HCL Technologies Limited (HCLTECH) Earnings Call Transcript & Summary

Ladies and gentlemen, good day, and welcome to HCL Technologies Q1 FY '27 Earnings Conference Call. [Operator Instructions]. Please note that this conference is being recorded. I now hand the conference over to Mr. Nitin Mohta, Head Investor Relations. Thank you, and over to you, sir.

Thank you, Darwin. Good morning, and good evening, everyone. A very warm welcome to HCL Tech's Quarter 1 FY '27 Earnings Conference Call. We have with us Mr. C. Vijay Kumar, CEO and Managing Director at HCL Tech; Mr. Shiv Walia, Chief Financial Officer, along with the broader leadership team to discuss the performance of the company during the quarter, followed by a Q&A. In the course of this call, certain statements that will be forward looking, which involve a number of risks, uncertainties, assumptions and other factors that could cause actual results to differ materially from those in such forward-looking statements. All forward-looking statements made herein are based upon information presently available to the management, and the company does not undertake to update any forward-looking statements that may be made in the course of this call. In this regard, please do review the safe harbor statements in the formal investor release document and all the factors that can cause a difference. Over to you, Sir.

Good evening, good afternoon and good morning, everyone. Thank you for joining our FY '27 Q1 earnings call. We began FY '27 with a focus to grow our advanced AI-led offerings increase our relevance to clients capitalize on the full range of AI-related market opportunities in a pursuit of becoming the world's best AI solutions provider. As mentioned previously, our intent is very clear. benefit disproportionately from the AA [ net ] and AA amplified opportunities, which together represent the fastest-growing pool of enterprise spend, while in AA disrupted services, we intend to innovate faster than the market to stay ahead of the deflationary core rather than be defined by it. The fusion of this is reflected in our growing advanced AA revenue. Advanced AA revenue for the quarter stood at $172 million, marking 10.3% Q-o-Q and 62.1% Y-o-Y growth. Let me dwell into the business performance for the quarter. AMG is typically a weaker quarter for us due to planned revenue declines driven by productivity commitments in large managed services contracts. Despite these seasonality, we delivered a good all-round performance. Our revenue declined by 0.5% sequentially and increased by 2.6% on a year-on-year basis in constant currency. Our operating margin stood at 16.9%, and an improvement of 39 basis points Q-o-Q, an increase of 56 basis points Y-o-Y. All growth rates referred to are in constant currency. Our services business grew 3.5% year-on-year and declined by 0.7% sequentially in constant currency. Our IT and business services grew 4.2% year-on-year and remained flat sequentially. Engineering and R&D Services grew 4.3% Y-o-Y and declined 3.7% sequentially. HCL Software annual recurring revenue is now at $1.063 billion, a 2% increase Y-o-Y in constant currency. Revenue grew 2.2% sequentially, while declining 5.3% year-on-year. We have completed the acquisition of JasperSoft, this adds the visualization layer to our data management portfolio. Just to recap, our data software product portfolio already covers the majority of the data value chains like data connects for data integration and quality, Ingress, HCL Informix, Zen and [indiscernible] for storage and data intelligence and observability for governance and AI analysts to engage and activate data. What was missing was the visualized layer, the capability that takes govern trusted data and delivers it as actionable insights to the business users who need it. From a bookings perspective, the quarter was good and the bookings was well balanced across verticals, service lines and geographies. Our net new TCV bookings for the quarter was $2.4 billion, highest ever Q1 bookings. This excludes the recent mega deal that we announced, which was signed in early July and not in Q1. Let me give a brief overview of this landmark win. We've been selected by a Europe headquartered Fortune Global 50 firm as a technology partner to accelerate AI transformation and management of their digital workplace and enterprise networks. We will leverage our AA force platform software-defined solutions and digital employee experience framework to implement an AI-first workplace and intelligent connectivity fabric, thus elevating employee experience and productivity for the company at a global scale. While there are several deals that added to this $2.4 billion, I want to talk about the marketing that shows the depth of value we deliver to our clients. Our Fortune 250 semiconductor equipment OEM selected HCL tech to accelerate AI drill transformation across its semiconductor engineering and manufacturing value stream. HCL Tech will deploy [ SAP ] enabled design to manufacture and integrate SAP with [indiscernible] and MES systems, establishing an enterprise backbone for a future-ready, scalable AI-led digital supply chain. On the people front, we have 223,889 people as of 30th June 2026, a decrease of 3,292 compared to the previous quarter. Our attrition stands at 12.7% on an LTM basis. Our AA strategy shows evident returns as seen in 3.3% year-over-year increase in revenue per employee which has gone up every quarter for the last 5 quarters. Coming to our AI update. As you know, our AI strategy is anchored on 5 strategic pillars designed to drive client impact accelerate innovation and strengthen our leadership position in the AA market. I'm pleased to share the progress we made across each of them this quarter. Our first pillar of strategy's proactive transformation of our services. We continue to embed deeply in our service delivery model, helping clients unlock measurable efficiency and accelerate business outcomes. A force is now deployed across 92 distinct client accounts, enabling organizations to relate to the benefits of AI within existing engagements at scale. A good example to the progress we are making in this area, a Europe-based global automotive manufacturers selected HCL Tech for a large-scale AI-led site reliability engineering transformation program across engineering, production, commercial and corporate application landscapes. Powered by AI Force, the program brings together SRE, AI Ops, Agentic AI, observability, automation and application life cycle transformation within a unified operating model. Coming to the second strategic pillar of building differentiated IP, differentiated IP remains a cornerstone of our AI strategy, enabling clients to move from experimentation to enterprise scale value realization. A force continued its evolution with 2.2 release, introducing capabilities such as [ VSCOdeIDE ] plug-in support multi-model AI, long-term memory, configurable governance broad rail, AWS native integration and enhanced observability. We also rolled out an agent store, an organization-wide validated set of AI assets, including agents, AF use cases, workflows, tools and connectors, and the next base enables reuse of AI assets across the organization. to innovate faster and better to develop more AI IP. We also launched AI Force with Oracle combining Oracle Fusion Agent Studio with HCL-Tech domain aligned agents accelerators and governance framework to accelerate enterprise adoption. In Industry Solutions, our intelligence regulatory platform solution achieved general availability while Visionx was named as the finalist at the AI awards U.K. in both the Best AI Product and AI Power Quality Assurance categories. We also launched 3 new industry AI solutions namely AI For Store Operations, product-to-cash platform. We now have 23 industry AI solutions. Our industry AI solution, VoiceOps AI designed for media platforms and entertainment vertical and telecom scale environments received the Product of the Year award at [indiscernible] in the intelligent technology category, recognizing its ability to transform voice-led service operations and customer engagement. Coming to the third pillar, expanding AI-led services. We continue to broaden our portfolio of AI-led services, helping clients address emerging opportunities. In AI Labs, we hit a major milestone in Q1, crossing 1,000-plus AI engagements delivered. Within AI factory, we announced a strategic collaboration with Red Hat to accelerate the deployment of enterprise-grade AI infrastructure through the AI factory ecosystem. A global technology major expanded its partnership with HCL Tech for an AI factory program with an incremental scope of over $180 million for AI data center build-out. HCL Tech Solutions will fast in the deployment of a large-scale infrastructure environment that leverages the latest GPU technologies to train large language models and advanced AI-driven products. In physical AI, a Europe-based manufacturers selected HCL Tech to engineer the navigation stack for its next-generation autonomous robots. HCL Tech will apply its pivotal AI and intelligent product engineering capabilities to deliver core navigation logic, motion planning and system integration for the product. In another deal, our AI engineering capabilities will translate chip specification into implementable silicon supporting the delivery of a secure hardware module that meets the stringent security standards for an Indian research organization. The selected [indiscernible] to support the development of a secure chip aligned to trusted computing requirements. This quarter, we also made a significant progress in building our sovereign AI as a service capabilities. Sovereign is not just government. It is for enterprises as well. Enterprises are realizing that there's been -- their know-how that gives them their competitive edge are their most valuable assets, and they don't want the value disappearing into some of those models. So the evolving enterprise AI architecture is based on 2 broad principles. One is Zero Trust. That is the default poster is that no data, no prompt or context ever leaves the enterprise boundary. And the second principle is a tiered approach where Tier 1 is private on-prem or VPC posted SLM fine-tuned on the enterprise data and Tier 2 is frontier models access through policy enforcing inferencing gateway that handles reduction, logging and cost economics. The gateway becomes the primary policy enforcement point which sits within the enterprise. So the demand is moving towards solutions that can enable clients to have complete sovereign assurance with custom models and enters rather than just renting the models from the big providers. Now coming to the fourth leg of our strategy, scaling a partnerships across the technology stack. Our partner ecosystem remains a powerful force multiplier, accelerating innovation and helping us deliver best-in-class AI solutions. Most notable is a recent strategic investment of $150 million in Shagun, India's full-stack sovereign AI company. This reinforces HCL Tech's position as an AI innovator, not just an adaptive, underscoring our commitment to building co-innovating and shaping the next wave of AI. By combining [indiscernible] search depth in multilingual India-focused AA models with HCL Tech's global enterprise [ relationships ], engineering expertise and software IP, we are creating a differentiated full-stack AI platform for governments and enterprises, spanning models, platforms, applications and managed services. This meaningfully opens up the Indian sovereign A market for us across industries and the government sector. This is clearly an early-stage market opportunity to build industry and bin-specific plans. While the world's attention has been captured by ever larger general purpose models, the real value for enterprise [indiscernible] in smaller, specialized models trained deeply on the language data and workflow of a single industry or a client. These models are faster, more cost efficient and more accurate where it matters, and the window to establish leadership here is open now. This quarter, we made significant progress with other partners mentioning a few, we expanded our strategic relationship with Google Cloud through the creation of a dedicated Gemini Enterprise business unit and launch of an autonomous finance platform that transforms core finance and accounting operations using Gemini Enterprise. We inaugurated AI Innovation Zone with Google Cloud and Intel at Santa Clara and Chennai, respectively, providing clients with immersive environments to explore, build and scale AI solutions. HCL Tech was added to OpenAI's Trusted Access for Cyber program, providing authorized teams access to advanced cyber-focused AI capabilities. In AWS, we achieved AI services competency, marking a significant milestone in our AI journey with AWS ecosystem. We also strengthened our modernization proposition by integrating HCL Tech composable agents into AWS transform Agent AI service, accelerating the transformation for mainframe modernization and VMware migration. Our ecosystem momentum was further recognized through prestigious industry awards, including Dell Technologies 2026, Global Alliance Americas Partner of the Year, HPE Storage Partner of the Year 2026 and more. Lastly, we expanded our partnership with MetLife Stadium, the venue for FIFA 2026 World Cup Final, the New York Jets and New York Giants as their official partner. We will leverage our AI capabilities to create intelligent scalable solutions that enhance customer experiences and support smarter, safer and more connected environments for the clients. On the fifth pillar of developing AI talent at scale, Tavern foundation remains critical to sustaining long-term growth and client success. In Q1, around 24,000 unique employees across the organization participated in AI and in AI learning journeys tailored to different proficiency levels and rose. These roles are primarily categories users, super users and AI builders. In parallel, focused capability-building initiatives are being pursued in areas such as physical AI, SLM builders role, partner platforms and hyperscaler technologies. Additionally, 200-plus employees were Black Belt certified during the quarter and are actively contributing to solutioning ideation into end realization of AI use cases. The examples include transformation of global IT operations for a client's global IT through an AI-led hyperautomation ecosystem by pioneering Agentic AI, AIOps and intelligent incident management capabilities across a complex global infrastructure landscape. In another case, we enable the client to move from fragmented G&A pilots to an enterprise scale automation strategy, delivering 40% productivity improvement while embedding AI into the core service delivery and commercial operating model. Our AI strategy continues to be recognized well by leading analysts, industry bodies and technology partners. While we have several recognitions this quarter, as detailed in our investor release, the one that stands out is HCL Tech was named as a market shaper in Gartner's inaugural physical AA services assessment becoming the only India heritage services company positioned in the top quadrant. Taken together, these demonstrate our continued strength of our AI strategy, the momentum of our innovation engine and the trust clients place in us as they transform their businesses for an AI-first future. I would also like to share an important strategic initiative for HCL, where we are entering the AI data center business. Global data center demand is set to triple by 2030 with AI driving roughly 70% of that growth. And in India, that growth is expected to happen at an even faster pace. India, given its scale is one of the most supply-constrained data center markets globally, and sovereign data requirements are increasingly mandating that workloads for government enterprises and even global consumer platforms will be delivered in country. The convergence of ALD demand, supply constraints and sovereignty needs represent a very compelling opportunity. This is a business which is shifting from physical infrastructure to higher-value AI-ready solutions, one we believe will be a new growth vector for HCL Tech. We create -- we will create full stack offerings by combining our capabilities across AI data center design, DevOps and cloud operations as well as our software portfolio with our new data center business. The biggest opportunity is not to rent AI, but on the full stack. The data centers that compute, the models built to address client-specific needs. As demand growth and supply catches up, the players who win will be will offer full stack offerings. In this regard, we will make a strategic investment of up to INR 3,500 crores and with the potential scale to 50-megawatt of capacity. This would also position us as a key enabler of India's sovereign AI ecosystem, expanding our presence in the fastest-growing market among largest economies with differentiated offerings around sovereign cloud, secure AI and managed Air infrastructure. We are in advanced discussions with clients to ensure we start with certain level of committed consumption from day 1. We would also like to highlight that we will consume some of the capacity internally as we build them into our managed services and outcome-based contracts for our global clients. Before I talk about the pipeline and market trends, I would like to take a moment to highlight our executive track record on mega deals. Over the last several years, you would notice, there are areas where we are undisputed leaders and where we command the execution premium, especially in mega deals. We also have a strong track record of executing mega deals with excellent client satisfaction and to the planned business case. This is also reflected in our renewals of our highest client categories. This is an important angle where we see large deals as a growth vector and our risk management framework and execution rigor ensures we don't compromise on margins. Our strategy continues to be to deliver superior growth at stable margins. As you would see, our margins have been stable over the years, including FY '26 with the exclusion of restructuring costs. Coming to pipeline and market trends, our pipeline remains healthy. Looking at the broader market trends, we are seeing a clear divergence across different segments of the AI landscape. On one side, we are seeing strong sustained growth both in AI native and AI amplified services. On the other side, AI disrupted services, the more traditional commodity continues to be optimized further as AI-enabled automation takes hold. Overall, we believe strong executors would gain a lot, but by changing their business pitch both as a native and AI amplified services. Looking ahead, we are retaining our guidance of 1% to 4% and margin guidance of 17.5% to 18.5% for FY '27. The guidance is organic growth guidance and does not include acquisitions, including [ JasperSoft ]. Now I would request Shiv to share more details on the numbers.

Thank you. Good morning, good afternoon and good evening to all of you. Thank you for joining our Q1 financial year '27 earnings call. Let me walk you through our financial performance for the quarter. Starting with the revenue performance. Please note that all the growth numbers quoted are in constant currency unless noted otherwise. Our total revenue for the quarter is 3,650 million, a decline of 0.5% quarter-on-quarter and growth of 2.6% year-on-year. Services revenue for the quarter came in at $351 million, a decline of 0.7% quarter-on-quarter and growth of 3.5% year-on-year. Our ITS services is flat quarter-on-quarter and grew 4.2% year-on-year. The ERS segment declined 3.7% quarter-on-quarter and grew 13% year-over-year. HCL software revenue for the quarter is $33 million, representing growth of 2.2% quarter-on-quarter and a decline of 5.3% year-on-year. In terms of geographies, during the quarter, the U.S.A. grew 2.9% year-on-year. Europe grew 0.1% in Rest of the world grew 10.8% and India grew 16.9%. Moving on to verticals. Our Q1 growth was broad-based with 6 out of 7 verticals registering year-on-year growth. Growth was led by public services and retail and which grew 12% and 10.1% year-on-year, respectively. In terms of clients, our continued focus on deepening customer relationships have helped us expand the number of large client relationships. On a year-on-year basis, we added one client in the $100 million-plus category, 6 clients in the $50 million plus category, 11 clients in the $20 million-plus category and 31 clients in the $10 million-plus category. In terms of profitability, our EBIT is at $66 million, representing 16.9% of revenue. Adjusting for restructuring expenses of 62 basis points during the quarter, our Q1 EBIT margins are 17.5% compared with 17.7% in the previous quarter. Net income for the quarter is 488 million, representing 13.4% of revenue. In terms of EBIT margin was, the margin is explaining the sequential margin movement is as follows. The reported EBIT margin increased by 39 basis points quarter-on-quarter from 16.5% in JFM 26 to 16.9% in AMG '26. Lower restructuring expenses gave us 70 basis points and benefit on [indiscernible] basis points. This tailwind was offset by a 10 basis point headwind from the seasonality due to annual productivity benefits and decline in ERS revenue ForEx gave us benefit of 60 basis points in the quarter. Now moving on to the return on invested capital, ROIC. Our ROIC continues to remain strong supported by our ongoing focus on profitability and efficient capital management. The last 12 months ROIC is at 40.7% [indiscernible] up 257 basis points year-on-year. Services ROIC is at 47.8%, up 260 basis points year-on-year. at full software is at 21.6%, which is up 75 basis points year-on-year. In terms of cash generation, over the last 12 months, free cash flow is at 1.98 billion, while operating cash flow is at 2.14 billion. Free cash flow to net income is 9% and operating cash flow to net income at 107%. Our balance sheet remained strong with gross cash of $2.86 billion and net cash of $2.84 billion as on 30th June 2026. In terms of DSO, our total DSO, including unbilled receivables is at 86%, representing an increase of 2 days quarter-on-quarter. In terms of EPS and dividends for our shareholders, normalized diluted EPS for the last 12 months came in at 66.9 representing a growth of 4.5% quarter-on-quarter and 6.9% year-on-year, including the onetime impact of the new labor code diluted EPS was 64.25, the [indiscernible] has declared an interim diet of INR 12 per share for the quarter. The report result 17th of July '26, and the payment date shall be 27th of July '26. This brings our last 12 months payout to INR 60 per share effectively distributing 93.2% of our net income. That is all from my side for now, and I would like to hand over the session to our moderator for the Q&A session. Thank you.

[Operator Instructions]. Our first question comes from the line of Abhishek Bhandari with Nomura

Congrats on the good deal wins. I have two questions. First is on your guidance. This quarter, we had 2.4 billion deal, which is the test content you said is highest ever for any Q1. And along with that, we also had a mega deal announced in first week of July. So what are the new biggest moving parts which is restricting you from increasing the guidance on? I'll come back to the second question.

So yes, we are happy to report a very strong booking. But as you know, our guidance band is a little broader. And this is only the first quarter. So we would like to see how things pan out in the next quarter. On the mega deal win, the transition is expected to start in a couple of months. And the steady state is expected to be reached only in the -- in April of 2027 which is coming in the next financial year. It will have a negligible impact to our revenue in this financial year. And that's really what it is to shape

Got it. My second and last question is on the investment in the data center. If I -- if you can share more details around it, what are the upper limits or the period of investment in this -- in the particular [indiscernible]. If I look at it, you closeout almost like $7 million per megawatt is you kind of the cost for a colo data center not an AI data center. So I'm little confused what makes you say the AI data center? Are there any increasing arisen on the investments once you dispose the INR 1,500 crores.

Yes. Our 50-megawatt is a long-term plan, the INR 3,500 crores is actually representing only a fraction of that capacity, and that is the initial investment that should get us started. And we will have a very disciplined approach to increasing investments based on the free cash flow that's getting generated from the business. So this is an initial investment that should get us started. This is not a colo business. This is going to be full stack rate. And there are potential possibilities of funding this through a mix of partners, arrangements with silicon and OEM vendors and committed capacity from clients and consumption models where the hardest financed against mutant demand. Even this could be funded through a mix of equity and debt. So we are not putting this entire investment in the balance sheet in a single year. We are not funding it at the expense of our stated payout policy. We will provide more details as we progress. So you should not correlate and calculate INR 3,500 crores for 50 megawatts. But 50-megawatt is a long-term plan, and this investment is for a much smaller capacity, which will be an end-to-end stack.

Our next question comes from the line of Abhishek Pathak with Motilal Oswal.

congrats on a fantastic quarter. I had a couple of questions. Firstly, how do you view token costs in context of AI adoption if there had not been so high, do you think our several revenue would have been higher. And over a 2- to 3-year perspective, how does your team look at open cost? I mean, do you guys expect to open cost to collapse which leads to massive AI implementation revenues? Or do you expect them to be elevated, which slows down AI displacement and hence leads to better defense for IT services? So that's the first question on and maybe I'll just follow up with the second one after this.

Yes. Our total cost, I mean, if you see about 3 months ago or 6 months ago, token cost was not a topic. It's only when enterprises started scaling the adoption of AI the whole various dimensions of token costs came into play. Now token as the token consumption cost, we believe -- I mean -- it really depends on the exact models that you are implementing. And customers are looking at creative ways to reduce their overall token costs. And that is where the tiered approach is becoming the most popular enterprise AI architecture, both for data sovereignty for the enterprises and for the right price performance. So token costs could drop. But however, the overall consumption of tokens will go up, so total cost will also go up. So you need to build a more economic model, which is where the -- our strategy of building a tiered approach with smaller models within the enterprise, which can be trained on the enterprise data and also a 0 trust architecture with the Policy Enforcement Gateway which ensures only -- which ensures that no data or prompts or context leaves the enterprise. So that's the model which is becoming prevalent. And this will have some meaningful very, very meaningful services revenue opportunity because in every client training excellence it requires a lot of data work and also training can also be quite intensive in terms of the search requirements and all of that. So we think it will be like another engineering services base that we can create by really kind of pursuing our strategy on a hybrid AI stack.

Understood. And in that context then, it was interesting when you mentioned that serum AI is something that you're looking at from the Indian market standpoint. Is it possible to take [indiscernible] low-cost models maybe to global clients as well? And are you kind of in discussions about that too? And the last question was to shave on margins. Do we expect to kind of get back to our original 18% to 19% sort of margin bank anytime soon, maybe in -- or do we expect the AI investments to kind of continue and kind of hold back our margins a bit going forward in the medium term as well?

Yes. So Abhishek, as you rightly mentioned, apart from what we can do in the Indian enterprises and public sector and government, there is an opportunity with the global enterprises. We have talked about tiered approach and SLM's model, and it is generating a lot of interest. So [indiscernible] is a very good option where we have a lot more stronger partnership and our ability to kind of really build the entire training infrastructure, training the small language models on enterprise data and some of the research capabilities, all that comes in very handy and we build it. But the model dependency still need not be serving because there are other options as well. But I think our closer strategic partnership helps us drive this with a stronger execution.

Abhishek, on the margin front, if you remember last year, if you take out the impact of restructuring costs, then our margins was closer to 18%. And this year, the guidance is 17.5% to 18.5%, and that also includes approximately 40 to 50 basis point [indiscernible] cost impact. As regards maybe the longer term or the medium term horizon of around FY '28, we will keep that guidance at a onto time when we keep guidance for '28 next year. So at this stage of time, I would just like to focus on this year's margin guidance, which is 17.5% to 18.5%.

Our next question comes from the line of Ravi Menon with Axis Capital.

[indiscernible] in the IT and business services considering for the seasonality and headwinds in the telecom customers. And I think the program ramp down that you had called out last quarter. But you was a decline of surprise, which segment posted is there any further plan anticipated in the R&D in the coming quarters?

Yes. The decline in R&D was in tech and telecom, media and entertainment verticals. And we did call out that we had some sharp cuts to discretionary spending into large U.S. telcos, and we did say that it will have an impact in the subsequent quarters, and that is what is playing out. And we had a very strong momentum in the tape vertical for last many quarters. So some of this is on the very high base. So that's really what [indiscernible].

And what's prompted everything on the air data investment is because you're seeing more customers now wanting to probably run open rate models and control the hardware where the better [indiscernible]?

Yes. Yes, absolutely. I mean -- and the closed models have their own significant limitations. So clients are looking at open models, both open weight and open source models. In data center, our play is a fundamentally different strategy because the large gigawatt announcements are more capacity plays and their infrastructure companies where the product is at for megawatt is in the product. It was just 3 anchored. Our value is in full stack of AI high-margin services, which we wrap around capacity. More importantly, it would be deploying efficient SLM led models, as you did call out, to address industry and vertical needs. And 50-megawatt is good capacity to build a large business if we want to do small language models and not frontier models. This will generate far more enterprise value per megawatt than raw hyperscale capacity because we monetize the entire solution, not just space and power. And this capacity is also going to help us to drive more and more outcome-based contracts and managed services contracts where we can consume some of this capacity, which gets bundled into our or outcome-based pricing and managed services pricing for global clients. So I think these 2 were very important kind of dimensions, which made this business very operative.

And last question, as your revenue per employee increases, do you also expect gross margin to expand.

Yes, of course, from last year to this year, our guidance is improving gross margins. But I think the our strategy works out as we have planned. we do expect the gross margin per employee to increase. However, we will continue to invest because the business. This is -- the business is in a significant inflection point and transformation. So we will not hesitate making the right investments, while, of course, continuing to demand and get greater value from our clients.

Our next question comes from the line of Sudheer Guntupalli with Kotak Mahindra Asset Management Company. Please go ahead.

[indiscernible]