Good afternoon, and welcome to Globant's Fourth Quarter 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 considered forward-looking statements. This includes our business and financial outlook and the responses 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 a straightforward method for comparing 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.

Hello, everyone, and welcome back. Globant has spent 20 years helping the world's leading companies build and transform their technology, developing deep engineering capability, real industry expertise, and long-term client partnerships along the way. That is and will always be our foundation. Over the past year, we have been adding a new layer on top of it. And what I want to share today is how that layer is already changing our trajectory. Enterprises are moving from AI experimentation to AI execution. After a period of significant investment with limited returns, our clients are now deciding with greater clarity. They understand AI's potential, and they are seeking partners who can deliver real outcomes, not just pilots, but production-grade solutions built with knowledge of their industry, their systems, and their business logic. That is exactly what we built with our AI pods, running on top of our industry specialized AI studios. And that is why we believe Globant is the AI-native technology solutions company. The partner enterprises are choosing to close the gap between AI investment and AI impact. We launched our AI Pods 9 months ago, and it is already proving real success with our customers. In 2025, we achieved both our highest revenue and strongest free cash flow generation ever while simultaneously restructuring our delivery organization and transforming our delivery model. In Q4, we produced the highest quarterly bookings of the year, up 32.4% year-over-year. Our pipeline remains robust at $3.4 billion. I want to use this call to walk you through our results, our strategy, and the specific metrics that demonstrate why we are convinced about the path ahead. The IT professional services industry faces a structural shift. Technology capital is flowing overwhelmingly toward AI infrastructure, with Gartner projecting IT services to grow just 4.4% in 2026, less than half the rate of overall IT spending. However, the big 4 hyperscalers are approaching $700 billion in combined 2026 CapEx, nearly triple the level of just 2 years ago. The scale of that investment is extraordinary, but it also created a massive implementation gap. In 2025, MIT research showed that most enterprise AI pilots did not deliver measurable P&L impact yet and a significant number of companies paused or restructured their AI initiatives during last year. Meanwhile, technical debt across the Forbes Global 2000 stands at $1.5 trillion to $2 trillion according to HFS Research. And Forrester reports U.S. customer experience quality at an all-time low after 4 consecutive years of decline. What this tells us is not that AI is failing; it is that the industry is entering its execution phase. After an 18-month cycle of experimentation, enterprises now understand what AI can do for their business and are actively seeking the capability to implement it at scale. This shift from exploration to execution is currently driving our record bookings. We are living through a generational transition. Think about what happened when AWS launched. It did not just offer cheaper servers; it gave birth to an entirely new industry. Cloud-native companies, modern SaaS, the entire start-up ecosystem of the last 15 years, none of that existed before AWS made elastic accessible infrastructure possible. That is the moment we are at now in technology services. AI-native delivery, intelligent agents supervised by domain experts operating on a token subscription model is not a better way to do what we already do. It is the foundation of an industry that does not yet fully exist. Globant has been the first to define what AI-native technology services look like, and 2026 is the year the market begins to validate that bet. Our core business, deep software engineering, digital transformation, and domain expertise built over 2 decades is not going anywhere. Enterprises will continue to need that capability for many years to come, and we will continue to grow it. What we are doing now is adding a new and powerful layer on top of that foundation, an AI-native offering that scales with the AI opportunity itself. For years, a company's digital products were its moat; building differentiated software required hundreds of top engineers and hundreds of millions of dollars. AI has made it faster and more accessible to build. And that is actually a demand accelerant for the entire industry. When every company can build software more efficiently, differentiation no longer comes from whether you can build. It comes from how much you build, how fast you iterate, and how continuously you evolve. We are entering an era of dramatically more software creation and dramatically faster competitive cycles. Our deep engineering expertise and 2 decades of domain knowledge now supercharged by AI, position us perfectly to meet that demand. Against that backdrop, we see 4 clear and growing avenues of demand. First, Agentic Workflow Orchestration. Enterprises need autonomous AI agents coordinated across complex systems, not point solutions, but end-to-end workflows that actually move business processes forward. Second, core modernization at AI speed. The Global 2000 carries $1.5 trillion to $2 trillion in accumulated technical debt, a massive anchor on innovation. AI-native delivery allows us to attack this backlog at a pace previously thought impossible, enabling the enterprise agility our clients need to compete and win. Third, custom software reclaiming ground from SaaS. For years, SaaS was the default answer for enterprise software needs. AI-native delivery is now expanding the range of what enterprises can build economically, making highly personalized software viable for use cases that were previously only practical with off-the-shelf platforms. This is not about replacing SaaS; it is about enterprises having more options, more control over their data, their workflows, and their competitive differentiation. SaaS and custom software are increasingly complementary, and we are uniquely positioned to deliver both. Fourth, AI governance and corporate sovereignty. As enterprises deploy agents from multiple vendors across departments, data scatters and control erodes. They need a trusted orchestration partner to govern it all and keep every interaction under their control. Our partnerships with NVIDIA, OpenAI, AWS, Salesforce, SAP, Oracle, Microsoft, Google, Adobe, and others are central to this strategy. We are the AI-native orchestration layer that makes it work for our clients. Our AI pods are AI-powered service units specialized by task and industry. AI pod software creates and evolves technology. AI agent workflows supervised by Globant experts produce working software artifacts on a token subscription model. AIPodOps automates business processes in production with institutional knowledge compounding with every token consumed. The customer owns everything, no seats, only usage. Unlike traditional models, our AI Pods operate on a subscription-based capacity model. Clients subscribe to a dedicated tier of orchestrated output with a defined token consumption cap. The delivery engine powering both is Globant Enterprise AI, our proprietary platform with 4 interconnected hubs, the enterprise hub connecting securely to all corporate systems, the AI hub routing intelligently across 140-plus LLMs while preserving full data sovereignty, the agent hub, where we build and publish industry-specific agents encoding 20 years of domain expertise, and the AI Pods hub where clients subscribe and scale. What I want to be explicit about is that this platform did not appear overnight. We have been investing in Globant Enterprise AI for years, building real products, real orchestration infrastructure, and real security and compliance architecture. That investment is embedded in our operating expenses and reflected in our current EBIT margin. In other words, the margin profile you see today already carries the cost of building a proprietary AI platform. 12 months ago, AI Pods revenue was 0. In 2025, we have reached an exit rate ARR of $20.6 million, with gross margins between 45% and 60% compared to our blended gross margin of 38%. This is not an experiment; this is a business. For 2026, we are targeting between $60 million and $100 million in AI Pods exit rate ARR. On top of that, we expect that margin profile to improve further as the subscription model scales and the cost per token continues to decline. This represents a fundamental shift in our structural profitability DNA. As AI Pods scale as a share of revenue, they are expected to expand our overall margin profile. Our AI Pods pipeline reached $283 million in Q4, up 34% over Q3 and now represents 8% of the total pipeline versus just 3% in Q2. Over 60 AI Pods operate across clients globally with 24 new subscription offerings closed last quarter alone. Several of our top 10 clients have completed rigorous security and procurement approvals and are actively running AI pods on the platform today. The pipeline is converting. The revenue is flowing, and we are just getting started. Based on the record bookings we are reporting today, the accelerating AI pods adoption across our client base, and the improving pipeline conversion trends, we have a clear line of sight to returning to positive year-over-year organic revenue growth by mid-2026. This is not a hope; it is supported by the bookings we have already signed and the pipeline that is converting. Our 100 squared accounts drove 73% of total bookings this quarter, a clear reflection of the market shift toward high-value, long-term transformations. Underlying these record bookings is our reorganization around AI studios by industry. The record bookings we are reporting today are a direct reflection of that organizational transformation we did last year. Several of our top clients have already moved past the pilot phase and are scaling AI Pods across their entire operations. Let me share a few examples. We are working with Employbridge, an Apollo-backed portfolio company, driving AI-led transformation through our AI Pod subscription model. After a successful pilot phase, Employbridge decided for AI Pods as their core operating layer, accelerating delivery and driving rapid adoption across the business. We are also working with Banco Galicia, one of Latin America's most prominent banks. After the pilot phase with our AI Pods, they performed an assessment to gauge the efficiency of the model among other vendors and similar teams. Our AI Pods ranked first in nearly every criterion, leading the institution to make the decision to move to a scaled phase with YPF, Argentina's century-old state oil company. With our human-supervised AI agents, we created a resource orchestration platform to help YPF better coordinate their complex supply chain, reaching over 5,000 providers. Our solution has already helped them reduce the requirement to contract process cycles by 30% to 40% as well as boost the productivity of their supply buyers by up to 50%. Through the use of AI on Globant's orchestrated platform, we are helping them with inventory optimization, enabling YPF's managers to obtain the best possible products for the task at hand before ordering new inventory. We have a long-standing relationship with FIFA, helping them enrich their fan engagement channels in the digital age. Through the deployment of AI Pods, we were able to move beyond traditional consulting services and achieve a major financial milestone for the organization, reducing costs by 20% without compromising the velocity or quality of our engineering output. Our initiative with LaLiga demonstrates how AI Pods rapidly transform an entire ecosystem. In just 3 months, we moved from concept to execution, deploying AI agents across critical functions like budget preparation, contract analysis, and audience data. The result is a massive leap in institutional productivity. By moving from traditional services to AI-native solutions, we are enabling LaLiga to shift new functionality at a speed previously deemed impossible. We also applied our AI Pods model to our long-standing partnership with Santander to power their new digital payment platform, Santander Pay. By deploying a specialized product definition AI agent within the pod, we cut the projected time for the app's product definition in half. This AI-native approach drove a 50% increase in the client team's overall productivity. In summary, it clearly demonstrated how we can accelerate the software development life cycle for one of the world's leading financial institutions. The professional services industry is being restructured right now. The companies that own the orchestration, the domain expertise, and the talent to supervise AI at scale will define what comes next. We will be relentless in delivering value for our clients, our partners, and our shareholders. We will be disciplined in how we invest, and we are determined to build what we believe is the defining AI-native technology services company of the next decade. Globant has spent 20 years building the foundation for this moment. We have the platform, we have the people, we have the offering. And with that, I'll hand it over to Diego Tartara, our CTO. Thank you very much.

Thank you, Martin. Hello, everyone. It's great to be here. Following Martin's perspective for the industry, we keep on firmly executing on our own reinvention and those of our clients, listening to customers, helping them understand their gaps, and curating tailored solutions that create real business value. This goes beyond cost savings and efficiencies and into strategic areas such as increasing market share or improving customer satisfaction. To do this, Globant has overhauled our delivery model to ensure that the quality of our delivery is both technology-focused and client-centric. The teams that previously executed under the delivery and operational areas have now been brought under the technology umbrella. This way, our teams operate without siloed priorities and have more cohesion between offering solution quality and delivering results on time. The result has been tech-powered solutions for our clients that have a stronger operational backing. I'd like to share a few examples with you. We are working with a leading bank in North America that is launching a strategic enterprise-level modernization of its credit and debit card platform, moving from Gen 2 to Gen 3 accounts on AWS. Globant has been selected as the strategic partner to lead this migration, delivering a next-generation cloud blueprint that elevates performance, accelerates delivery, and positions this line of business for continuous innovation at scale. This project showcases our strength in helping financial institutions that are already in the cloud and at the forefront of innovation to continue pioneering the industry. We have also been working with Trafilea, a global e-commerce group that builds and scales direct-to-consumer brands needed to rapidly migrate new client stores to their Trafilea platform. We built an AI-powered solution that automates the entire process, resulting in a 40x faster migration. This not only saved Trafilea significant time and resources but also enabled faster onboarding of new customers. In the pharmaceutical industry, we are working with PharmaMar, a world leader in the discovery, development, and commercialization of marine-derived anticancer drugs to accelerate oncology research with AI. Through Globant Enterprise AI, together, we created a multi-agent AI system that delivers more than 90% accuracy in complex data retrieval and reduces time to insights up to 15-fold, helping scientists select high-potential drug candidates for clinical development in a fraction of the time previously required. This intelligent system integrates information from internal databases, scientific publications, and regulators such as the FDA and EMA, allowing PharmaMar's teams to identify promising treatment combinations and make more informed, faster decisions. We also partnered with TOURISE to develop the foundations of the world's first universal Agentic protocol for tourism. AWS, Salesforce, Amadeus, Red Sea Global, and Riyadh Air, among others, are also part of the initiative. We presented it at Davos in Switzerland to over 30 global CEOs, and it is gaining strong traction as the standard for how AI delivers seamless, personalized traveler experiences at scale. GUT had a landmark 2025. The agency closed the year with breakthrough campaigns for some of the world's most high-profile brands, including a fully integrated 360-degree campaign, Renaissance of Snacking that took over the Las Vegas Sphere and launched Cheetos and Doritos Simply NKD product line. GUT is a genuine competitive differentiator, and its creative momentum continues to grow. Strengthening our partnerships with leading AI model developers, enterprise platforms, and hyperscalers remains a key priority. Globant continues to present its strategic partnership with OpenAI to top clients in its key markets. Weeks ago, we hosted their first multi-industry event in Spain to discuss opportunities with over 60 current and potential clients in that region. In December, AWS granted us competency certifications in both financial services and media and entertainment, further solidifying the autonomy and quality of the solutions of our AI studios. We also received the SAP Excellence Award 2025 for delivery quality in Latin America, thereby becoming the most certified SAP partner in the region. Our Salesforce ecosystem capabilities also expanded significantly, reaching expert-level implementation distinctions across MuleSoft Anypoint, Data Cloud, and Agentforce, along with top-tier partnership status across multiple Salesforce clouds. Our teams will take the stage at the NVIDIA GTC in March to share how LaLiga is transforming its business through the most ambitious AI program in global sport using Agentic AI to build connected intelligence across operations, competition management, content, marketing, sporting performance, broadcast, and fan engagement. In such a disruptive year, we considered it especially important to share our perspective with the global business community. In Q4, we published industry reports on retail, games, and our annual tech trends outlook. You can download all of them at reports.globant.com. While AI continues to dominate many conversations, the real differentiator in 2026 will be execution. Companies that want to remain relevant must accelerate their transformation journeys. Over the past year, we've evolved Globant to be the partner of choice for organizations ready to act and set the pace for the next decade. Thank you very much.

Hello, and good afternoon, everyone. I am pleased to discuss our fourth quarter results. We are encouraged by the stabilization of our top-line performance and a shift toward more optimistic client sentiment, which represents a meaningful improvement over the conversations we were having 9 months ago. We closed the year with a solid quarter in terms of operational discipline with revenues, operating margin, and free cash flow metrics above our initial estimates. In the fourth quarter, our revenue stood at $612.5 million, coming in above our guidance of $605 million. This represents a 4.7% year-over-year decline, including a positive FX tailwind of 180 basis points. Now let's turn to profitability. Our adjusted gross profit margin for the quarter was 37.6%. Gross margins were slightly impacted by the USD weakness relative to LatAm currencies and to a lesser extent by statutory cost increases in 2 of our main delivery centers, Colombia and India. However, our adjusted operating margin remained at 15.5% for the quarter, flat sequentially. We successfully optimized our delivery pyramid and tightly managed our SG&A, allowing us to protect the bottom line while we work on accelerating our growth. The effective tax rate for the quarter stood at 23.5%, and our adjusted net income for the quarter was $68.9 million, representing an adjusted net income margin of 11.3%. Adjusted diluted EPS was $1.54, consistent with our profitability targets. I am particularly proud of our cash generation mechanics this quarter. During the fourth quarter, we generated $152.8 million of free cash flow, marking the highest quarterly figure in our company's history and achieving a free cash flow to adjusted net income ratio of 221.6% for the fourth quarter or 355.3% on an IFRS basis. On a full-year basis, free cash flow reached a record $211.7 million, translating to 76.6% of adjusted net income and 203.6% on an IFRS basis. During the fourth quarter, we invested $50 million to repurchase shares as per the plan announced in October 2025. We plan to continue executing on the share repurchase program. A significant improvement in our days sales outstanding, combined with working capital and CapEx efficiencies helped drive an improvement in our liquidity. We ended the year with $250.3 million in cash and short-term investments, an increase of nearly $83.3 million sequentially. With a modest total net debt position of $116.4 million, our balance sheet remains strong, providing us with the flexibility to continue our disciplined capital allocation strategy, including our share repurchase program. Now let's move to our outlook. Let's start with our 2026 full-year guidance. Based on current market conditions, we are providing a revenue range of $2.460 billion to $2.510 billion, implying 0.2% to 2.2% year-over-year revenue growth with approximately 100 basis points of FX tailwind. We have set the lower end of our range as a prudent baseline. The upper end reflects the conversion trends we are already seeing in our pipeline and the accelerating adoption of AI Pods across our client base. In terms of profitability, we are expecting an adjusted operating margin to be between 14% and 15%. This range includes the impacts of USD weakness and statutory cost increases in Colombia and India. We view the lower end as a stress test scenario as it assumes a further appreciation of local currencies beyond today's spot rates. The upper end contemplates a more positive currency environment and the benefits of our ongoing efforts in SG&A dilution and increased utilization. We continue to prioritize our operational discipline to offset these headwinds and drive toward the higher end of our margin target. The 2026 IFRS effective income tax rate is expected to be in the 21% to 23% range. Finally, we are guiding an adjusted diluted EPS of $6.10 to $6.50, assuming an average of 44.2 million diluted shares. The lower end incorporates the conservative margin assumptions I mentioned earlier, specifically the potential for continued USD weakness. At the same time, the upper end reflects the operating leverage we expect as we scale. For Q1 2026, we expect revenues in the range of $598 million to $604 million. This is an improvement relative to prior years, where the Q1 decline was more significant. The Q1 year-over-year guidance implies at the midpoint, a 300 basis points improvement relative to the Q4 year-over-year performance. For Q1, we expect our adjusted operating margins to be between 14% and 15%. Gross margins will be slightly impacted by the weakness of the USD plus certain statutory cost increases in Colombia and India, as mentioned before. The IFRS effective income tax rate is expected to be in the 22% to 24% range, and adjusted diluted EPS for the first quarter is expected to be between $1.44 to $1.54, assuming an average of 43.7 million diluted shares. To conclude, 2025 was a year of consolidation and evolution. We have diversified our revenue streams, shifted our go-to-market, streamlined our operations, and strengthened our financial foundation. We enter 2026 with a healthy pipeline, a more efficient delivery model, which embeds AI in all our projects and the financial strength to capture the opportunities ahead.

We'll take the first question from Bryan Bergin at TD Cowen.

So 2 questions. I'll ask them both upfront here. First, just a growth clarification for the year on the upper end. I think you mentioned it assumes a solid pod demand trend that you've been seeing in 4Q. But does it also require some level of macro or broader demand improvement versus it being like the same macro backdrop? And then my second question is on the pod model on your GenAI solutions. When we think about the clients that are utilizing these pods, is it pieces of work, broader engagements? Can you kind of just talk about where it's being used specifically as well as then the net impact from like a transition from old to new, if you can kind of get us there.

Thank you, Bryan. So as for the first part of the question, the upper end of the guidance assumes that we will continue to perform very well with our pods plus some improvement in the overall market. The midpoint is the most likely scenario as usual, where we see basically more or less more of the same. I mean, no big changes on the macro, no changes, no big changes on the business overall. And that's how we build the guidance for the year in terms of revenues. As for the second part, I will let the team here.

Yes. We are observing that 7 out of our 10 top customers are highly enthusiastic about our new model. This enthusiasm reflects a shift from traditional engagement methods to an output model where we charge tokens, with tangible business results associated with our services. We are transitioning from previous ways of engagement to this new approach. Some customers are beginning small pilot programs, while others are moving from pilots to full-scale implementations without additional requests in between, due to the outstanding results we've achieved, as shown in my previous examples. This shift is transforming the company's future. We are not only able to expand our teams but also to connect directly with developments in the AI sector. We are establishing a new market for AI-native technology service companies, which require a reliable method to deliver their services using agents that perform specific processes to ensure high-quality, secure outputs, all overseen by humans. This transition has been significant; just 9 to 12 months ago, this product did not exist. Now, we anticipate over $20 million in annual recurring revenue by 2025 and are scaling with major customers such as FIFA, Santander, LaLiga, Employbridge, and others. I believe this change is very positive and positions us uniquely. Additionally, we leverage over 800 relationships with top-tier corporations and have 28,000 people ready to supervise the products we can generate with our agents and the technology platform we've developed to deliver these services, along with a business model that is groundbreaking. Importantly, this is not merely a forecast; it represents a real business, and we are extremely pleased with our progress.

Well, I guess it partly did. The aspect I'm trying to get at is you mentioned certainly, the gross margin is very high relative to what your historical is, right, in these pod structures. But I'm trying to think about the revenue transition. So if you start from scratch, great in an engagement. But if you start on a client that had an existing engagement, what is that revenue? Like you're getting more productive. Is there a netting impact there on the revenue?

No. I'm absolutely happy with exchanging the revenue. I mean, we are kind of getting the teams that we had in that customer and transforming that into AI Pods with a very different revenue proposition and a different revenue value proposition. So it's a transition that is happening slowly, but it's happening. And sometimes there are new customers. Sometimes there are customers that are working with us on a fixed price that we are delivering now in this new way. So that transition is starting to happen, and we expect that transition to gain momentum as the year progresses.

Yes. And in certain customers, Bryan, what you're going to get is that this additional productivity that we have can translate into helping them to reduce all the technical debt that you typically find in organizations. In other cases, it may be in a specific project that you are able to maybe to price in a way that is more cost-efficient. So there's going to be a lot of cases, right? But the common factor here is that a lot of the technical debt that many of our customers have, now we can be more productive and we can offer them to do basically part of that additional work with our AI as well.

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

I'm hoping that you could comment on your expectations for Latin America in 2026, just particularly given some of the recent uncertainty that's resurfaced related to tariffs.

Sure. In Latin America, at the start of 2025, we encountered some challenges, and the region showed negative growth for a few quarters. However, in the second half of the year, we began to recover and ultimately finished strongly, making Latin America the fastest-growing region for that quarter. There are various circumstances in different countries. Argentina and Chile, which are two of our key operations, are performing very well. Brazil is doing okay, meeting our expectations. We now need to assess the situation in Mexico, which remains uncertain at this time. Overall, the main countries are doing well. The recovery we saw in the latter part of the year was primarily driven by customers in Argentina. Therefore, we don't anticipate any significant challenges arising from Latin America.

Okay. Great. And then you sounded pretty optimistic about converting the pipeline as well, but I also caught in the prepared remarks that maybe you're expecting clients to look for larger scale or longer duration projects, which I would imagine would kind of change the pace of pipeline conversion and would change the ramp-up of revenue over time. So can you help us understand how that's reflected in the guidance and maybe if it's different from historic?

Yes, Maggie. So what we are seeing is shorter sales cycles in smaller deals. And the bigger deals still lagging just a little bit behind slower than we would like to in terms of closing and ramping up. But leveraging the amazing quarter we had in Q4 and also Q3, we're expecting to start ramping up onboarding and converting to revenue very quickly in Q2 and in H2 even. So it's true that clients are cautious, are taking time to make decisions when it comes to very large investments. But the robustness of the pipeline is still there. The quality of the deals is very solid. The Henry Square are performing very, very well, where the vast majority of the bookings are coming from, like Martin said, 73% in Q4. So I'm pretty confident that this combination will allow us to move forward in a very confident way.

The next question comes from the line of Puneet Jain from JPMorgan.

So with all the news flow over the last 1 or 2 months around the evolution of Agentic AI, what does that mean for IT services spend? Like Martin, you mentioned that it's time for some of those AI investments to move into execution. Are you seeing increased urgency among your clients to embrace Agentic AI given all the news flow over the last 1 or 2 months?

In recent months, we have observed that companies are taking initiative in this area. They are exploring ways to enhance their technical capabilities, replace some less robust Software-as-a-Service solutions, automate processes with AI, and substitute previous workflows involving agentic AI, while ensuring human oversight remains. Additionally, they are focused on improving customer experience. Research indicates that consumer satisfaction with interfaces and experiences has declined over the past four years, highlighting a significant technical need of around $1.5 trillion to $2 trillion, alongside a demand for better consumer experiences. This has led to a call for updating interfaces to modern standards, creating substantial demand for AI. I believe delivering next-generation AI services requires a fundamentally different approach than in the past. Think of our AI Pods as recipes or refined processes built over years, each with specific steps aimed at producing secure, enterprise-ready solutions. The output from these tools is not only more scalable but also faster compared to previous methods. Customers recognize this. Simply providing AI tools does not yield the desired results; hence, emphasizing the need for a new industry approach is crucial for realizing cost savings or enhanced productivity from AI teams. Our AI pods offer a clear understanding of how to achieve these savings, contrasting the inefficiency of just distributing AI licenses. The challenge lies in orchestrating and supervising agents in software development to achieve real productivity, which is significantly different from merely offering tools. This is precisely what our AI pods are designed to do. I am witnessing momentum in this space, and I believe it will continue to grow.

Do you think the spending on AI for core modernization, consumer experience, and AI Pods will lead to increased IT services spending, or will those budgets come from reductions in other discretionary spending?

No. I believe humanity will create significantly more software than before, and this is beneficial for us. I don't think we should settle for minor improvements in productivity or functionality. Companies are delivering functionalities faster than ever, and I've seen numerous examples of this in recent weeks. I expect this trend of growth to continue. As we are able to create software more quickly, we will consume more of it and demand greater functionality, which will ultimately lead to higher customer satisfaction. It's not just a trend; I sometimes notice a limited perspective from analysts and reports. The message I want to convey is that there is no limit to the scope of what we can achieve. The technical depth alone is substantial, and when you consider the depth of consumer experience and all the new developments, we will produce far more software than in the past. This will lead to better solutions across more platforms, with enhanced AI capabilities and a stronger development pipeline. Over the past few years, much of the investment has gone into AI infrastructure, which hasn't directly translated into demand for professional services. Previously, those investments were focused on cloud improvements, resulting in enhanced Software as a Service and more implementation services. However, that cycle now needs to be revisited. It's crucial that the technical and consumer experience dimensions catch up; otherwise, customer satisfaction will continue to decline over the years, which is illogical. Despite advancements, we are witnessing a drop in customer satisfaction with company interactions. This situation raises questions. Companies have been sidetracked by investing in AI, and now is the time to take this seriously.

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

I guess just thinking high level, Globant has always been a double-digit grower, organic grower. And this year was kind of a transition year, grew 2% for the year and obviously down 5% for the fourth quarter. What can you point to like specifically happened this year that might not be recurring in years to come? Was it just certain client consolidation? Was it any AI pricing pressure that was priced into the model? Like what exactly is the difference that happened this year that necessarily won't recur as we go forward?

You mean this year or 2025, right?

Yes, 2025 versus, yes, going forward.

Yes. I think 2025 was a year of uncertainty in general. Companies retracted budgets in many cases. I think it was a year in which macro uncertainties were extremely hard to overcome for many of our customers, and we suffered that. I think that right now, the situation is a little bit more clean in that aspect. So that increased my expectations of having a more normal year. That kind of compounding downwards from the revenue last year, we bottomed on that revenue, and we expect to come back to growth by the year-over-year by the half of this year. So the exit rate will come backto a pretty decent level of growth as we approach the end of this year. So what you see on the year-over-year is kind of, okay, it was a year of reaccommodation, restructuring, customer uncertainty, so on and so forth. The whole industry growing slower, which is kind of a killer. And now we are catching up and we are starting to grow again. And towards the end of the year, the exit rate will be much healthier than what you are seeing now. A note on the year-over-year that you are seeing, this already represents something that is stationary, right, that has to do with the moment of the year. And it represents a huge improvement from what we did last year at the same time. I don't know if you noticed that or Juan.

Martin is discussing the first quarter in comparison to the same period last year. This year's beginning is certainly stronger than last year's, but the growth rate for 2026 is still influenced by last year's performance. The exit rates for 2026 are trending towards mid-single digits, and as we compound this growth, we should be in a better position for 2027. There has been an industry-wide issue, as most companies are showing growth rates of only 3% to 5%. The growth in the sector has slowed down following significant investments made during the COVID period, indicating a transition from that phase. Nonetheless, the demand remains, and the pipeline suggests that customers are accumulating technical debt, which will need to be addressed eventually. A stronger macroeconomic environment and a robust U.S. economy should provide assistance in due course. After two years of global uncertainty, the situation has not improved much. Overall, the fourth quarter appears to mark a low point in year-over-year comparisons, with the first quarter already performing better than the fourth quarter, and we expect this positive trend to persist throughout the year.

Yes. My quick follow-up, Juan, is how do we model headcount growth and revenue per head for this year? And does that model change at all as we embrace more of the AI Pods?

Yes, definitely, yes. We are seeing that we can do slightly higher numbers; we can continue to grow our revenue per head. With the same or even less headcount, the AI Pod model by definition requires less people. It's AI Pods, which are agents supervised by some few people. So there is less need for talent. So I think that not just for Globant, but in general, the sector will start to change a little bit that trajectory of headcount and revenue that we have seen in the past 20 years. Definitely, the more we are able to penetrate our customers with AI Pods, the more the mix of AI Pods relative to the rest of the business increases, that should be a positive for revenue per head and also for margins.

The next question comes from the line of Arvind Ramani from Trust Securities. It appears that there is an issue on the line of Arvind, so we'll jump to the next question. The next question comes from the line of Jim Schneider from Goldman Sachs.

Could you provide some insight into the AI Pods business and the steps needed to reach the upper end of the $100 million run rate ARR goal? What requirements do you have to meet that target? How many additional bookings are necessary, and how much of that is supported by your current AI Pods pipeline? Additionally, could you discuss your general outlook or confidence in achieving the high end of that range?

Thank you for the question, Jim. The upper end of that range could be reached without needing many large customers to switch to that model. However, we remain cautious. We are very excited about our progress and are currently seeing engagements of $20 million, $18 million, and $15 million transitioning into this type of engagement, which is very encouraging. We anticipate achieving those figures, but I want to temper expectations as this is our first time guiding on these numbers. I don't expect to provide this guidance every quarter, so I aim to be moderate in my outlook. Nonetheless, I am quite optimistic about the potential to reach the top end of our guidance by the end of 2026.

If I can add to Martin's comments, the behavior of the pipeline regarding AI Pods is very encouraging. We're seeing a positive trend and accelerated growth. Additionally, our top customers are open to starting pilots and scaling up. When you look at the clients beginning to adopt this new technology, it is indeed encouraging. We are very confident and believe we will be close to the range we projected for AI Pods.

That's helpful color. And then maybe you talk a little bit about the profile of the gross margins for your overall business as we head through the year. Juan, I know you mentioned some issues relative to FX and regional costs that were sort of providing some pressure in Q4. Should we expect that we're sort of at a trough on gross margins and we can see acceleration throughout the year? Or how should we think about how that shapes up?

Thank you, Jim. We have indeed been affected by the weakness of the U.S. dollar. The Colombian peso, Mexican peso, Chilean peso, and Brazilian real, among other currencies in Latin America, have significantly appreciated throughout 2025. This trend impacted the last quarter of last year and is also affecting the start of this year. The dollar is currently at a historically low level, which may contribute to this situation. However, it is crucial for us to focus not only on currency fluctuations but also on advancing our business towards AI Pods, as this is where we can see productivity gains and improved margins. The more we operate under these models, the more efficiently we can manage them. While we do not anticipate massive growth in pricing for the general business this year, there is definitely an opportunity to enhance our share of AI Pods, which will help us maintain or improve our gross margins as we grow that segment.

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

I wanted to ask what in your customer conversations in January and February gives you confidence around the conversion timelines that are contemplated in your outlook, particularly given some of the client caution you've called out and some of the conversion challenges you may have seen historically?

So we are seeing clients more open to resuming big deals conversations than in the past. We are seeing also some of the volatility and the uncertainty lowering their levels in their conversations. And also another interesting fact to consider, Jonathan, is that when we architected the numbers for 2026, we were able to bake in some very relevant deals that we closed in Q3 and Q4, right? And some other deals that we are working on and hopefully will close before the end of Q1. So some of that volatility going away and some of the clients being more open and those deals that we closed and we are in the process of onboarding and ramping up give us the confidence that the trajectory will be different.

Great. That's encouraging to hear. And just as a follow-up, can you help decompose what you're expecting across your verticals over the course of the year? And are there any that you expect to decelerate versus accelerate relative to what you've seen?

When we look at our different industries for last year, financial services had a good year, growing approximately 13%. We have seen consumer retail and manufacturing performing very, very well. We continue to expect to see that behavior in that particular industry. So far, we have not seen the recovery of professional services, which has been kind of one of the drags during 2025. Technology will come back. We are starting to see some big deals shaping up with our tech customers, which was another sector that was not doing as we wanted last year. But definitely, when we look at the Q4 and some of the expectations going forward, that's going to be fine. And finally, health care. Health care and gaming, right? Those are the 2 that are big deals that have already been signed that are in the process of ramping up and that are part of the explanation of the sequential growth that we should see for the rest of the year. So that's in general, I try to go to all the industries as we report them. So hopefully, that helps.

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

On the bookings growth and momentum in the business. Great to see. So I was wondering about AI Pods and the conversations with your customers. Are you seeing the procurement teams becoming more comfortable with the AI Pods business model versus legacy?

That's a great question. Thank you. This has been one of the most challenging aspects. However, as the idea gains traction in the industry and among analysts, the procurement teams are becoming more at ease. Additionally, the fact that we are discussing something incredibly solid and significantly more transparent than the traditional model is appealing to procurement. When you can connect any produced asset to the number of tokens and understand that correlation, it provides a clearer value compared to simply stating the number of hours spent on a task. I believe our AI Pods offering is very robust. Of course, there’s a long way to go in convincing more people about this. The more support we receive, the more progress we can make. We appreciate any insights from your reports, as analysts from Forrester, IDC, McKinsey, and Bain are already presenting this method of working. According to a recent report, 70% of technology buyers are anticipating a shift in how engagements take place. The response to that shift is likely to be a monthly subscription, a set number of tokens, or some form of combination, but it must fit within that framework. Procurement teams are responding positively to this approach. That said, it is always complex, but it’s not impossible, and the business is relentless in driving this forward.

When we started this, we associated the AI Pods with the capacity equivalent to a certain number of people. Procurement is accustomed to that kind of metric. We have become much more advanced in our approach, and we are now linking consumption and subscriptions to specific outcomes, providing full transparency in the process. Additionally, we have significantly improved how we describe and demonstrate the performance of an AI Pod, which has eased the concerns of many procurement teams.

Yes. So to complement a little bit what Martin said, from the financial side, the transparency that comes with the use of the models has allowed our clients to connect the value that they are getting with the way they are paying. And we believe this is something that is enabling a much better conversation with our clients and the kind of projects that can be discussed.

Thank you very much, Arvind. Unfortunately, that's all the time we have for our question-and-answer session for today. So with that, I will now ask Martin to provide some closing remarks. Martin, the line is open.

Thank you so much, Arturo, and thank you, every one of you, for your support, for your help, and for being here today. Bye-bye. See you next quarter. Thank you.