific percentage today, but the aspiration is to evolve our current business into something structurally different. This includes new ways to charge—per output or per consumption—rather than per hour. How fast this happens depends on customer adoption and how effective our AI Pods are in practice.

I didn't catch the last part of my earlier question. Specifically, why might clients not adopt AI Pods faster, and how should we think about the balance between AI Pods, fixed-price contracts, and traditional services over the long run?

AI Pods require clients to rethink processes and embrace agentic solutions, which is a bigger change than simply layering AI onto existing workflows. The process of redesign and organizational change takes time. We are helping clients both ideate and implement these changes with forward-deployed engineers who design the future process and embed AI Pods to run it. Over time, some traditional services will persist, but AI Pods can gain market share and change how we price and deliver services. The rate of adoption will depend on customer readiness, the quality of our implementations and the tangible benefits we deliver.

We're seeing very strong interest among top customers; most are in piloting or scaling phases and progressing through evaluation and implementation. There is no structural friction—it's more about customers understanding the technology and progressing internal processes. The interest level at top clients is very strong.

One quick follow-up on forward-deployed engineers: how much of this is a rebranding of work you used to do versus structurally different? Does it require more on-site presence and change the economics given your offshore delivery model?

It's a combination. On formation, forward-deployed engineers require platform expertise, enterprise architecture knowledge, data and security understanding and solution-building skills. We are retraining and upskilling top engineers to become forward-deployed engineers, conserving much of the existing knowledge but adding new capabilities. Regarding location, discovery is often better on-site because it requires interviewing stakeholders across functions and understanding processes. However, a lot of work can still be executed offshore. So while on-site presence helps for discovery and alignment, execution can be hybrid.

With that, that's the last question we have time for today. I will now turn it back to Martin Migoya for some closing remarks. Martin, please go ahead.

Thank you, Arturo, and thank you, everyone, for being here today and for your continuous support. Thank you so much. See you in the next quarter.

Thank you.