Globant SA Aktie

[Presentation]

Good afternoon, and welcome to Globant's Second Quarter 2026 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] 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. We'll 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. Today, I want to talk about a change we are leading, a new way of creating value for our customers, delivering our work, a way of pricing it, which is already starting to compound. For more than 20 years, we have engineered the digital reinvention of the world's leading organizations, building the software products and platforms that run their businesses, delivered by dedicated high-performing teams and priced through on fixed scope engagements or time and materials. That work remains the backbone of Globant.

One year ago, I introduced you to AI Pods, a new AI native revenue stream built on that foundation, but priced on the actual output and value we deliver or on consumption, rather than on the hours we bill. As AI Pods deliver more work at higher margin for a similar price, our top line can understate the progress underneath it. As this grows, it will be relevant to assess annual recurring revenue, revenue per head, AI Pod margins and client penetration, alongside the total revenue line.

Before I go further, let me be precise about 2 names you will hear all call. Glob.AI is the platform we opened to the market last week. AI Pods are the service units that live on it, run by AI agent workflows and supervised by our experts. The revenue they create, I will call Glob.AI ARR. Hold those 3 together: the platform, the pods and the number.

This quarter's revenues grew roughly 60% to $52.8 million, and we estimate that Glob.AI's ARR will surpass $110 million by year-end. Let me walk you through it in that order. The model, the number that measures it, where the growth is coming from, how to read our reported revenue, while both models run side by side and where it already shows results. The technology services industry as a whole is growing at roughly flat rates right now but flat is an average, and averages hide the real story. Inside that flat industry, we have found a growth runway: AI native services. And it is growing because it expresses what enterprises want for AI better than a traditional hours-based approach does. Clients can tell the difference, and a growing number are moving budgets accordingly and more are choosing to work with us with this new model.

As enterprises abstract away layer after layer of complexity, infrastructure, platform, software, some are now beginning to abstract away business services themselves. We think of this as service as software. Just like how the cloud transformed software infrastructure and provided predictable and recurring revenue, Glob.AI does for professional services. You turn on the outcome and pay for what you consume with Globant's experts built in.

It opens budgets we have not had access to before. Annual spending of the global professional services industry is estimated at more than $6 trillion, roughly 4x the size of the IT services market that Globant has been evaluated in. We are taking this deliberate decision to respect our current market while expanding our offering to a larger total addressable market. We are steering clients toward the new model. Our AI-native delivery system of AI Pods has now been adopted by 45 of our clients in many of their projects.

Today, practically everything we deliver carries AI. We do not count that as Glob.AI ARR, which only captures the revenue that is delivered and charged differently on the output, value or consumption our clients receive, not on the hours behind it. It is a strict measure and that is deliberate. When this number grows, it is not AI being bolted on to existing work. It is the business model itself changing.

Glob.AI ARR reached $52.8 million as of June, up from $32.8 million in March, roughly 60% growth in a single quarter. We have seen plus 30% more productivity than with a typical engineer plus AI approach. Pipeline stands at $436.8 million, up from $352 million in Q1. Adoption has reached 45% of our top 20 accounts. Gross margins on this model run close to 10 percentage points above our traditional delivery. We now expect to exit 2026 at no less than $110 million in Glob.AI ARR. That is the yardstick, AI-native revenue becoming core to how we believe the market should value Globant, measured quarter after quarter.

These changes have affected Globant as a whole as well. Globant's revenue per head reached $95,800 on a run rate basis, up 9.7% year-over-year. We are delivering more value with the same talent and capturing it. Glob.AI ARR captures 3 of the biggest waves of demand in our industry. They are core modernization, experienced debt and agentic process transformation. We have shared them with you on previous earnings calls. What changed is that all 3 now convert increasingly through AI Pods.

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

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

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

We keep seeing the pocket of growth I mentioned earlier, demand for AI Pods. We are choosing to accelerate these migrations, even if it means a short-term impact on revenue. Because over time, it creates more value for the client with predictable outcome-based consumption and more value for Globant with higher margins and access to more sophisticated projects.

This quarter, 96% of our revenue came from repeat customers, and we grew our top 20 and top 50 clients by 6.6% and 6.9% year-over-year, respectively. This is concentrated where Glob.AI and AI Pod penetration is highest. Our Data and AI Studio is now our second largest studio by revenue, close to 11% of sales and growing close to 35% year-over-year. Our AI studios are increasingly selling AI-native services alongside traditional staff augmentation, and providing their depth, since that top 50 growth is a sign they understand these clients' industry as well.

Our core business is acting as the distribution engine that carries Glob.AI, and the AI pods that run on it into large enterprises on relationships built over 2 decades. Pipeline and bookings are at a healthy level. Its composition is shifting towards AI, data, cloud and integration work.

Having said all this, we are operating in a tougher environment this quarter: Geopolitical pressure in our new markets, volatile oil prices weighing on travel, and longer decision cycles in North America. Juan will take you through a revised outlook for the full year.

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

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

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

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

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

And with Vercel, clients can ship AI built applications natively in a single click, turning multi-month projects into same week deliveries. Together, we launched Vercel-powered AI Pods, agentic units that design, develop and modernize enterprise digital products on [ Next.js ].

FIFA is using AI Pods powered by Glob.AI to scale its digital ecosystem into a continuous, personalized experience for football fans worldwide. Its key platforms recognize fan preferences across competitions, and powered by AI Pods, use real-time data to generate new experiences year-round.

This quarter marked 3 years since the foundation of our partnership with British Airways, delivering a platform built for speed and continuous innovation. In June, British Airways reached an important milestone on this transformation journey with the launch of their new mobile app, following extensive testing to make every stage of the customer journey simpler and more intuitive, acting as a real-time travel companion. Positive customer feedback has highlighted the improved user experience, particularly the live flight notifications feature.

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

GUT delivered a solid Q2 2026, culminating in another standout performance at the Cannes Lions International Festival of Creativity in June. The network earned 22 Lions, including a third consecutive Grand Prix for long-standing client, Mercado Libre, the first agency client partnership to achieve this milestone at the festival. GUT also launched new work for Google Chrome and Ray-Ban Meta, created the world's first clay bar for Stella Artois at Roland Garros during the French Open, and introduced Rimowa's For a Lifetime of Lives Platform, celebrating craftsmanship through stories of longevity and evolution.

We are building a meaningfully different services business deliberately with a growing base of revenue underneath it. And with a number I have asked you to hold us to every quarter. This next chapter also means disciplined choices today, including decisions on our cost base to fund the transition and protect our margins. I do not take those lightly, and I'm grateful to our teams for the resolve they are showing.

Thank you to our clients, our partners and our Globers around the world building this alongside us every day. With that, Diego will show you the machine underneath. Thank you.

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

The legacy professional services model trades human hours or custom solutions, forcing engineers to solve the same foundational problems repeatedly. Glob.AI breaks that cycle by operating as an asset-based engine. Within the platform, we codified over 2 decades of enterprise engineering and industry domain knowledge into curated battle-tested playbooks. These are deterministic documented agentic workflows designed for production-grade reliability.

Because these agentic assets are modular and validated, we achieve extraordinary cross-industry compounding value. an IT root cause analysis workflow built for an airline client, for example, can be replatformed into a pharma supply chain or media distribution pipeline in a matter of weeks rather than months. AI Pods serve as our direct vehicle for monetizing this compounding IP, taking clients from a natural language challenge to production-ready deployment without the traditional friction.

As we set out in introducing Glob.AI, raw LLM prompting produces significant token waste, hallucinated logic and expensive retry loops that includes additional time for human supervision. Glob.AI solves this through structured deterministic process optimization. Before an AI agent executes work, our platform automates context assembly, architecture mapping and data preparation, enforcing automated quality gates at every step. By optimizing the orchestration layer, we ensure that every token consumed yields verifiable production-ready output.

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

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

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

Glob.AI works at 2 levels: your organization and your projects. Your organization is the foundation where you can figure the tools and settings that apply to all your projects. Your projects are where the work happens, each with its own goals and one or more AI pods running simultaneously at different prices, which always include not only the tokens consumed, but also the human supervision required for the project.

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

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

Right below, your customized dashboard also gives you 4 key metrics. Selecting the period, you can see the spend, tokens used, tasks total and artifacts produced. Beneath that, a quick summary, your active goals, the units of work in progress, always visible at a glance. And finally, your AI Pod fleet, the specialized teams running your delivery.

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

Goals are the units of work your AI Pods will execute. And you create them by simply telling the agent what you want to achieve. You can connect the repository and let the agent analyze your code base directly. You can describe your needs in plain language or you can attach a document and let the agent extract the requirements from there. Either way, the agent proposes the goals, you review them, you approve them. And if something needs to change, you tell it directly or bring in your expert, always available in the chat with full context on your project.

When you're ready, you say start. That single action locks in your project and hands it to the forward deployed engineer who supervises every step of what comes next. Artifacts is your shared workspace for project files. Here, you'll find every document, spec, [ ABR ] or implementation summary produced by your AI Pods, ready to preview with a single click. You and your FDE can all upload files here, keeping everything in one place.

Some artifacts will also be delivered directly to your GitHub repository as commits or pull requests. Clicking on your name gives you access to your notification settings. You choose how Glob.AI reaches you: e-mail, WhatsApp or Telegram. And you decide which events trigger each channel, approvals waiting on you, actions required, new deliverables or run updates.

Clicking on your organization gives you a complete control panel with 4 tabs: Overview, with all the general information; Members, where you manage your team; Billing, your full financial picture; and last, Usage, a breakdown of consumption for the current cycle.

The capability behind Glob.AI is not built on theory. It reflects what we have been proving on the ground.

In our previous calls, we shared how early AI Pods deployments drove milestone efficiency gains whether accelerating drug discovery research at PharmaMar 15-fold, compressing supply chain contract cycles by 40% at YPF or reducing legacy migration time lines from 14 months down to 2.

What makes Glob.AI so significant today is that those custom high-impact successes are no longer bespoke projects. We have productized those learnings into our standard catalog. Backed by our deep co-engineering alliances with hyperscalers and model providers, Glob.AI turns those proven enterprise outcomes into an on-demand, repeatable capability accessible to every client from day 1. We have built the underlying platform, secured the governance framework and proven the economics at scale. Everything I just described is what compounds behind one number: Glob.AI ARR. We look forward to driving this next chapter together. Thank you very much.

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

Revenue was $614.4 million, within our guided range, slightly up year-over-year, up 1.2% sequentially. On a year-over-year basis, Q2 revenues included 80 basis points of FX tailwind.

From a geographical standpoint, compared to the prior year period, Europe and Latin America expanded by 6.8% and 5.9%, respectively. Conversely, North America experienced a 2.4% contraction and new markets saw a 17.7% decrease. The new market segment represented a consolidated drag of roughly 115 basis points to the year-over-year revenue growth figure. Due to the ongoing conflict, this specific geography suffered unexpected project delays over the course of the second quarter.

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

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

In response to these conditions and to optimally align for subsequent expansion, we initiated a business optimization initiative in Q2. Through this initiative, we ensure the acquisition and retention of the capabilities required for our AI-focused strategy while simultaneously rightsizing our cost baseline to the prevailing market landscape. The main actions under this plan included a comprehensive review of our workforce to align skills and size with our strategic priorities, a consolidation of our global office footprint based on an analysis of our facilities and lease contracts, a strategic prioritization of our delivery centers to support future expansion.

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

Despite FX headwinds, we plan to improve margins with the additional efficiencies planned for Q3 and increasing our AI Pods in the mix, which [indiscernible] with margins above company average.

Adjusted net income came in at $60.3 million with a 9.8% adjusted net income margin. Adjusted diluted EPS ended at $1.40.

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

On capital allocation, the share repurchase program our Board authorized in May, up to $125 million over 6 quarters, is active. At today's valuation, buying Globant remains one of the highest return investments available to us as the market is pricing Globant as a legacy services company in a soft cycle when what we are is the fastest-scaling AI-native delivery platform in our industry. At the current valuation, the company is trading at double-digit free cash flow yield on a normalized free cash flow basis.

Now let me turn to our outlook. Three external factors have primarily impacted our May expectations, and our revised guidance incorporates all 3. In May, the lower end of our guidance contemplated a significant deterioration in our new markets region that, at the time, was not reflected in our forecast. That scenario materialized, and our expectations for the second half of the year have now changed in the region. Our commitment to the region is long term and important relationships there continue to grow. But the prudent assumption today is that this environment persists in the short term.

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

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

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

We expect strong free cash flow generation in the second half, consistent with our seasonality. And our capital allocation priorities are unchanged: the repurchase program and the continued build-out of AI Pods.

The business optimization initiative we carried out this quarter will be visible in our margins as we exit the year, positioning us to enter 2027 with a leaner cost base, record revenue per Glober and the highest margin delivery model, AI Pods, approaching by year-end close to 4% of revenue on a run rate basis.

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

Thank you, Juan, and hi, everyone. [Operator Instructions]

And with that in mind, we will take the first question from the line of Bryan Bergin from TD Cowen.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The next question comes from the line of Tien-Tsin Huang from JPMorgan.

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

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

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

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

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

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

How much was the FX impact in the last year?

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

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

Yes. We're seeing very good traction on the 100 Squared program. Indeed, it grew -- that group of customers grew -- the top 50 grew like 7%, something like that. It's extremely encouraging, right? And it is where we're delivering these new things and the first experiences during these last 9 months of execution or a year of execution of our AI Pod. So this is very encouraging by itself.

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

And these 2 models is a place in which you can optimize margins, you can improve supervision. You can do it more with less. Or maybe in some accounts, we need to put more supervision for certain specific projects, but it's managing a totally different manner from before.

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

So making a parallel between those 2 things, sometimes it can seem difficult. And honestly, we have not much story. I mean we have 1 year implementing this. We already have some signals. It's enough for us to put a pricing on those million tokens or this output that we are charging. But we need to see many more things happening to be able to take the kind of conclusion you want.

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

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

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

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

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

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

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

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

And also there's a market share gain too, because when you present this new way of doing things and new way of charging things, for every dollar you sell on this new model, you are able to capture maybe another do, right, of that same budget because you are doing things that other vendors we are doing. So we're extremely excited about those 2 things happening at the same time, expanding into other places and capturing more dollars for that work that we used to do.

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

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

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

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

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

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

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

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

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

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

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

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

I was going to say, Bryan, that sometimes what we've seen is that it may take longer, a lot longer, to convince to persuade the procurement teams and our customer to transition and keeping the same level of revenues with more productivity. So sometimes, we're seeing that -- we know -- we want to migrate, okay? And sometimes, we can do it faster if we're willing to provide some efficiencies immediately to the customer in terms of price. But we believe that because the model is so much more efficient and so it makes so much more sense for them, that we should be able either to expand on other areas of the organization, to win market share from other vendors because we -- I mean what we believe is that this is a model in which we need to deliver services. Now if we can do it faster, we will do it. And I think that's a key message that we are giving here. .

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

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

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

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

And I think that explains the sharp increase. If you look at the revenue per head, 3, 4, 5 years ago, it was around $60,000, $65,000 per employee. Now we're getting close to over $90,000 and getting close to $100,000.

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

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

And then second question around that is you also mentioned a lot of those clients who are leveraging Glob.AI is existing clients. But how many clients -- or what percentage are like kind of new clients, right? Like who are not using that?

And just last question on that is that what's kind of Globant's kind of unique value proposition, right? Is it around enterprise context? Is it around routing logic? Like what's proprietary to you?

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

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

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

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

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

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

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

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

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

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

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

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

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

Now to do that same thing, even with Globant in a traditional way, would have taken at least 2 or 3 weeks, because of the meetings and the things and the scope gathering, all those things, all that process that was extremely inefficient before has been concentrated in a very simple way of doing it now.

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

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

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

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

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

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

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

Now that's demonstrated on the top accounts that are growing at 6% and 6.9%.

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

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

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

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

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

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

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

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

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

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

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

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

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

Good afternoon, and welcome to Globant's First Quarter 2026 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] 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 1 week earlier, Anthropic launched a $1.5 billion Enterprise AI venture with a different group of PE firms. The 2 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 6 quarters, representing close to 7.5% of today's market cap and close to 15% of market cap in aggregate between the 2 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 2 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 2 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 3. 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 5 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 3 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 4 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 3-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 by 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 1. 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 3 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's 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 Lat Am. 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 2 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 Lat Am 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 2 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 Lat Am 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.

[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 -- sorry. The pipeline remains in a very healthy state. Conversion is quite good. We're seeing large deals that we have been closing during last year and also closing during this first quarter that will gain traction moving forward. So it's configuring like a space in which we'll have like several big deals starting to yield some results moving forward, and we are very happy for 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 and the amount of the price of the fuel that is kind of changing the landscape for some trips. But in general, we see a quite positive environment in terms of bookings, long-term deals, which are extremely important that are coming back and gaining traction.

And one remarkable thing that I would like to mention is that the growth on the main accounts is way above what we are seeing in the full company, right? So this is kind of the result of the focus we are having on the 100 square accounts and the focus that we are getting on those large customers that are needing more than ever. When we talk about AI Pods, we're talking about a way to deliver the traditional services. We're not talking about a specific offer, but we're talking about the broader conversation, too, and a new way of delivering that broader conversation in a way which is AI-native. So I cannot split the conversation from the AI Pods from the broader conversation. But yes, I can say that in general terms, conversations are going in the right direction.

Okay. 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 gross margin assumption for the year, are you including any tailwind from these -- from the AI Pods structures?

Sure. So in the first quarter, compared to the last quarter, we see about 1 percentage point of FX headwind coming from mainly Colombia, Brazil, a little bit in Mexico. In terms of -- for the rest of the year, so far, the assumption is the same. I mean we cannot predict what's going to happen in terms of FX, but we will definitely work to be as efficient as possible to increase utilization levels as different ways to offset part of that. And we do have very little positive impact being assumed toward the last part of the year.

As you know, last quarter, we mentioned a run rate -- an expected run rate of $60 million to $100 million of AI Pods, and that's going to be towards the end of the year. So even though it's growing very fast, it is still a small part of our business. But what is more interesting is that this continues to scale the way it is scaling? It's a good place to be looking into the future, right? Because this model is proving to be with better margins overall relative to the rest of our business or to the rest of the delivery models.

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?

Yes. I mean as always -- I mean there is competition. But at the same time, we see that as we scale projects with AI Pods, we improve significantly our agents. We improve how we use the different models and the tokens. And also they get more efficient because the agents that we build, as they learn, as they evolve in the project, they get more efficient as well. So I think that, that's going to take us or that's going to help us offset whatever pressure might come from other places. So the expectation for us is that the AI Pods delivery model will overall deliver higher margins than the other more traditional...

We are in the trend of growing revenue per head for many, many years already, right? So this is constantly reflecting the way we understand how to scale our business, always looking for margin or looking for new practices and innovation, and customers are reacting quite well 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. And maybe you could just comment on how those capabilities differ from your historical workforce and what additional changes do you need to make to the workforce to continue to capture market share?

Yes. I will answer the first part. The second one will be on Diego. The forward-deployed engineers is something that we have been doing for many, many years. We didn't call it that way. But our engineers working at our customers' premises and understanding the processes and trying to propose like new ways of doing things. And now they became like agents of transformation, but instead of using just one platform, they can use pretty much any platform. And so they are being very welcome within our customers. And this is something we have been doing forever.

And now I think the next generation of understanding or knowledge has to do with changing full processes. I mean processes that before were impossible to change. Now it's possible to automate or at least thinking in a totally different manner. And that kind of mindset is the mindset that we are embedding and putting into our teams in front of our customers or forward-deployed engineers in front of our customers. I don't know, Diego, if you want to complete.

No, I think Martin captured pretty well the whole idea. So Maggie, just to give you an idea and similarity, this is the actual version of what an enterprise architect used to be. The thing is they're called deploy because now there's a platform involved that you need to deploy and then implement. And implementation is exactly what Martin said, which is having knowledge on how to map the company's data structure, architecture, different components, connect that and build and create the platform for building the solutions on top of that. So it's that typically accounts for the top-notch engineers, the most senior-tier engineers. And like you said, they tend to contribute to that revenue per head uplift.

Next up is Tien-Tsin Huang from JPMorgan.

Martin, I like your comments on the -- in the prepared remarks about the rewiring of the industry and things like that. So I'm just curious, just to focus on that with these LLMs investing in services, how do you see the competitive landscape changing? I know we've seen this a little bit before in software and enterprise software. Do you see it differently here? It is a validation of services, of course, but not sure exactly what their long-term intent without domain knowledge can be like what Globant has. So how do you see the competitive dynamics evolving here?

That's a great question, Tien-Tsin. Great to see you back. So first, I believe that the massive change that is happening and the things that must be done moving forward are so large, but so large that there's no way that all those things can be captured by just 1 or 2 companies, which, by the way, wouldn't be independent. So I think the value of being an independent company, the value of being able to create and facilitate -- can you hear me?

Yes.

Okay. Sorry -- so the value of creating and saving the tokens that the customers are producing, the value of advising your customer and reengineering the processes without any bias and being able to use the best possible technology is still there. So I know -- I would like to say that I've been in this business for many, many years, and we have seen many times in which companies are moving back to services from product to services.

And I believe this is a huge stamp of approval that we have been talking about that for the last 2 years. I mean the big prize is deployed. It's not just the model. And we are playing the game of deploying it. And our relationships with our customers and trust and confidence and level of innovation is absolutely there. So I see this as a very exciting news. So I don't know, Diego, if you want to...

I want to make a little comment. We are actually in conversations with our partners. The same companies that are putting together their services are in conversations with that. And this is actually the model that the industry has been having for 20 years. It's what Amazon does, it's what Google does. They all have services capabilities, Microsoft as well. And that's the excuse to capture business and route it to the partner network. So a ton of the work that we do for AWS, as an example, comes from AWS themselves. So this is actually a very -- and that's why their team is actually so small in scale. So the idea is the major lift of this type of work should be done through their partner networks, but they need to be able to capture. If they don't provide services, they are not a go-to person for capturing that.

That's a full demonstration of what we do, 100%.

Yes. No, I'm glad you guys answered it that way. It feels like a validation, and I think the market, hopefully, will appreciate that. Maybe just my quick follow-up, just to ask a model question for you, Juan. Just thinking about -- I think you talked about it earlier, Bryan's question, but just thinking about Q1 being the trough, 2Q seeing a little bit of sequential growth. Should we continue to assume it builds from there based on the backlog of work and what you expect in terms of closed sales? I mean should we walk into faster accelerating growth and then we exit the fourth quarter a little bit faster, assuming there are no other surprises from the macro?

Yes, definitely. When we look at the fourth quarter last year, we did -- we closed at minus 4.7%. We look at this quarter, it was minus 0.7%. The next quarter -- and between Q1 and Q4, there was some sequential decrease. Now when we look at Q1 to Q2, we're going to see that there is sequential growth. We might also -- depending on where we land within the range, there's a chance that we end up with some year-over-year growth. And when we look at the second part of the year, the combination of more working days that are still relevant, plus what Martin explained at the very beginning, some large contracts that have already been signed, they will start to generate incremental revenues.

I think that's what should help us to have sequential growth both in Q3 and then in Q4 and probably end the year in a much better way when we look at the year-over-year growth. And then on top of that, we will see, hopefully, the acceleration of our AI Pods that should be very -- I mean should be -- it is important because it's going to start helping us not just on the growth, but also on the margin 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. Maybe is that just a sales focus and a little bit about maybe 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. Thank you, Bryan. I'll take that one. So we are seeing some very strong growth on our top 10 clients, around 4% and quarter-over-quarter. And that is a result of the 100 square strategy where we've been investing so much focus and effort. When you take a look every sample that you take from our top 20 clients, you'll see that the growth is really much higher than the rest of the lineup of clients.

And the kind of work that we are doing largely focuses on AI-infused projects. We are advancing conversations around migrating existing operations or starting new development with AI Pods in the vast majority on our top customers. So a lot of focus on using AI to gain efficiency to develop faster, better to get to market in better shape to deliver more features and to test these products with consumers in real-life production in shorter iterations.

One very good example of that is Disney, where we're also seeing some very nice recovery this year compared to 2025. And where the focus of the new CEO, Josh D'Amaro, is really interconnecting the Disney guests, the Disney customer experience using Disney+ at the center. And by having Josh coming from parks and experiences, he knows very well our work with Disney for so many years, and we are very well positioned to capitalize on his strategy moving forward. And at the same time, obviously, we are also having with both Disney parks and Disney media, a ton of conversations around migrating their operation to AI Pods as well.

I want to add something to that because I think it's important. You talked about large customers. And with every single large customer, operational efficiencies and getting the most out of money is still the conversation. It's there. And those large accounts, those top accounts, typically, they either belong to a heavily regulated market like airlines, banks. They have very high standards of security. And when you see that, we have deployed AI Pods on 40% of the top 10, correct me. 40% and more are on the way, which pretty much not only validates AI Pods, the concept with top clients, but also speak, most of those companies are pretty advanced when it comes to AI. It's not like they haven't tested, they haven't done it. And still, they found a lot of value there. So I just wanted to add that because I think it connects with what they needed and what Fernando mentioned before.

No, that's really helpful. And then just a quick follow-up. Middle East exposure in general, how much do you guys have? And what's the outlook for Middle East kind of going forward? Will it -- I mean have you built in some cushion for potential disruption there?

Yes, I'll take that one. So when we look at new markets, that accounts for about 6% of revenues. Middle East is about 2/3 of that. In the numbers that we provided, the midpoint basically is assuming that things will continue more or less the way they are. We are seeing deals getting closed. We are seeing some deals actually starting, hopefully very, very soon.

The strong pipeline as well.

The pipeline is very solid. So the way we build the guidance for the year, basically the lower end would imply a significant deterioration of that business. That's the main assumption on the low end is a deterioration from today that so far, we are not seeing it in our numbers.

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

Good set of results. I wanted to follow up on the question Tien-Tsin asked earlier. Certainly kind of validation sort of these Anthropic and OpenAI making these investments, it validates the services model in terms of like last-mile delivery. I think that's quite clear. Do you all kind of view them as a little bit of competition because they're going to be out there grabbing some resources, competing with your clients? And how do you view the competitive environment? And just on that as well, if you can also comment on sort of the relationship you have with Palantir.

Arvind, thanks for your question. This is an extremely large market. I mean as I was saying before, every day, there's a new company that is trying to compete there, and these guys has very good distribution. But they have some, I would say, some things that are structural. For example, any of those 2 companies that are being formed right now cannot offer like model independence or cannot offer now like the way of -- I would provide you with a piece of advice, which is absolutely the best for you, right? And that's something that is difficult to cope with. But of course, we see them as a competitor. We see them as also a partner because we do things and they will do things through us.

We have built in these years, in these 23 years, exactly what they want to build right now. This is a massive support to our long-term business. And the other thing is this is not a business in which one winner takes all. There are other business in which one winner takes all. In this business, there's a -- it is a business in which the relationships with the customers count the whole relation -- corporate relationships and MSAs you have and people that knows people and things like that counts a lot. And I would say that this is a scenario in which we have a lot of assets and a lot of things that we developed with the years to cope with that.

So again, this is a massive market. I said $2 trillion, only for technology. If you expand that into BPO, into core process, all the processes that you have outside there, it is much larger than that. So I don't know. This is something that is too large. The change is that much. We are innovating. We are bringing the latest way of thinking to our customers. The customers are loving it. I feel extremely confident. I feel extremely confident that for us, it's only a great signal of what we're building, as I said on my opening remarks.

Yes. Yes. Martin, I would agree with that sort of my own research also suggests that enterprises are looking for multi-model approaches because if you just kind of go with a single model, whether it's Anthropic or OpenAI model, you kind of are locked into that model, right? But -- and then you're kind of stuck with their pricing and kind of development. But if you have this multimodel orchestration layer on top, then you can -- and not just these 2, right, you can even use some Chinese models. So what are you saying makes a ton of sense.

Not only that, Arvind, but also hybrid models where you...

You can switch.

You can actually use your own locally run chip models for simple things. So yes, that is totally correct.

Right, right. And if I can just also maybe reask the question on Palantir, right? Because, I mean are you all seeing Palantir on certain deals? Do you look at them as a partner? Or do you compete with them? Kind of what's your approach on Palantir?

No. We see them as a partner. I mean we like them. They're a great company. They -- I think that in certain places, in certain specific situations, we cooperate. So again, we are a company that needs to solve the problems of our customers in the best possible way. And that commitment that we have and that we will continue having is independent on any of the products that we use in the back.

And sometimes we have things that can do a good portion of what our customers need, we use them. Some other times, we need to go with a partner and we go with a partner. But what is not compromised in any of our decisions is that what we are proposing to the customer is the best for them. So I see Palantir as a company that we can cooperate, that we can expand our relationship, and we respect them a lot. They have a great product. And we believe that in certain places, we will cooperate with them.

Perfect. And then just kind of a quick follow-up, right? I mean certainly, a good set of results. When I think of like guidance, which is reaffirmed -- was that reaffirm mostly because you're being a little bit conservative? Like why not raise guidance in line with the beat and the momentum and all of that?

Arvind, there is -- as you know, we have part of our business in the Middle East. The situation there, as you know, changes all the time. And we need -- we wanted to be in a safe place and not take unnecessary risk at this point in time. There is nothing to gain from taking too much risk on the guidance.

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

I'll just ask Slide 2 upfront. So Martin, I'd be interested in your perspective about Globant GUT. It seems like it's kind of like the higher end of strategy consulting. And I'm wondering how you can use Globant GUT to generate incremental revenue downstream. And then, Juan, if I could just ask, last year, macro was under pressure in Lat Am. If you could just give us the macro for -- the quick notes on macro, macro for dummies in Latin America, that would be great.

I would take the first. I will ask Diego to complement. But GUT for us is a very good way of entering customers, marketing and technology and to the AI gets connected deeper every day. And the kind of caliber of ideas that these guys are having is really impressive. When I see the reviews that we do every month with the teams, and I see when the guys from GUT come, it's very rewarding to see the caliber of campaigns, the caliber of ideas, the caliber of customers that they are getting. And this is for us, like a door open for then come with all the rest of innovations we have on the technology side and keep on selling. I see this as a magnificent vehicle to expand that relationship that every day, marketing, technology, operations will be more integrated into the same thing. And we can, as a company, tackle those 3 things with our offering.

When we look at Latin America, we are seeing a more stable scenario. Argentina is the country that is driving most of the growth in the region right now, followed by Brazil. But in general, I think it's a more stable scenario relative to other years.

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

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

In the second quarter, no?

No. I mean -- so basically, when you look at the first quarter and April and the couple of weeks from May, situation is similar. We are not seeing big changes there. Overall, we had a very strong Q4. As you remember, it was a record quarter. That is helping us a little bit on what happened in Q1, where we were able to exceed a little bit our initial guidance. And it's also helping us to reaffirm the full year. The level of bookings that we've seen in Q1 and in whatever has passed of Q2 is also allowing us to maintain the guidance even in the situation that we know that the new market region is under a little bit of stress. But so far, no big changes, and that's enough for the guidance that we have today.

Got it. Appreciate that color. And what in your customer conversations gives you confidence around that back half ramp, particularly around sequential growth in the fourth quarter? And how much go-get is potentially needed there?

So I mean, as we were discussing before, part of the -- or the second part of the year has 2 main components. One, which is a higher number of days in the second half of the year. And the second one is there is basically 4 large customers with whom we have already signed contracts and those contracts should be able to help us because they are scaling as we speak, right? One of them is a professional services company that has been one of the drivers of the lack of growth in that sector that is coming back. There is a big tech company that we recently became a preferred vendor that's going to help us also on the second part of the year. So -- and then we have already spoken about a gaming company in the last quarter and a PE-backed company as well. So those 4 contracts that are scaling as we speak, combined with the account days of the second half are the drivers of the second half of the year.

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

Congrats on resilient results, really great to see. So I was wondering if you could discuss a bit more about the early customer feedback from AI Pods. And specifically, what are they saying are the greatest benefits from the program? And if there are specific industries that are seeing more traction than others currently?

So like I mentioned -- sorry, like I mentioned before, one of the good things is that the data comes from our top accounts, which are the main drivers of the growth of AI Pods. So 2 different things. The first one is the benefits of the models, both in terms of efficiency but also in terms of the quality of the outcome. So we've not just proven that we can produce faster, but actually that the quality and the full product and release is top notch, right, according to the standards.

So feedback has been very positive. In fact, a lot of the growth, we typically -- the way we do AI Pods is we have an experimentation phase -- we have -- and then we have a scaling phase. And so typically, you don't scale if you haven't passed a testing, right, a POC, only one part operating under this model and then they do the switch. So it is important to understand that when we are reporting revenue, it's actually -- it has been tested. A couple of things that I think are super important and make a big difference.

First of all, the process is baked into the tool. And this is actually great. This is the first time we can do that. Before that, the process was actually a manual, if you wish, and you train people to follow that process. Now it's being baked into the tool. So it's a lot more resilient to people and it holds your knowledge. The second one, token consumption. This is something that we haven't mentioned, but it's extremely -- it's becoming extremely important. A lot of the companies that have implemented tools such as cloud code, Copilot, et cetera, they're working with them, and they're not getting the most out of that.

But on the other hand, they have increasing spend on the token consumptions that start to be actually part of their P&L, an important part of the P&L. And part of that consumption comes from misuse of the tool. which means incorrect prompting and data preparation, incorrect description of the process you must follow, quality gates, et cetera, et cetera. So a task well executed typically takes 1/3, 1/4 or even less tokens than the same task with reprompting corrections, et cetera, et cetera. So that's another interesting and important data point because you can actually see the tool in action and you pay for what it actually produces output.

So feedback so far has been great on every single implementation. The efficiencies have been shown, and that's why it is a keeper. We have had not a single client actually going back from AI Pods, which I think it's a solid statement of the benefits it has.

Yes. And also 2 more things. The fact that you can have like an enterprise-ready process baked in into that thing. I mean there are plenty of people now by coding solutions inside corporations. But then they're local in their machines, they're not scalable, not secure, not ready for the enterprise. And with our AI Pods, we're being able to grab those things and those ideas and take it to the next level in terms of enterprise readiness. So that's extremely important. How the process is documented all along the way, and we have an enterprise-ready kind of solution, right?

And then the rest of the things is just benefits, right? You consume less tokens, you have a corporate process inside there. You can repeat the process and improve the process every time with your customer, you can customize the process with the data of your customer. So it's much better than the traditional services. This is what Diego was describing, is a real AI-native service as opposed to the traditional service. And this kind of scale on supervision is more similar to an assembly line rather than just a massive matrix of projects that you need to fulfill. So the current business is not going anywhere. And as you see and demonstrated, it will keep on being and keep on existing.

But this AI Pods is on a different level of execution, totally AI-native, totally AI-driven plus human supervision and it's being charged per consumption. You don't need to interview people. You don't need to do anything. You just submerge it there and everything gets executed with enterprise class and human supervision to ensure that you are doing the right thing.

So it's really a different value proposition, and our customers are really welcome it because it's a totally different way of being transparent to, right? A full transparency in each asset that we create, each artifact gets connected to a number of tokens, get connected to a number of consumption that you have there. So it's really paying by the output rather than paying hours. So it's really a new model.

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

My question is on capital allocation. So buybacks, of course, suggest the confidence that you have in the stock. But on the other hand, it could limit potentially strategic M&A. So if you could please share how do you see the need for M&A in the short to medium term to remain competitive?

We are always looking for things and for opportunities. That won't go away. And the other thing on the buyback, right, was -- it's at management's disposal. And as we see an opportunity to buy the company that we know that is Globant, and that we trust, and we think it's undervalued. So -- but if we find a better opportunity or better use to invest, of course, on our AI Pods or a company that we like and we want to acquire, so on and so forth. I mean we are not limited in doing so. So a constant assessment on which are the priorities for our capital is being carried out, but we want to be extremely disciplined in how we increase our return on equity or return on invested capital moving forward. I don't know, Juan, if you want to.

No, definitely. We have the firepower to do M&A in case we want. But of course, I mean there is one stock that today is trading at a very low multiple, and it's a company that we know very, very well, and that's our company. So between that and buying something else, sometimes it really needs to be very, very strategic. It really has to meet a very clear need for us at this point to go and do that because at the current valuation, there is a mismatch between Globant and some companies in private sector.

Very clear, guys. If I may follow up. I think last quarter, you guys seemed a little bit conservative on tackling fixed price contracts, mainly on margin concerns. And we see fixed price as a percentage of revenues roughly stable versus last quarter. What's your current view on that?

Yes. The market today pushes for fixed price. It's something that is a reality across the industry. Interestingly, now we have tools that allow us to deliver in a more efficient way. So we can use our AI Pods to deliver on many of those contracts. So we are more confident on the fixed price than what maybe we would have been a year ago or 2 years ago. So it's something that we need to look at because the market is pushing for fixed price. And the tools that we have today in front of us allow us to do better than -- or to do well in fixed price contracts as well.

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

I guess, Martin, you've been very clear about the ambitions for the AI Pods model. Is 2026 effectively the year that you're gathering, I guess, data points to kind of really push forward with the strategy at this point? How do we think about where the longer-term ambition is? How much of your revenue can you get there? And then what is the current friction in terms of why clients aren't adopting it faster given all of the data points that Diego kind of highlighted?

I didn't get the last part of your question, Surinder.

The last part is just that Diego highlighted a lot of really positive data points about the AI Pods model. And so how do we think about that in terms of why clients wouldn't be adopting it faster? Is there a natural balance within your business ultimately in the long run between the AI Pods model, maybe fixed price contracts? Or how do you think about where all this is heading and where you would like it to ideally be?

Sure. AI Pods is kind of a way of delivering, which is absolutely different from before. And it's an AI-native service in which we deliver in a totally different manner from before. Now our forward-deployed engineers are there just trying to do the agentic transformation, the AI agentic transformation of our customers, helping them with processes with reinventing and rethinking marketing processes, human resource processes, account receivables, account payables, finance processes.

So there's a constant connection between how you create a future project with our deployed engineers and how ambitious is that project and how you deliver that. Both things must be extremely innovative. And this is what we're bringing to the market. First, the idea, how to make an agentic transformation of your business. And then when that is ready, we don't deliver in the traditional manner, but we deliver with AI-native services.

So long term, my ambition is that although our current business as we deliver today will keep on existing because many of our customers is the preferred way of engagement, this new way will start to slowly, number one, gaining market share, right, from other competitors; and number two, transforming the way we deliver our current services for our customers. So the ambitions are large. I prefer to refrain from giving you any number, but I have in mind like as a way of transforming our current business into something totally different.

And this gives you a place to think about many other things, like how to create those tokens that we will use in the AI models, how to distribute them, how to route them, how to -- I mean it's a pretty different game when you start thinking about charging per output or per consumption in the case of software development life cycle. But then when you are talking about an AI-powered operations, you may charge per streaming monitoring hour or ticket sold.

I mean there are hundreds of different delivery units that we may use on our AI Pods that our customers will be extremely tangible and not in the same way it used to be. So this technology is giving us an opportunity to change the whole business, and this is the aspiration we have. Now how fast we can do it will depend on our customers on how good our AI Pods work, so on and so forth, that is what Diego was describing. I don't know, Juan or...

Listen, we are seeing like many, many very interesting conversations progressing with all of our top customers, right, most of our top customers. And our top customers are really marquee customers, and they are leaders in the space and where they are. And without exception, they are either in the piloting phase or scaling phase and those who are about to start are assessing the technology. But the interest we are seeing in the top customers is very strong. There's no structural friction with the clients whatsoever in the model. I think it's just a matter of our clients understanding the technology and progressing the processes and so on and so forth.

That's helpful. And then just as a quick follow-up on the commentary about the forward-deployed engineer. How much of that based on your earlier comments, is what I would call just a rebranding of the way that work used to be done in certain instances? Or how much of that is potentially structurally different that you guys might have to do, meaning does a forward-deployed engineer have to be on-site to a larger extent? Does it change some of the economics? How does that impact you guys given that you guys have optimized for mostly delivery offshore?

I think it's actually -- it's an interesting question. So I'll tackle that in 2 different stages. First, the formation. I mean, what does it mean and what's the delta between a very good engineer and a forward-deployed engineer. First of all, is the platform and knowledge of the platform. Any forward-deployed engineer deploys a platform and has to have profound knowledge of that platform. The second one has to do with the work that most of enterprise architects used to do, and that's the keeper, which is understanding the architecture components, data, security, et cetera, of the target client and what's the best integration strategy.

The third one is a little bit of building on top of that with regards to building the solution. So that's the enablement of the forward-deployed engineer, then it comes to solutioning. And the deployment is actually functional to that solution. So it's also important that, that person understand the problem is trying to address. So there's a conversion and reskilling that while conserving a lot of the learnings of that type of engineer, you need to build something on top of that. So we needed a retraining of most of our top engineers to make them forward-deployed engineers.

And do they have to do more work on-site or -- because on-site are very different than offshore.

Yes, second part of the question. Yes, we can actually execute a lot, typically what's called the discovery. It's a lot better when it happens on-site because a lot of the things have to do with interviewing people that are related not only with the platforms, but also with the areas and the processes you need to convert. So typically, if you do it on-site, it's a lot better, still can be done offshore, and we have done it.

So with that in mind, that's the last question we have time for, unfortunately. 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.

Good afternoon, and welcome to Globant's Fourth Quarter 2025 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions]. 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, 6 Juan Urthiague, followed by a Q&A where they will be joined by our Chief Revenue Officer, Fernando Maskin. 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.

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 over 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 it's 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 controller roads, 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 Pods software creates and evolves technology. AI agent workflows supervised by Globant experts produce working software artifacts on a token subscription model. AI Pods ops 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 product, real orchestration infrastructure, 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 pod's 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 pod's 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 Employee Bridge and Apollo-backed portfolio company, driving AI-led transformation through our AI Pods subscription model. After a successful pilot phase, Employee Bridge 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 move to 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 cycle 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 La Liga 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 La Liga 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 apps 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, 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 intelligence 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 tourist to develop the foundations of the world's first universal agentic protocol for tourism. AWS, Salesforce, Amadeus, Red Sea Global and Riad 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 Chitos and Doritos simply naked 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 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 Agent Force, 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 La Liga 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 globin 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 two 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 entered 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. Thank you for your continued support.

[Operator Instructions] So with that in mind, we'll take the first question from the line of Bryan Bergin from TD Cowen.

So two questions. I'll ask them 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 pipeline 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. 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 AI pods, plus some improvement in the overall market. The midpoint is a most likely scenario as usual, where we see basically more or less more of the same. I mean no big changes in the macro, no changes, no big changes on the business overall. And that's how we built the guidance for the year in terms of revenues. As for the second part, I will let Martin.

Yes. What we are seeing in our 7 out of our 10 top customers, we're seeing that people are loving it. And when I say loving it is that people are really looking to change the model from ours or other types of engagement into these kind of output model in which, of course, we charge the tokens but always there's a business result attached to those things.

So what is happening is that sometimes we're transitioning that work from our kind of engagement to this new kind of engagement. In some of our customers, there are some small pilots that are starting to happen. In some others, we're going now from pilots into scale without any kind of ask in the middle because the results are really amazing, as I laid out on the examples I provided.

So that is kind of changing the whole dynamic around the future of the company, right? Now we are able to not just scale our teams with new people, but now we can also be connected to everything that is happening on the AI space in a direct way. There's a new market that we are creating, which is called the AI-native technology services companies. And those AI-native technology services companies must find a way to deliver their services, having agents that repeat certain processes that ensure that what is produced is enterprise class with the right security, with the right kind of characteristics for what they need to be produced. And then humans supervising those assets that are being created.

And that transition has been -- 12 months ago, indeed, 9 months ago, this product didn't exist. And now we are in a situation that we have in 2025, more than $20 million in ARR and now we are scaling big customers, like the one I mentioned, like FIFA, like Santander, like La Liga, like Employer Bridge and many others.

So I feel that change is very healthy. It positions us in a different place. And of course, everything is mounted on top of what we already have, more than 800 relationships with top-notch corporations, 28,000 people that are ready to supervise all kind of products that we can produce those patients the right technology platform to be able to deliver those services and a commercial model, which is absolutely different from anything that we have seen before. And the best thing is not just a prediction, but also a real business. So we're extremely happy with that. I don't know if that answers your question.

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 and 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?

I'm absolutely happy with exchange in 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.

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 airports as well.

Thank you, Bryan. 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. So Latin America, as you remember, at the beginning of '25, we faced some issues and the region for a few quarters was showing negative growth. But then towards the second half of the year, we started to recover, and we actually ended up in a very healthy manner, being Latin America, the fastest region for the quarter. They are different, as you pointed out, there are different situations in different countries, Argentina and Chile which are two of our main operations are doing very well.

Brazil, it's okay. We are basically performing in line with our expectations. And now, of course, we need to see what's going to happen in Mexico is a little bit of an unknown at this point. But the main countries are performing well. I think that the recovery that we achieved in the second part of the year when we look at which are the customers driving that, most of them are in Argentina. So we don't see -- we are not -- we don't see any headwind coming 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 will 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 the slower than we would like to in terms of closing and ramping up. But leveraging the amazing quarter we had in -- the amazing quarter, we had 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 the clients are cautious are taking time to make a decision 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 100 square are performing very, very well, where the vast majority of the bookings are coming from, as Martin said, 73% in Q4. So I'm pretty confident that this combination will allow us to move forward in a very confident way.

Thank you, Maggie. 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 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 like increased urgency among your clients to embrace Agentic AI given like all the news flow over the last 1 or 2 months?

Yes. In the last few months, what we have seen is that companies are moving into action in that space. The avenues are, how can I accelerate my [indiscernible]. How can I replace some not very deep Software-as-a-Service solutions. How can I automate my processes using AI. How can I replace workflows of Agentic AI processes that I had before, of course, they must be supervised by humans.

And I believe those 3 avenues and the fourth avenue is that how can I improve my customer experience that research really bumpy when I read it about the idea of consumer happiness, yes, consumer happiness about how interfaces and experiences are evolving is falling in the last 4 years in a row. So there's a big technical debt of $1.5 trillion to $2 trillion, but also there's a big consumer experience that.

So another avenue of demand is saying, okay, how can I update all these interfaces to the next generation of interfaces. So all these avenues are creating like a lot of demand for AI, I believe that the way to deliver those next-generation services, those AI native services must be absolutely different from what we did in the past. And imagine that we have each of these AI Pods, Puneet, unit are like a recipe or like a set of instructions like a process that we have been refining for years and years.

It has different steps to create enterprise-ready, security-ready types of solutions and what we are producing using those tools is really much more scalable than before and really much faster than before. So customers are seeing that now. If you just throw AI tools to people, you don't get those results. And that's why it's so important to stress the point that this new industry is the way to create the savings that you are expecting or if you don't want savings, is the way to create the productivity that you're expecting from these AI teams.

So that's why I believe that the AI Pods are really catching up. It's a pretty simple way of understanding how to make those savings real as opposed to just keep on throwing licenses of AI tools to people to use them. I'm not really sure that they will use them in the correct way. And again, it's much more different to orchestrate and to supervise a set of agents producing software and that's real productivity and just throwing AI tools to people. It's an order of magnitude of difference between the two things. And this is exactly what we are doing in our AI pots. So yes, I'm seeing momentum, and that will keep on growing. That will keep on growing.

Okay. And then all the spending on AI, whether it's for core modernization, consumer experience, AI Pods. Do you think like it will represent like incremental spending on IT services? Or will this those budgets will stem from cutting elsewhere other parts of discretionary spend?

No. Look, I mean I think humanity will create 100x more software than before. And that is only expansionary for us. So I don't see that this will -- well, now we are happy with this small increment on the productivity and the small increment on the functionality of our product. You hear and you listen companies delivering much faster functionality than before live. I read many examples during the last few weeks.

So I believe that this is something that we will only keep on growing and the more you can do, the more you consume, and that's a historical trend, right, in every single -- so if we can produce more software faster, we will use more software and we will expect more functionality and we will expect more customers to be happy. So it's not a trend.

I mean, sometimes what I see analysts and when I see reports, I'm going to read to report, I see that there's a kind of a limited amount of scope, and what I'm trying to -- the message I'm trying to convey to you is that there's no limit amount -- there's no limited amount of scope. Just the technical depth is another industry of our size, just the technical depth, right? If you add on top of that, the consumer experience debt, all the new -- there's no way that it will be the same amount of software as before. It will be 100x more software. So that will be translated into better solutions with more platforms, with more AI Pods, with a stronger pipeline. Well, all these things are building up.

In my speech, what I said is 4 years, we have received -- sorry, for almost 2 or 3 years now, the vast maturity of the investments has gone into AI infrastructure that don't necessary translate into demand on the professional service space. Before that same investment, were going into better cloud that was yielding better software as a service, more implementation services, but that cycle now needs to come back. And that's why I made the point on the technical depth, on this consumer experience that because at some point, those things needs to catch up. Otherwise, the Consumer Experience Index will keep on going down for years and years and years, and doesn't make any sense.

In the moment, we can have the better and the best experience for our customers, we're having a decline in customer satisfaction for interactions with companies. How can we explain that? So one way or another, companies has been distracted investing in AI, throwing AI to people now is the time to make it -- to get it serious.

Thank you, Puneet. 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 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 suffer 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 on the revenue last year, we bottom on that revenue, and we expect to come back to growth in -- by the year-over-year by the half of this year.

So the exit rate will come back to 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 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 know if you now this one or Juan may...

As Martin is referring to, the first quarter compared to the first quarter of last year. So the beginning of this year is definitely better than the prior year, but the cadence of the quarter last year is somehow impacting the growth rates for 2026. When you look at 2026 exit rates, they are more like mid-single digit. And if we keep on compounding, that should put us in a better place for '27.

Now of course, there has been an industry situation. I mean if you look at the vast majority of the players, they are all between 3%, 4%, 5%. So there has been less growth in the sector after massive investments in COVID times and around that time. There is a little bit of giving -- going past that period of massive investments, but the needs are there. The pipeline shows that customers have been accumulating debt technical debt, and that needs to start converting at some point. Of course, [indiscernible] macro, a solid U.S. economy should help eventually.

I think that we are coming out of 2 years of a lot of uncertainty globally and that has not helped. But all in all, in summary, I think that the fourth quarter shows a bottom in terms of year-over-year numbers. Q1 already shows a better performance relative to Q4, and the expectation is for that to continue throughout the year.

Yes. My quick follow-up one is what do we -- how do we model out head count growth and revenue per head for this year? And does that model change at all as we get more embraced with more of the AI Pods?

Definitely, yes. We are seeing that we can do slightly higher numbers. We can continue to grow our revenue per share with the same or even less head count. The AI bot model by definition requires less people. It's the AI Pods, which are agent supervised by some few people. So there less need for talent. So I think that not just for loan, but in general, the sector will start to change a little bit that trajectory of head count 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 airports relative to the rest of the business increases, that should be a positive for revenue per head and also for margins. .

Thank you, Bryan. The next question comes from the line of Arvin 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.

I was wondering if you could maybe address -- on the AI Pods business, the path to get to the upper end of the range on the $100 million in a run rate ARR in that business. What is required for you to get there? Do you -- how many more bookings do you need to put in, how much is supported by your existing pipeline of AI Pods business? And I guess maybe you just kind of talk about the broad outlook on your confidence of kind of getting to the high end of that range.

Great question. Thank you, Jim. The higher part of that range could be achieved with not many big customers moving into that model. But let's see. That's why we are always being cautious here. We are extremely excited about the progress of that. Now we are seeing engagements of $20 million, $18 million, $15 million being transitioned into this kind of engagement, which is extremely encouraging for us.

So we expect to achieve those numbers. But I don't want to be -- I mean, it's the first time we are guiding them. I don't expect to guide those numbers every quarter either, but I'm trying to be moderate here. So -- but I'm quite optimistic about the possibilities of reaching to that top line -- top guidance that we did at the end of 2026.

If I can add to Martin. The behavior of the pipeline when it comes to AI pods is very encouraging. We've seen a positive trend and a very accelerated growth. So -- and on top of that, the openness of our top customers to start piloting, right, and to start scaling up when you review the list of clients are starting to ramp up in this new technology, it's really encouraging. So we are very confident and we trust that we are going to be very close to the range that we guided in terms of 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. So I mean, yes, we have been impacted by the U.S. dollar weakness. If you look at Colombian peso, Mexican peso, Chilean peso, Brazilian real, most of the currencies where we operate in Latin America have had significant appreciations throughout 2025 and that is what impacted the first -- sorry, the last quarter of last year and what is also impacting the beginning of this year.

I think that the dollar is getting to a point where it's on an average, it's kind of on a very low place relative to historical terms. So there has to be a little bit coming from there. But also more importantly, I think that we need to keep on focusing on not just looking at what's happening with the currencies, but moving the business towards AI Pods because that's where productivity increases that where margins become higher and the more we operate on those models, the more efficient, we can run them.

So I think that pricing will be okay. I mean it's not going to be a massive growth this year in terms of pricing for the general business. But definitely, there is an opportunity to increase our share of AI Pods and hence maintain or improve our gross margins as we scale that business.

Thank you, Jim. 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 time lines 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 deal conversations. And 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 that 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 this year, 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 in 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 two 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.

Thank you very much. The next question comes from the line of Sean Kennedy from Mizuho.

Congrats 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 their procurement teams becoming more comfortable with the AI Pods business model versus legacy?

That's a great question, Sean, thank you. This is [indiscernible] of the most challenging things. However, as the thing gains -- as the idea gains momentum in the industry on the analyst side, on you guys, the procurement teams are getting more relaxed. And also, I believe that the fact that we are talking something that is extremely solid and it's, I would say, an order of magnitude more transparent than the traditional model, procurement love it.

So whenever you can tie any asset that is being produced to the amount of tokens and understand that, that correlation is what you're paying is much better than saying we consume this amount of hours to do whatever. So I think the AI Pods offering is extremely solid. Of course, a long road on convincing more people about this. The more you help us, the more we can do it. So we appreciate any kind of explanation on your reports.

And analysts from Forrester, from IDC, from McKinsey, from Bain, they're already explaining this way of working. And 70% of the people, as I read in a report the other day, 70% of the people that are buying technology are expecting a change in the way the engagements happen. And the answer to that change is either a monthly subscription, an amount of tokens or some kind of combination there, but it must be on that cycle. So procurement teams are responding quite well to that.

Having said that, of course, it's always complicated, but it's not impossible. And the business is pushing very hard for that.

And there's also when we started this, we tied the AA parts with the capacity that it was equivalent to Timoftamount of people, right? And procurement is used to that ensure -- and we become much more mature nowadays. And we are actually talking in correlating the consumption and the subscription with outcome to a certain provide full transparency as well. So there's also -- we've been getting a lot more mature in describing and showcasing how an AI bot performed and data has also relaxed a lot of the procurement teams. .

Got it. And then as my follow-up. I think you stated at the high end of the guide embeds that the current conversion levels that you're seeing are consistent. So I was just wondering how it's been trending over the last few months.

For AI Pods or in general?

Excuse me.

You're talking about AI Pods or in general?

No, no, just in general, in total. .

Look, they are -- I mean, we build the guidance a couple of weeks ago. And so far, the conversion rates that we are seeing some of the big deals that we closed last year that are ramping up. They make us comfortable to be at the midpoint of what we guided. The pipeline that we have plus the expectation of some improvement throughout the year somehow can take us to the upper end. But definitely, with the current level of -- or the current conversion rates, plus we have already done during Q4 and the beginning of this year, that will take us -- should take us to the midpoint of our guidance. But again, that doesn't -- the midpoint doesn't include any material improvement or material change on the overall environment. .

Thank you, Sean. The next question comes from the line of Arvin Ramani from Trust Securities.

Good set of results. I'll set of questions on AI. So I'll kind of hop on to the trend. I mean, AI Pods generated about, I think you said $21 million in ARR this quarter, very impressive given it's still early. But still, it's less than like 1% of your overall revenue is still pretty small. But when you look at this model, it's basically designed to do more work with tokens and less with humans. And as this AI Pods scale, how do you prevent them from cannibalizing your core seed-based revenue?

And then secondly, what is the internal modeling saying about the revenue crossover point when you're doing -- you're generating more from like token-based revenue versus head count based revenue?

I'm not in a position to prevent cannibalization. So I want that transformation to happen. And that puts us in the right side. And that means that as AI grows, we will keep on growing. And the way we are delivering our services with these AI Pods is by far very scalable. It kind of the style years and years of experience and the configuration [indiscernible] we are using for each of those AI Pods and how the agents must run the process is really very, very impressive to see how those small recipes to achieve the assets that our customers have are really changing the way we are using AI and the current models that we have, because we are baking into those configuration files, all the experience that we have in the company.

So this is the north for us on how to deliver technology and solutions moving forward. And of course, there will be customers that are comfortable with the hours and our current business we have with them and so on and so forth. And I'm extremely happy to keep on doing that. But we are extremely encouraging our customers to move to this new model because we believe on the benefits for transparency, for productivity, for the long-term relationship we have with them.

And not necessary AI Pods are cheaper, they are more productive. So we see a transition year in which we were going to be transitioning from one kind of business to the other type of business. So it will be like a rational migration rather than anything else. So I don't know if that answered your question.

For the second part, as we migrate the business to AI Pods and AI Pods start to gain share, hopefully, by the end of the year with the current forecast that we have in our internal projections, the numbers that Martin mentioned in terms of ARR for the end of the year. So definitely, we went from 0 to $20 million run rate in just 2 quarters. The model has been under a lot of evolution, a lot of testing with customers, a lot of internal work on making sure that it is -- it creates a differentiation for [indiscernible] that makes us stronger relative to other players or other models that may be out there.

And now it is starting to accelerate. As we discussed before, when we look at which are the customers that are now getting on board, which is the size of some of the deals. Now it's not just the -- let's try with a small thing here, but some customers are actually talking about $10 million, $15 million, $20 million being migrated to the new model. So I think that we are starting to get that acceleration after a couple of quarters of understanding the customer and getting feedback.

We just launched this in Q3 last year. So it's only a few quarters that [indiscernible] around. It's already creating interesting revenues, creating a lot of momentum with customers. I would say that by the end of the year, will be more relevant relative to overall pie. But definitely, it will be next year when the curves start to get closer.

Yes. And also for your models and for everything that you are covering us, I think that we must acknowledge here that the industry is shifting and that this new industry of our AI native services is going to be, in essence, different from what it used to be. And AI native services is leveraged on, of course, on knowledge, but also on repeatable processes and things that we have never had before. So in the same way, Amazon created the cloud computing industry when they launched Amazon Web Services. Of course, at our scale, I don't want to be comparing with Amazon, but our scale, we are kind of executing this vision of AI native technology solutions. .

And the way to model that and the way to do that is absolutely different from what it used to be. That's why I started talking about ARR because it's kind of a recurring revenue that is not coupled to the amount of people. Right now, we are using people to supervise what the agents are producing. Every kind of asset has a certain amount of time for those things to be supervised, so we can calculate how much people we need for that. But what we believe is that the revenue has nothing to do with the amount of people that we are putting there.

The revenue has to do with the amount of assets that we are creating and how enterprise-ready those assets are, right? You can use [ Code X ] but you won't get all the discipline and the rigorous approach that enterprise software needs. So what we are creating here our process is to create assets that are enterprise-ready, security-ready that they have the scalability and the repeatability and maintainability that you need to have moving forward.

So it's really a different way of understanding the industry itself. There's a $2 trillion industry that must change to a new model, and this is the very beginning of that.

Yes. That's inedible helpful. Just a quick follow-up here, you're going to -- just a quick follow-up. In terms of like the token side, the tokens cost your particular amount of money and then you're charging your customers. What are the margins you're making there higher or lower than the company?

As we reported, margins are between 45% to 60% depending on the AI Pods. And depending on the customer and depending on the things that we need to create. We expect that margin as we progress with time to increase as we get more efficient with technology and we get more efficient, supervising and the technology for supervision gets improved, too. So this is the kind of model we have in mind.

As we are able to supervise more assets with the same amount of people with less people or with better technology, we will need less supervision and we want to increase our margins. And that's a virtuous cycle that happens here. But not just that, every single conversation and every single token is being installed on our enterprise AI platform. And those tokens can be used to improve the processes and to retain corporate

Sovereignty of the processes of the company. So this is kind of an explosion of productivity and -- and it will reshape the whole industry and not just for software development, it will happen also for process operation.

Today, we have AI Pods called AI bot software, and we have another AI Pods operations. And also both of operations they get that kind of doing things for operating certain processes of companies, and we charge it also per consumption. So it's a radically different way of understanding how professional services and how services will be rendered moving forward. There's a lot of value to add for companies like Globant, and there's a lot of change of mindset that is needed to understand this new industry. I could be talking forever about these.

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.

Good afternoon, and welcome to Globant's Third Quarter 2025 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] 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 Financial Officer, Juan Urthiague; and our Chief Technology Officer, Diego Tartara. This will be followed by a Q&A section. 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.

Hello, everyone, and welcome back as Globant presents its earnings for Q3 2025. We appreciate your continued interest as we navigate the ever-evolving technology landscape. Our commitment to innovation and reinvention remains at the core of who we are. The speed of change is only accelerating. This quarter, we are excited to share how we are not only adapting to market trends, but also proactively shaping the future of our industry.

Our focus on sustainable growth and delivering exceptional value continues to drive our efforts as we look ahead. Our business fundamentals remain strong, and we continue to perform by putting innovation first. Our AI Studios bring together our talent to provide a new kind of AI-based solutions specific for each industry. They transform how consumers interact with brands and how our clients run their businesses. Our AI bots are our next-generation offering designed to deliver agentic AI-based services that scale faster, operate more transparently and focus on measurable outcomes.

They combine the speed and autonomy of AI with the creativity and oversight of our experts enabling customers to access continuous outcome-driven transformation at scale. All our agentic AI-based solutions from our industry-specific AI Studios to our AI Pods are orchestrated through Globant Enterprise AI, our central intelligence platform that acts as the golden path for enterprise-wide AI adoption and impact.

Delivered through a transparent consumption-based model, it transformed AI from isolated experiments into predictable, scalable and measurable source of enterprise value. Together, these elements form the backbone of Globant's growth to provide value for our customers and shareholder returns. During Q3, we generated $617.1 million in revenue, $2 million above our most recent guidance. We also launched a share buyback program, reflecting how bullish we are on our long-term prospects.

The pipeline has hit another all-time high currently at $3.7 billion, representing 30% year-over-year growth. It marks the solid demand we see for our services, and it grew this quarter despite very strong bookings. AI continues to emerge as the world's dominant technology with an expected market of $4.8 trillion by 2033. It will have made a 25x increase in 1 decade. Over the past few months, we have seen a healthy dose of realism in the AI space.

There has been a shift beyond hype towards tangible and effective adoption. We see a tremendous potential in AI transformation today. While Software-as-a-Service has played a crucial role in corporate technology by providing efficient and scalable solutions, our new AI Pod subscription model represents a significant evolution in how organizations can leverage technology. With our AI Pods, we empower leaders to develop tailored solutions that effectively address their unique and ever-changing needs.

Our AI Studios and Core studios are having these conversations with our clients to provide clarity in AI transformation, build versus buy and cost optimizations that are top of mind for corporate leaders today. Since doubling down on our 100-squared strategy this year, we have seen the execution being shown in bookings and revenue. Our top 5 clients grew sequentially by 2.1%, exceeding the company's average growth over this period.

The share of clients we have identified as 100-squared potential as part of our total bookings is currently 56.7%, up from 50% last year. Today, we have over 1,000 engagements related to Gen AI, Core AI or data currently running, representing 1/3 of our overall projects. We have over 900 projects related to AI readiness in our pipeline.

The new offering of AI Pods a departure from traditional consulting engagement models has nearly doubled in its share of our pipeline. This growth significantly outpaced the overall pipeline expansion. Clients access these solutions via the Globant Enterprise AI platform, which serves as a multipurpose Hub.

First, as an AI Hub connecting seamlessly with more than 140 LLMs, clients can interact with the LLMs that is best for their needs without being locked into a single provider. Second, it is a corporate Hub that connects with all major corporate information systems and data lakes like SAP, Salesforce, Databricks and many others. And third, an agent Hub that allow clients to create Agentic workflows to automate corporate processes.

Globant Enterprise AI can be acquired on a subscription basis. This shift to our subscription revenue model is not just a theoretical goal. It is actively underway in our most valuable client base. Within our top 20 customers, a group that collectively represents close to 40% of our total revenue, we're currently embedding our subscription model with 17 of them in meaningful ways. This is a huge milestone, specifically considering we officially launched this methodology in June of this year.

We're encouraged to see how our clients are incorporating this new model. For example, at YPF, the largest shale oil operator in the world outside the United States, we're moving into full execution with 46 agents to optimize sourcing, inventory, contract and supplier management, bringing clarity and efficiency to how the company interacts with its complex supply chain. As you know, Globant has a talent for applying AI to reinvent the human experience in entertainment, which is why we are particularly proud of our new engagement to bring Agentic process to La Liga, one of the world's top sports league.

Diego will expand on this later. A great example of our growing partnership is our work with Natura, the Brazilian multinational cosmetics company. This quarter, we announced that Globant will lead their S/4HANA migration, chosen for our ability to seamlessly integrate innovation and AI into SAP methodology, development and testing while enhancing traditional implementation efficiency. Together with SAP's Joule, our AI agents and platforms will accelerate delivery, reduce time to market and support the clean core strategy by anticipating deviations and suggesting real-time corrections.

Governed by our AI agents, this project brings a new vision from how technology can transform SAP implementations and drive business performance. This month, we also announced an important partnership with Riot Games. The company behind global esports phenomena, League of Legends and Valorant. Globant will support its advancement in artificial intelligence, new game development, esports experiences and software engineering capabilities.

Over the next several years, both companies will push the boundaries of technology to deliver richer, more personalized experiences for millions of players and fans globally. This partnership is one of the largest agreement in the history of our games business. We are proud to work with companies that continue to shape global esports culture and inspire millions of players. We're making decisions to unlock the full power in our core studios as well.

We recently announced that all of Globant's marketing and advertising efforts were consolidated under the GUT brand umbrella. Today, Globant and GUT bring a uniquely consistent and complete value proposition to the entire C-suite, empowering CTOs and CEOs to transform their business through technology while helping CMOs push creativity and marketing performance better than ever. Just as Amazon transformed the technology landscape by removing friction from how business access and scale computing infrastructure effectively, inventing the modern cloud industry, we aim to do the same for technology and professional services through our AI Pods and subscription model.

Traditional consulting engagements are filled with friction, lengthy planning cycles, detailed scope definition, change request and constant budget negotiations that slow down execution and dilute impact. Our AI Pods eliminate those barriers by combining Agentic AI with expert human oversight in a transparent token-based subscription model that focuses on outcomes rather than hours.

We defined supervised token capacity and continuous monitoring, execution becomes faster, auditable and adaptive, allowing our clients to focus on delivering value instead of managing project logistics. We are not just redefining consulting. We're leading a revolution in how business access technology and professional services. Thank you for joining us on this exciting journey.

Hello all. As we look at the third quarter, one thing has remained constant, the urgency for enterprises to deliver measurable results through AI. We have tirelessly enhanced our portfolio of services and products around that very premise to enable our clients to apply AI faster and effectively to unlock business value at scale. What we are doing with La Liga is a great example. The world's most successful football league is becoming the first global sports organization to adopt Agentic models to reinvent its business end-to-end from talent development, performance analysis, workflow automation to personalized content creation.

This quarter, we also expanded our footprint in immersive high-impact experiences. Through our strategic collaboration with Adobe and Red Sea Global, Saudi Arabia vertically integrated real estate developer, together, we're building a connected visitor experience platform from trip planning to arrival and stay. The platform unites content, data and AI agents to deliver personalized context-aware journeys at scale.

Globant Enterprise AI is at the core of our AI-centric solution and keeps delivering on our commitment to make it the best common gateway for clients to navigate the complex forest of AI. Less than a week after OpenAI launched the Agentic Commerce protocol in late September, we released a new version of Globant Enterprise AI, including ACP and enabling our clients to create AI agents capable of executing commercial transactions safely and intelligently.

Our partner ecosystem remains critical to scaling our AI vision. And as we see that our clients' biggest challenge is not the lack of technology, but the complexity of integrating it for real business outcomes or how to make their long-standing core systems agile intelligent and cloud native without disrupting the business. With Unity, the world's leading platform to create interactive experiences, we joined a service partner program combining Globant's global footprint with Unity's real-time 3D capabilities to power new immersive and interactive experiences in industries such as automotive, health care and manufacturing.

With AWS, we achieved the MSP partner program designation, recognizing our ability to deliver end-to-end cloud transformation and manage mission-critical operation at scale, a fundamental layer for AI adoption. While other provides basic cloud migration, Globant differentiates by focusing on cloud-native development and optimization. We leverage the full stack of AWS services from serverless computing to their Bedrock AI platform, to build resilient, scalable and cost-efficient solutions.

With Microsoft, we have been appointed as finalist of the 2025 Microsoft Media and Telco Partner of the Year Award. Globant was honored among more than 4,600 entries from more than 100 countries for demonstrating outstanding Microsoft cloud application services, devices and AI innovation during the past year. And by joining the IBM Quantum network, we are preparing our clients to embrace quantum computing and unlock the next computing paradigm, ensuring they remain ahead of the curve as the future of intelligent systems unfold.

GUT, now powered by Globant's global creative and marketing capabilities, keeps accelerating cross-selling and elevating leading brands, including AB InBev, P&G, Mercado Libre, [ Easting ], Kraft Heinz, Verizon and Havaianas. Also, Brazil's team created the first fully AI-generated campaign for Mercado Libre, Latin America's largest e-commerce platform in partnership with Samsung.

Additionally, the official Cannes Lions report was published, listing that as #9 global agency network at Cannes Lions 2025. Across sectors and geographies, our team continue to execute with passion and creativity. Our AI Pods are gaining traction. Our AI platform continues to improve and new industries are embracing our approach to reinvention. We believe the winners will be those who act decisively today, and we are positioning Globant to help them accelerate that journey as we continue shaping the future of enterprise transformation. Thank you very much.

Hello, and good afternoon, everyone. I am pleased to discuss our third quarter results. During this period, we increased our top line, expanded profitability and generated strong free cash flow, all while maintaining a prudent and healthy balance sheet. Our revenues reached $617.1 million, up 0.4% year-over-year and 0.5% sequentially, exceeding our previous guidance expectations. Excluding the positive impact of foreign currency, revenue was flat year-over-year. Turning to profitability. We closed Q3 with an adjusted gross profit margin of 38.1%, flat relative to our previous quarter despite significant FX headwinds coming from LatAm currencies.

Our adjusted operating margin reached 15.5%, an increase of 50 basis points sequentially. In addition, this quarter, we managed to dilute adjusted SG&A by 20 basis points sequentially. The effective tax rate for the quarter stood at 29.4%, increasing significantly due to the acceleration of the Argentine peso depreciation during the quarter, which resulted in higher taxes than anticipated. We were able to partially offset this impact with FX hedges. Despite the mentioned tax effect, we achieved an adjusted net income of $69.7 million with an 11.3% adjusted net profit margin, flat relative to our previous quarter.

Adjusted diluted EPS for the quarter was $1.53 based on 45.6 million average diluted shares in line with our guidance. Our balance sheet remains strong, ending this quarter with $167 million in cash and short-term investments or $205.3 million in net debt. We repaid $56.7 million of our debt during the quarter, reducing our total leverage. During the third quarter, we generated $67.5 million of free cash flow, achieving a free cash flow to adjusted net income ratio exceeding 96% -- this strong performance is consistent with our historical pattern, where free cash flow generation is much stronger in the second half of the year.

Lastly, as mentioned by Martin, authorized a $125 million share repurchase program, which reflects our belief in our long-term strategic position and our commitment to enhancing shareholder value. Now let's turn to our guidance. Demand trends across our client base have started to stabilize, though the macro environment remains fluid. For the fourth quarter of 2025, we expect revenue to be at least $605 million, reaffirming the implied guidance provided in our prior earnings call. This Q4 guidance implies a minus 5.8% year-over-year growth and includes a positive FX impact of 150 basis points.

We expect a non-IFRS adjusted operating margin to be at least 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 at least $1.53 per share, assuming an average of 45.2 million diluted shares outstanding during the fourth quarter. For the full year 2025, we now expect revenue to be at least $2.04474 billion, representing 1.3% year-over-year growth.

This expected growth includes a positive FX impact of 30 basis points. We now expect our non-IFRS adjusted operating margin to be at least 15% and the IFRS effective income tax rate is expected to be in the 23% to 25% range. Our full year non-IFRS adjusted diluted EPS is expected to be at least $6.12 per share, assuming a full year average of 45.2 million diluted shares outstanding.

To conclude, while much of the uncertainty persists, we are confident in our market position and ability to adapt. Our DNA is built on constant reinvention and industry-leading growth. Based on our operational discipline, we will continue investing in our AI studios, our subscription model and top-notch talent to deliver differentiated value to our customers. Thank you for your continued support, and we look forward to sharing more updates on our growth and achievements in the coming months.

Thank you, Juan, and hi, everybody. [Operator Instructions] we take the first question today from the line of JPMorgan. Puneet.

So I wanted to ask about AI use cases. Like are you seeing clients looking for AI use cases in Globant GUT area like AI-powered form factors for customers to do retailing or banking through new form factors?

Thank you, Puneet, for the question. You said new what?

So the new platforms, like the new way like in which consumers can buy stuff or do banking, like -- which is powered by AI.

Yes. I think the whole consumer experience is being transformed, and there's a lot of active projects that are going into the direction of changing that interface from a navigational interface towards a transactional or, I would say, a conversational interface. And in that direction, we have been doing several projects on those areas in many different customers. But it's not just connected to financial services. I would say that this kind of conversational interface is being seen in many different areas and in many different type of industries. I would love Diego to take it over.

Sure. So Puneet, here's an overview of how -- what we are seeing and how it's working. Many large companies, especially the ones that are heavily regulated, what they're doing is they're building their platform for AI transformation and development. But while doing that, they're already doing AI projects.

You mentioned, as an example, financial services. Fraud detection is one of the examples. Hyper customization for client management is another one. With regards to operation -- internal operation, portfolio management is being also handled by Agentic systems these days. So that is how it looks now. Even the most regulated sectors are jumping into AI, doing AI projects. There's -- I have to say that more than half of our projects are heavily related to AI these days. AI, sorry.

No, that makes sense. The reason I ask, it seems like there's a lot of demand -- the underlying demand for AI, but that's not reflecting in overall results. So do you think the clients are at a point that all those AI use cases and AI projects that they are ready to move them into mainstream or into production so that can overcome the weak macro or other headwinds that you faced. Basically, can -- should we expect much better growth rates next year based on the pipeline, based on what your clients are saying compared to current trends?

Yes. I mentioned in my part of the speech, I was saying, Puneet, that the pipeline grew to something that was 30% higher than in the same period last year. And about 900 projects are currently being inside that pipeline that are based on this kind of AI transformation projects. So I see a clear evolution from the beginning of the year in which projects were more exploratory and now there are more kind of transformational efforts going across the different parts of the company.

And this is not just on what we were talking before, which is consumer interaction, but also on how to run processes. And specifically on that case, we announced a case with YPF, but also the one with Riot Games with the one with Natura, which AI kind of takes a central role. And I think that this is something that will keep on evolving as we move forward.

Also, our AI part offering is also gaining a lot of momentum. It's kind of the pipeline more than double from what we had on the last quarter, just in 2.5 months that we launched the initiative. Bookings are also high. The number of customers got increased substantially, too. So we are seeing that AI is taking like a central role.

Of course, the digital transformation projects, the enterprise projects, like SAP migrations, now all of them are including this kind of AI initiatives inside of them. So it's difficult to split them, but it's very clear that digital technology is making an impact. And again, it's not that it's easy to implement one of these things and make it productive and make it into production for large corporations.

We're talking about probabilistic systems that needs to be managed in a slightly different way from the traditional systems, and that will require a lot of our help to our customers moving forward. And I see pretty much all the industries now growing as opposed to the last few quarters. All of the industries are moving forward in terms of revenue.

So that is helping. And as you have seen on the news, we have announced many deals with many different big companies and large deals in many different sectors. So I hope that will propel the revenue for 2026, and we will see good growth next year.

The next question comes from the line of TD Cowen. Bryan.

I was hoping if you could just help us connect the strong pipeline commentary with the operational headcount dynamics just sequentially. I understand you were going through a transition here. But can you give us a sense of just early 2026 client budgeting conversations? I think just trying to determine when a growth trough may form for you? And just any early commentary you're willing to share here on next year's top line potential?

Yes. I would take the pipeline thing. The pipeline, as I said, is much higher. The conversion speed as opposed to what we see in the first half of the year has also increased in the last few months. So that makes us happy. And I would say that we see a clear evolution towards the end of the year with all the deals we have. In terms of the headcount, I would like to take it to Juan to answer it.

Look, in terms of headcount, as you know, last quarter, we announced a business optimization plan to align our company, our headcount to the needs of the business, given the changes that we put in place in terms of industry studios, in terms of the subscription model and also looking at the level of growth. You have to keep in mind that we started the year with expectations of much higher growth.

Now all that is aligned. We are seeing flattish type of numbers for fourth quarter. And when we look into 2026, and we look at how the new AI studios -- the new AI industry studios are tractioning combined with the traction on the pipeline and also on our top customers with related to the subscription model, I think that puts us in a much better place to start thinking about 2026. The conversations with customers are ongoing. Everybody is finalizing budgets. When we look at all our internal numbers, initial numbers, we are seeing more growth in '26 than what we have now for the rest of the year in '25.

So we are optimistic. I think that the situation is improving. You start to close deals like the one we recently announced with Riot Games or the one or some other things that are being worked right now where they are growth oriented. And for us, that's always great news, right? When we start to see all the deals we are doing with YPF or with Mercado Libre, a lot of those deals are growth oriented.

And when that happens, we tend to do better, we tend to gain market share, and that puts us in a much more optimistic position relative to '26 than what we were before. And as you can see, we guided -- I mean, after a difficult year in terms of guidance and everything, this quarter, we were able to maintain the implied fourth quarter. We were able to raise a little bit the full year number based on the $2 million that we exceeded the number in Q3. So in general, we think it's a much better quarter, and we are optimistic about '26.

Okay. That's helpful. And maybe just one on the margin front. So obviously, that's a bigger focus for you going forward. Talk about the early efforts around efficiencies and how you're feeling about those efforts?

Yes. So this quarter, we had a good quarter in terms of operating income. It increased about 50 basis points sequentially during Q3. Together with accelerating growth, we have mentioned over the last two, three calls, and we continue to mention that there is a much bigger focus also on maintaining or improving margins, also on our free cash generation. It's a moment that until the level of growth becomes much higher, we need to pay attention at the same time to all those variables together, right?

And that's what we are doing. We will be executing on that. When you look at, for example, the CapEx levels going forward, they are going to be a little bit more aligned to the current levels of growth. So we are paying attention not just to the revenue or to the top line, but also to the gross margin, and you can look at the numbers. There has been a lot of peers taking margin significantly down. We have been very cautious on not doing that. If you look at our margin, gross margin was stable, operating margin improved. And when you look at the fourth quarter, operating margin is again above 15%. So we are trying to balance all the different things that are happening at the same time.

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

Just want to ask about the pricing environment in general. There's some concern just with Gen AI that there's pricing pressure through contracts and contract pricing as cost saves get passed on to clients. How do you guys think about the whole pricing environment through -- as Gen AI gets put into all these contracts? And what do you think about pricing as you head into next year?

Thank you, Bryan, for the question. We don't look at major pressure on the pricing environment. I believe that the deals that we are putting together has kind of a lot of value added, and that help us to position the pricing in the place we want. Indeed, the revenue per head is doing okay. So it's not changing or going down. So that's a good sign of us being able to maintain that pricing efficiently.

But the most important comment I would say is there's a very strong connection between what you offer and how much you can charge for that and which is the value that you're creating for your customer. And at Globant, we have always paid a lot of attention to that value creation and to that specialization. And now with our AI studios that are capable of delivering like a very substantial know-how for each of the industries in which we specialize plus our Core studios are bringing solutions that can go across pretty much all the industries and I think that value proposition is resonating quite well.

And if you add on top of that, we are accelerating the offering. And now we are discussing with 17 out of the 20 top customers, the next-generation model on how to engage with us, with our AI Pods and with the subscription model. And Enterprise AI, which is our platform, also is gaining a lot of traction as each time we sell an AI Pod, it has to do with our Enterprise AI platform. So I believe that this is being accepted and this is being like -- we are able to reflect that on the price that we put on proposals, hence, maintaining our margin and maintaining our revenue per head. I don't know, Juan or Diego, if you want to comment?

No, I think that you pretty much summarized it. If you think about the individuals, like on a profile basis and you tell me how does probably that price compare to what it used to be 4 years back, yes, there's pressure there. But the mindset today is about efficiency. The mindset is about business impact. And when you talk about that, and that's one of our main strategies with the AI studios. When you talk about that, conversation changed completely. So -- and that's why we've been able to maintain our revenue per head.

Got it. And then that's helpful. And then just, Juan, just thinking about the third quarter being roughly flat in revenue growth and then it drops to about 7% organic ex currency. Can you just help us to step down in revenue growth? What's causing that? And then I'm guessing this might be the trough in revenue growth in the fourth quarter? And then what does the first quarter look like sequentially?

On the -- talking about the fourth quarter, the main impact that we have over there are the furloughs in mostly in professional services. That's impacting pretty much -- that's explaining pretty much the decrease on a sequential basis. When we look at -- and I'll just give you some color on Q1. But when we look at the Q1 right now in all the numbers that we are seeing, -- we don't see any scenario similar to what we had in the last few years.

For example, 2025, Q1 was sequentially down 4.7%. We don't see anything similar to that at this point, anything at all. And that puts us in a much better place to get the year that gives us also some -- when we look at, okay, how the year is building up, how are the conversations with the customers, what each AI studio is bringing to the table, which are the -- we just signed a very large deal with a gaming company as we discussed. When we accumulate all that, the Q1 number is definitely a lot better than what we have seen in prior years, right? And I think that puts us in a much better place getting into 2026.

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

I wanted to put a finer point on the margin question, particularly as it relates to SG&A. Can you drive more SG&A dilution from here? And are you planning to? Or is this a reasonable level for SG&A to settle as a percentage of revenue?

We closed the quarter at 17.7%, almost 1 point below Q4 last year, for example. There is -- of course, there is always room to keep on diluting over time, but we also need to balance the growth that we expect to recover. We need to balance all the changes that we are making in terms of our offering, all the changes we are making about our business units with all the AI industry studios.

So there is more room. But I mean, as always, you need to keep looking at 10 to 20, even 30 basis points of dilution every year, not more than that. But definitely, as a business, this is a business that has the potential to run at about 15% SG&A over time, but it's something that you have to achieve as you scale, right? When you look at which are the companies that are running at those levels, those are the ones that are already at a very large scale. I think that 17.9%, 17.8.7%, it's a good number for the size that we have right now, given all the different things that we are doing these days, right? So I think that's how we see SG&A, Maggie.

That's helpful. And then it does sound like there's some momentum building across the business. I was wondering if you could comment on professional services, in particular, maybe if you back out the impact of the furloughs that you already commented on, do you feel like that vertical is showing signs of stabilizing?

Yes, definitely. I mean when you look at -- and I think when we are looking into Q1, for example, it's one area of recovery, right? I mean after the furloughs in Q4, we have started to see stabilization in one large customer that was impacting that group. Plus we are seeing growth in two or three others that will help us to offset what has happened to that customer that I mentioned before.

But even in that large customer, now it has stabilized in a new level. But we see opportunities to recover from this new level upwards. So we are -- I think on professional services, once we go through the furloughs, that's the bottom of that sector for us, and we should start to see better numbers going forward, starting in Q1.

The next question comes from the line of Goldman Sachs. Jim.

As Jim tries to get his line back, we will go on to the next participant. The next question comes from the line of Guggenheim, Jonathan.

Can you help unpack some of the vertical and geographic assumptions around that 4Q outlook and maybe the level of conservatism that you're assuming?

Yes. As mentioned, the one sector that will come down further down is professional services because of the furloughs that is going to be impacting that sector. And pretty much for almost all other sectors, we're going to see stable numbers. So I think that's something that, again, I think that after a few quarters of moving pieces, we are definitely seeing stabilization in the business with some green shoots that are putting us in a more positive way looking into '26.

Deals like some of the ones that we announced today have been on the cook for several months and you start to see them closing. Some of them and companies are again becoming more aggressive in terms of growth. And I think this is always a positive sign for Globant. Conversations are a much better place than where they were 6 months ago. So we are more confident about '26. And we think that, that's something that will be very positive for the business.

Yes. And also, I think it's quite clear how the difference in terms of conversion that we have seen in the -- at the very beginning of the year. I mean, at the very beginning of the year, everything kind of get frozen, right? And now the things start to move not at the speed we saw in 2021, but much faster than before.

And that is quite remarkable because -- and also the pipeline generation has been quite strong because we closed like large deals. And even closing those large deals, the pipeline grew a lot. So I think that dynamic is very different from what we have seen in the first half of the year. And that's the most remarkable part. That conversion coming back, our AI studios being able to articulate that value proposition much better. I think that evolution of Globant and that evolution of the market are two positive things to consider moving forward and into 2026.

Appreciate that color, guys. As you think about your confidence around 2026, what gives you incremental confidence that these client conversions or these pipeline conversion should continue into the middle of next year?

Well, we saw in the last few months, a lot of activity in the space. I would say, abnormal as opposed to 1 year ago or something like that. So I believe that this momentum will continue moving into Q4 and Q1 next year that would generate increasing opportunities and incremental opportunities. And as Juan said, we don't see something happening on the first quarter like happened in the first quarter of 2025. I mean first quarter of 2026 will be much more close to Q4 than it was before. So I think that, that's a positive sign of what we are seeing and how the momentum is coming.

Jonathan, I think that what we are seeing is mostly shared by the industry today. So I think that everybody has been more positive about the market, the overall market condition about 2026. So I think that we are -- after a few quarters of -- or a few quarters or even a few years, if you look at some of our peers of a very negative sentiment in terms of the market, in terms of the opportunities, I think that everybody is becoming a little bit more constructive, and we are on that same boat.

Yes. And everybody is realizing that creating these projects takes a lot of energy and takes a lot of knowledge and takes really deep knowledge on how to navigate the AI landscape that is exponentially growing and exponentially becoming more complex. So I think that discussion is coming to an end and people are starting to realize that, yes, they want to adopt AI.

They need someone to help them adopt AI. Hundreds of new projects that didn't exist before now are happening and are possible to happen. And then the traditional projects need to keep on going now accelerating with the new AI technology.

So the opportunity keeps on building, keeps on being very large for the whole industry. And I'm more convinced than ever that once we pass this kind of difficult situation during the first half of the year, the opportunities moving forward will multiply and expand our opportunities for 2026.

The next question comes from the line of Itaú, Maria Clara.

I just wanted to explore more about how you can balance employees and growth ahead. So even the current headcount and utilization levels, do you believe that you need to hire new people to honor a potential acceleration of growth in 2026? Or maybe your employees are becoming more productive with AI, so you are fine with your current headcount?

Yes. Thank you, Maria Clara. So there's going to be a combination of slightly higher utilization and hires. We're not going to be able to get back to higher levels of growth without incrementing a little bit our headcount going forward. We have made all the equalization or the balancing of the level that we need right now. But as we get into next year and as we start to see those deals materializing utilization, there is still room to go up because even though we increased 50 basis points, we're still below our target of 80%.

So there is some room there. But also we see that headcount is still part of the equation. Of course, AI increases productivity for our developers, but you also will see headcount growing as we get higher levels of growth going forward.

The next question comes from the line of UBS, Leonardo.

First of all, congrats on the huge leverage reduction, 20% quarter-on-quarter. I've been particularly critique about cash generation now you've proved me wrong. So congrats on the figure. My question is about AI. I think you mentioned something about the embedded solution in 17 -- embedded AI Pods in 17 out of the top 20 clients, right? You said they are embedded in a meaningful way. I would like you to discuss that a little bit so we can try to assess how could that eventually become revenue?

Leandro, let me first clarify what I said. I said inside 17 of the top 20 accounts, we are discussing about that. Not in all of them, we included already the AI Pods, but in some of them, yes. But the important thing is that those discussions are progressing quite healthy. And I think the acceptation in general of the model around a consumption model instead of different kind of metrics, while you have like variable scope and you need to have a methodology that don't punish you and is more transparent than other methodologies that you have in the past is the concept that has been extremely well accepted by our customers.

So what we foresee is that many new deals will come and are coming with that offering inside the proposal by default. So what we are seeing is a natural growth of the pipeline of this. The conversion of that is quite healthy it's almost doubling the pipeline, doubling the conversion and the amount of customers is almost doubled from the 18 that we announced last quarter into what we have now. So I believe that those are the variables to have in mind. I don't know if you want any specific explanation on how we are implementing those things, but please expand your question, if you want.

Guess, I didn't learn since 2020. No, it's quite clear on that. I think just if you could talk a little bit -- maybe this is difficult to predict, but maybe a little bit ahead 3, 5 years, how much of revenue could come from subscription model and if AI Pods will be the single driver of outcome-based out of time and materials? Or are you thinking on something else?

No. Look, I mean, I don't have like a prediction to share with you about how much of the revenue that will be. Yes, what I can tell you is that the model is progressing much faster than any other thing that we have proposed to our customers in the past in terms of next-generation proposals. So that's a clear sign that it will take over, I think, by storm next year, but I cannot predict a specific number.

I know you want to include it in the model, but the thing is I don't have a number to provide to you at this moment. It's just 2.5 months. But the things are the signals that we're receiving from the customers are very, I would say, positive.

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

So I was wondering if you could discuss what factors could raise conversion rates for the pipeline because as you noted, the growth there is robust. Is it just as simple as a better global economy? Or are there other factors like AI as in your customers are taking more time to think through their AI strategies before investing?

Yes. I think there are several factors that may help. Of course, as the global economy improves, it makes more sense for people to make more transformational projects. I know companies are -- I think that by the nature of understanding and going deeper into the benefits that any company can get from this new technology, I think companies are starting to understand that they need to move out from, I would say, trials into full programs.

And this always takes time. And in other massive technology shifts we have seen in the past, this took time. So we expect now to -- there will be needed some more time for the companies to agree that they need to go in the full transformation -- multiyear full transformation AI program for every single area. But the good news is that we are seeing that happening already, maybe not in 100% of the cases, but in many more cases than 6 months ago.

So that's a clear maturity of understanding how these projects must be developed that will help in the -- sorry, that will help on the conversion of these deals. And then if interest rates goes down, if the economy in the U.S., which is one of our main markets, has been quite stable if you take out the investments in AI. So I believe that this will come back to growth in some way as the whole economy improves, and that will help a lot, right?

But then on the internal side, on the Globant side, as we progress with our AI studios and as we progress with our offering, -- and as we progress with our value proposition of new ideas like the AI Pods and the enterprise AI and the subscription model, all those things will help customers say, okay, yes, let's do it. Enterprise AI is a perfect path for adoption of AI.

It will isolate you from any vendor dependence. You can connect with 140 LLMs on one side, on the other side with all the corporate information systems, then you can use those two things to create agents and to create workflow that automate processes, but also that transform how consumers interact with your brand. So as that value proposition gets stronger and deeper and goes deeper into our customers, I think conversion will accelerate, too. So there are multiple factors that are affecting in my perspective in the future. But I don't know, Juan or Diego.

No, I think just to add a little bit on top of what Martin said. I think there's something related to what you mentioned, Sean, that the market continues to be in a mood that is about efficiency and impact, right? And this is very important because what we see is, first of all, all the proposals that we send, they're being evaluated. And of course, they need to understand the impact that will have in the business.

And they're either a go or no. But I think with regards to the time it takes to evaluate proposals, close them up, which has certainly, there are larger period of times, lead times until closure. I think that it has a lot to do with the maturity, both of the market and the technology as well, evaluating a proposal, how to properly use new platforms, the proper models, the implementation, which is super complicated.

And you have three different offers that might be totally different and you're not even super mature with regards to that tends to take a lot more time. I think that will only improve in time. And hopefully, we will get back to the usual times of the industry.

Great. Good to hear. And then as a quick follow-up, I was wondering if you're seeing demand from helping companies, or companies prepare for AI in terms of data and cloud, like before the AI Pods implementation?

I think there was an interesting data point mentioned in the script. There is 900 projects or potential projects in the pipeline that are what we would call data readiness projects, which is either data, either generative AI, either AI Pods or a mix of the above.

So there is plenty of projects that are happening and plenty of projects that are in the pipeline that are AI related. We still see many companies that need to get prepared for making a better use of AI, right? And that's going to continue for a while. And you have some companies that are there, others that are getting there.

Sorry, but not all the projects are generative AI. I mean there's a lot of projects that is traditional AI, machine learning projects in which a massive amount of information is being involved and models are being trained or tuned or -- I mean, not all the projects are about conversational projects or interfaces.

There's a lot of AI projects that is the traditional AI projects, of course, get enhanced by the use of generative AI, but it's much more the traditional data gathering and then trying to train models based on that information to predict certain factors or certain things that you cannot do only by using a generic LLM, right?

So it gets accelerated by using LLMs, but it's traditional AI or fine-tuning or doing machine learning on specific industries, on specific sectors on specific areas of the company that are also fueling that pipeline and that amount of projects that Juan was mentioning.

Thank you for your question, Sean. Unfortunately, that's all the time we have for the Q&A section today. I will now...

Arturo, hold on a second. There was one that got missed on the line. I don't know if he's ready for the question. Jim?

Jim, are you there on the line? If not, we can move to one more question then. I'm sorry. Unfortunately, that's all the time that we have today. I don't see Jim there. But with that, we will conclude the call today. And I would like to turn over the line to Martin. Martin, please go ahead for some closing remarks.

Thank you very much, guys, for supporting us, for being here with us for another quarter of Globant and looking forward to see you on the next one.