NIIT Limited (NIITLTD) Q1 2027 Earnings Call Transcript

Ladies and gentlemen, good day, and welcome to the NIT Limited Q1FI27 Earnings Conference Call. As a reminder, all participant lines will be in the listener-only mode, and there will be an opportunity for you to ask questions after the presentation concludes. Should you need assistance during this conference call, please signal an operator by pressing star, then zero on a touchstone form. Please note that this conference is being recorded. I now hand the conference over to Mr. Vijay Thadani, Vice Chairman and Managing Director of NIIT Limited. Thank you, and over to you, sir.

Thank you. Good afternoon. Actually, good evening, and welcome to NIIT Limited's Quarter 1 F527 Earnings Call. As usual, we thank you for your interest in NIT Limited, as well as the time that you are spending today with us in the middle of a busy results season, and for joining the call and giving us your support and suggestions. Today's agenda is to discuss with you the quarter one FI27 performance highlights. Second, what is shaping FY27 and the actions that we are taking, our priorities and outlook. I'm happy to share with you as a start that we are starting off FY27 on a strong note, definitely stronger than the same period last year, and I think it is increasingly becoming stronger as we go forward. It is both enterprise as well as consumer go-to-market engines showing growth in Q1. While technology continues to grow well from AI-led investments in scaling, we also have growth from banking financial services and others. Order intake continues to remain strong, vindicating our investments. In the new AI programs, as well as our go-to-market initiatives. On the profitability front, our EBITDA is moving in the right direction, with our operating costs growing slower than our revenue. Just to remind that certain parts of the business have been in an investment cycle, and in quarter one, those investments are normally higher than other quarters. With that, I'll hand you over to Pankaj, our CEO, to take you through the quarter one performance in detail, and then we'll open up for a question now.

Thank you, Vijay, and good afternoon, everyone. I will cover the Q1 performance first, the revenue, order intake, and business trends, and then step back to talk about our priorities for the rest of FY27. Do note. That our business has originality. So we look at year-on-year trends rather than quarter-on-quarter. Revenue for Q1 FY27 came in at $957 million, which is up 14% year-on-year. Enterprise revenue was at 618% which is up 8% year-on-year. This was driven by enterprise tech training. Which grew 16% year-on-year to 498 million, which was as an outcome of our strategy to focus on upskilling and re-skilling natural job roles, even as pressure onboarding and training remained volatile. On the consumer side, the consumer revenue was at 339 million, which was up 27% year-on-year. Within that, consumer tech continued to see momentum. Growing 15% year-on-year to Rs. 182 million. Our direct-to-college strategy is creating a pipeline of job-ready talent, which university clients are increasingly valuing. The recovery that we see in consumer business from BFSI and others in Q4 saw further pickup in volumes in Q1, as pressure hiring picked up pace at partner banks. The strong growth in the consumer business has led to a shift in the enterprise-to-consumer revenue mix. From 68 is to 32 in the same period last year, to 65 is to 35 in Q1 this year. Viewed from a product lens, technology continued to grow well, clocking revenue of 680 million, up 16% year-on-year. Revenue from BFSI and other programs was at 277 million, which is up 9% year-on-year. Driven by strong pressure hiring, even as lateral training continued to be under pressure. Order and take. In Q1, it was at 953 million. I will now invite Sanjeev, our Chief Financial Officer, to provide an update on the financials.

Over to you, Sanjeev. Thanks, Pankaj. I will take you through financial results. A bidder for Q1 was negative at 14 million. This is a significant improvement from the negative 63 million in Q1 of last year. This is driven by improved productivity and operating leverage while we continue to invest in GTM capacity and new AI offerings. As Vijay mentioned in his opening remarks, while our new top line grew by 14%, our operating expenses grew 7%, putting us back on the path to positive EBITDA margin. Below EBITDA, depreciation was at 96 million in Q1. Net other income was 180 million. This is primarily comprising of treasury income of 175 million and other miscellaneous income of 24 million. That is offset by net finance cost of 3 million and there are some exceptional expenses of 15 million primarily because of the legacy tax matter that has now been concluded in NIT's cover. And some part of the cost is pertaining to the scheme of arrangements for amalgamation of RPS and IFBI into NIT Limited. This resulted in a PAT of 81 million for the quarter, which is up 85% YUI and EPS of 60 PASA, that is up 84% of YUI basis. Now coming to balance sheet and cash flows, cash and cash equivalents remain strong at 7231 million, 7231 million, underpinning our ability to invest through the cycle. Capex was 68 million for the quarter. We are past the peak on capital investment in platform in the current investment cycle and we expect capital expenditure to mold it from there. DSO was at 53 days in Q1, which is same as last quarter. Employee count at the end of Q1 was 866 million, which is down 65 on QOQ basis and 19 number of people on YUA basis. Now back to Pankash.

Thank you, Sanjeev. Let me talk about what we are doing right now and through the rest of FY27. We will be accelerating what is working. On the tech trading front, AI and new logos is working. We are continuing to scale AI programs and work pro offerings, which showed strong growth in FY26, and that's where we see demand signals being the healthiest. We are continuing to expand coverage of GCCs and India enterprise companies, and positioning reskilling around role evolution, particularly AI-enabled role redesign through outcome-led programs. On the BFSI side, we have been recovering, and that's the plan, our strategy of diversifying beyond the top four private banks to a broader set of financial service players, including NBFCs and insurance companies, is progressing well. In Q1 FY27, NIIT moved beyond its banking anchor to activate four new solution lines across insurance, NVFC, Wells, and Gen AI. These are not pirates. These are live commercial engagements with more than 15 clients outside of traditional bank induction kind of programs, which is generating new revenue for us. As we accelerate this transformation, we hope to further reduce concentration risk and drive growth through the cycles. In terms of the road ahead, our investment thesis is showing up in new logos, digital engagement, order intake, and a pipeline that steams. We are seeing improved consumption of our differentiated, outcome-oriented offerings across the technology landscape, with working professionals and job seekers both contributing to growth. In BFSI, the picture is too speed right now. Onboarding demands showing early signs of recovery, while upskilling and L&D budgets at large private banks remain constrained. We are positioned to capture the onboarding recovery and are actively broadening the customer base and shifting the program mix to be less dependent on L&D cycles of any individual customer. With merger of RTS Consulting and IFBI into NIIT, we have strengthened our offerings to address the reskilling and retooling agenda, including deep transformative programs for existing talent. The AI Opportunity AI represents one of the most significant demand opportunities in front of us, and it is happening now, not at some point in the future. AI is now embedded across a larger share of our portfolio, and revenue from AI programs has grown to 9% of total revenue. Our OI story is becoming sharply refined, and nowhere is this more visible than in our work with GSIs and GCCs. AI augmented engineering teams are already running 40 to 70% smaller than their conventional equivalents. One engagement we are aware of compressed a planned 150% team down to 42%. Across GSIs broadly, analysis suggests that more than half of current task content roles face displacement over the next 36 months in waves that have already begun. GSIs and GCCs are positioning themselves as the change agents for their clients' AI transformation. But the transformation they are driving externally will need to be mirrored internally. A number of current roles are becoming redundant and must transition into new AI-era roles, and that creates a three-part talent opportunity for us. Reskilling existing employees whose roles are evolving, retooling staff displayed by productivity gains into new AI-era roles, and onboarding new early career talent into roles that require accelerated outcome-based programs rather than traditional induction. In-house L&D teams will struggle to scale at the pace this transformation demands, and the existing response, internal AI academies, built around course completion and certification, is structurally inadequate. Training is moving from skilling to capability orchestration. Completion rates do not prove judgment under uncertainty, AI output verification, or agentic workflow design. That is precisely the opportunity for NIT. During the quarter, we deepened our AI curriculum with the launch of training programs for forward deployed engineers, site reliability engineers, AI auditors, and also the AI prism. These complement our established offerings in AI engineering and agentic AI, and together they address the full life cycle of enterprise AI adoption, building, deploying, operating, and governing AI solutions at scale. What distinguishes these programs is their design philosophy, applied, use case-led, learning journeys built around higher-value, AI-augmented roles that enterprises are actively hiring and upskilling for. Beyond broad AI fluency and Gen AI capability building, we are now winning specific need-based client engagements covering AI economics, capex planning, token optimization, and AI audit, areas where the demand signal is sharp and client willingness to invent is high. A structurally similar dynamic is playing out across BFSI and India enterprise companies, and our AI programs are well positioned to serve that opportunity. On the early career side, iamneo directly addresses the onboarding opportunities. Through its university partnerships and college-to-corporate bridge, iamneo enables early career talent to take on roles that previously required years of experience. Our synthetic work platform and the architect on graduation product are purpose-built for exactly this transition. Let me quickly take you through the guidance for Q2 FY27. We expect double-digit revenue growth year-on-year in Q2 FY27. On margins, we expect near-break-even at the EBITDA level in Q2, positioning us for positive margins in the second half of the year. We expect stronger revenue growth, improving margin, and continued order intake momentum for FY27 as compared to FY26. Medium to long term, the structural opportunity in skilling remains substantial, and we are fully committed to our strategic objectives. With that, Vijay, I hand it back to you.

Thank you, Pankaj. Just summarizing, we have started the FI27 with a robust growth, a strong order book, a broader customer base, and a clear sense of what and where are we winning. We are responding to the areas of pressure by wiping the demand base, accelerating the parts of the portfolio that are working. Especially technology and AI, and maintaining cost discipline while continuing targeted investments. Our investment cycle continues. However, our focus has more become on AI programs and usage of AI in every program that we are serving our customers with. What gives us confidence is that the portfolio is becoming more resilient. Strengthening of a product portfolio for working professionals, rollout of new AI programs, go-to-market expansion, and the I Am Here initiative are all showing early results. We remain confident of the longer-term structural growth opportunity and are committed to making the investments needed to capture that opportunity. So, in addition to investing in new programs and stronger go-to-market initiatives, we continue to follow a disciplined approach to evaluating inorganic opportunities that enhance capabilities, channels, and or intellectual property, and which offer a clear path to returns and cash returns. So, I want to pause here and open this line for questions. And then we can take the decision. Operator.

Thank you very much. We will now begin with the question and answer session. Anyone who wishes to ask a question may press star and then one on the touchstone telephone. If you wish to remove yourself from the question queue, you may press star and then two. Participants, you are requested to use handsets while asking a question. Ladies and gentlemen, we will wait for a moment while the question queue assembles. A reminder to all, you may press star and then 1 to ask a question. We have the first question from the line of Harsh Yadav, from Dollars Capital Markets, Private Limited. Please go ahead.

Hi, a very good evening to you. Am I audible?

Sorry to interrupt, Harsh, you are not audible. Please use your handset mode and speak.

Hi, a very good evening to you. Am I audible now?

Yes, very audible. All right.

So, my first question is, basically, in the presentation, you highlighted that AI-led programs now contribute about 9% of overall revenue. Given that enterprise clients are compressing the traditional team sizes, how are pricing realizations and ARCU trending for AI-led capability building compared to legacy IT training?

I mean, you know, you said first question, so is there another question that you can ask?

Yes, there are a few more questions I have.

Why don't you answer the question? Okay, let me answer the question. The direction you are hinting at is true. AI-led training does have a higher realization than traditional training. But batch sizes will tend to be smaller for AI training than the more traditional training. Especially for some of the advanced concepts like agentic AI, etc. There is a doing-in requirement of knowing how to code, knowing Python, So, those entry criteria need to be met. So, the average realization will be higher, but typically batch sizes would end up being a little smaller.

Okay. My next question is, so, consumer posted a robust growth of 27% year over year, even though your total enrollment saw a quarter over quarter dip by around 150,000. Could you provide some color on the split between Early Career and WorkPro Learners this quarter?

So, we used to track early career work pro, but those lines have become so fuzzy that when we are talking of consumers, consumers also have work pros built into them. So, we are not at this point of time breaking that sufficient to say that the early career part, if we were to take IMDb's offerings for it, They service a large number of universities, and those will all... I think that part...

Just to follow up on that, as we have seen that top five IT services firms continue to curtail their freshers hiring, so within consumer, has growth primarily been driven by experienced working professionals that are upskilling in AI? And also, I just wanted to know how StackRoot and P-Pass are performing in this environment?

Sorry, I haven't heard the first part, which I'll answer. The second part, I'll ask you to repeat, if you don't mind. So, there is a... Now, let me further subdivide early career in two parts. One is pressure. 2, 0 to 3. In that segment, because people are reskilling themselves, like our agentic AI programs. For example, the pull for those is higher because the current people who have been hired or are working in organizations need to reskill themselves very quickly, A, to retain their jobs, and B, to find growth opportunities. So, I think that's where the real push is. The research... It's largely driven by the onboarding requirement of corporates, which have not started yet, but there are, when we look at IT hiring, we look at the top 10 or top 20 IT services companies. And other companies which are also in the hiring team and GCCs, where the numbers are not individually at a very large level, but there are a very large number of companies. So I think there is a momentum which is building up there.

Okay. All right. My second part of this question was actually I just wanted to know how StackRoot and TeePass are performing in this environment.

Okay, I think... The terminologies have... And I think that's also reflective in how we have managed our past, but maybe, Pankaj, you will talk about this and I can hear this.

So, we've combined RPS and StackRoot entities and we call that Enterprise Technology Learning Solution. They are both housed under NIT, and therefore, you don't have those available separate parts. And we've actually integrated those things. So, it's not that we can separate out either. It's actually integrated into one team. But to answer your question on how they're performing in this environment, they are performing very well. We are seeing robust growth. We hope as an interface deck. All right. In the sleep performance. Thank you. Significant components of our business have performed well.

I just have a very qualitative question. Just wanted to shoot it. So, I've been noticing with the advent, so there's an advent of a lot of IIT and IIM offerings with respect to online certifications, degree programs, especially in this AI, agentic applications, FDE, etc. So how do we position ourselves in this environment and what are we doing to create like an edge in terms of program structure or like an implementation point of view with this upcoming courses and programs from so many different educational institutions within the country and also outside?

So, you are right, there is a lot of different programs that are coming in which makes it difficult It's important for a customer to actually understand. What they are getting for, right? So you have programs which promise agentic AI training from 10 hours up to 600 hours. And therefore, a customer will find it difficult to compare those two things and understand what they should get into. What we are doing is, of course, trying to provide as much information as we can. On the consumer side, and on the corporate side, of course, there are differentiators that we bring to the table, especially outcome orientation, right? One of the things that we talk to customers about on the enterprise side of the business is on delivering outcomes through our training programs rather than completion, right? So, therefore, it's not that we will just track how many attended, how many completed. We will work with customers to track outcomes of the programs we deliver. So, those are The areas that we are able to differentiate, how we provide this training. But you are right, it is becoming a very competitive market. And people are using buzzwords like FDE, etc. to bring new offerings. And it's up to us to keep educating our customers and providing the differentiation we need to do.

Okay, thank you so much. No, I'll let me add one line. I think we at least believe that in this, in the new world that we are in, it is the capability which counts rather than the credential. So we are not running after credentials, we are running after building capability. And I think that success is very visible in our enterprise Enterprise, uh, uh, uh, enterprise offering. Our enterprise offerings are showing a clear differentiation, because we are able to demonstrate outcomes in terms of capability, which leads to productivity and effectiveness of the workforce. So people are preferring that rather than adopting a credential-based program. On the consumer side, that awareness is not yet there, but wherever we have access, we would like to focus on that part. Because I think the long term lies in, not in credentialing, but in the capability which can be demonstrated. And employers will now hire for capability and not the credential.

Yeah, okay. I agree, actually. Thank you so very much. These were my questions. Yeah.

Thank you very much.

We will take the next question from the line of Aman Prakash, an individual investor. Please go ahead.

Hi, thank you for taking my question. And my question is to Pankaj. You mentioned about outcome-based learning, right? So I want to understand more about this because you're right, you know, that, I mean, if you use AI, it is in the end the outcome that counts, right? And if you take this into account, then the umbrella of opportunity is far bigger. It's not just IT companies, right? Eventually, it might circulate down to other sectors as well. So, I want to know more about how we are going about this outcome-based learning right now and what are the plans for the future?

So, Aman, actually, forever NIT has been talking about delivering outcomes through learning, right? So, it's not just now in the AI era that we are talking about outcome-based learning. We've always believed that there's no point in doing a learning program unless we are able to deliver and demonstrate that outcome. That belief continues in how we approach training and we build a fit-for-usage kind of training program. So depending on who it is and what it is being made for, we create training programs that will deliver specific outcomes. We are working across the organization. So at the entry level, we deliver boot camp oriented programs to help New joiners become productive from day one. So we deliver that kind of an outcome. At the more senior level, we deliver architecture programs which help seasoned architects become even better at their job at managing large teams and delivering outcomes. And we also do some leadership training programs where the final outcome is a change in behavior. So the way we do this is by tracking before and after training-related metrics and working with our customers to track the outcomes of our training.

Vijay, I guess outcome depends, as Pankal rightly pointed out. Outcome depends on what is the outcome that you came for. If you came for, we are firm believers of the fact, getting a job is not the problem. Getting the job is the real challenge. When people join a course, they are not joining it for a job, a job you can get, but the job, a job which is consistent with the investment that you made in that course. And that you will get only if you demonstrate that capability in terms of being able to do and create a live application. And I think there are enough and more ways by which. So, if you are able to build and solve that problem that is given in the hackathon then you have a reason. So, I am giving you that as an example. An agentic AI, for example, program, a person who's doing, he may have an agent that he, or a bunch of agents that he has to create to solve a workflow problem in his organization. In which case, was he able to do that? In this program, by the end of the program, you could actually have an early part or an early version of that agent ready for deployment. So I think that is not something which any credential-based program typically offers.

Okay, all right. Thank you for the response. Just one last question regarding this outcome-based, right? One is the outcome at the personal or the individual level, right? But we see in India a lot of, like, these legacy companies, right, which eventually will have to, like, or will move towards AI. So then there is, because a big part of our business, I think, is more than 60% is now B2B enterprise level. So, is there, like, a thing, let's say, an organization approaches NIT and then the outcome-based AI, like, how do you say learning or the transformation can happen, anything of that sort, like, is going on or is it in the pipeline?

Yeah, yeah. So I gave you some examples of an early career person. But in organizations who are deploying, for example, GSIs or GCCs, they have specific initiatives happening where their people have to be billable. How long are the people billable after they join that organization is an outcome that they have. It's very important to them. We would like them to be billable in day one, hour one. And if we are able to deliver that, then the organization would prefer that. So I think that's also an example. How do their realizations improve? How do their deliverables improve? So although actually in an enterprise program, in a running enterprise, when you introduce AI, outcomes are more easily definable.

Okay. Okay. Yeah. Correct. Thank you. That's all from my side and all the best.

Thank you. Thank you.

Before we take the next question, a reminder to all the participants, you may press star and one to ask a question. We have the next question from the line of Ganesh Shetty, an individual investor. Please go ahead.

Good evening, sir, and thank you very much for taking my question. My question is regarding integration of StackRoot, NIT enterprise business, and also RPS consulting. So after this integration of these businesses, whether we have fine-tuned our go-to-market strategy, and whether this will also result in easier processes for the company and market improvement. Can you please throw some light on me.

Thanks, Ganesh, for taking the time to join the conference and for the question. In one word, yes, integrating StackRoot and RPS together improves our go-to-market. They are both very complementary offerings in many ways. One does, one used to do OEM-specific training, the other builds long-term. Solutions for customers based on what they want specifically. So both of those are complementary offerings and that makes our go-to-market that much stronger. They also had reasonably complementary customer bases. One was GSI heavy, the other GCC heavy. So that also helps us build a stronger market presence for that business. So, definitely the integration has improved our ability to go to market with their offerings. And in terms of easier process, that's an ongoing work that we've been doing, which is to simplify parts of the organization and simplify things how we work. Yes, this integration, of course, helps us simplify some of those things, but it's an ongoing NIT-wide initiative anyway that we are working on to improve our ways of working and simplifying things. I hope that answers your question, Marich.

Yeah.

Net-net, I think what Pankaj is trying to say is that the combination has... And I think the combination has got integrated in the last few months, right? Even though officially it has happened from 1st of July, but it has been in the works before that. And I think the combination has got going, as you can see, from the enterprise tech results also. And I think we'll see more efficiency and... And better performance as we go. Obviously, the tailwind of the environment is also has a pain. Yeah.

So, my second question is like continuation of earlier respondent. We are now serving mostly BFSI and technology sector and as AI is now entering all the sectors and is a part of you know natural progress. So, are we targeting any other sectors, you know, for giving them AI-related training or we are preparing ourselves to market ourselves as an AI leader in training to access other sectors, auto or anything like that, industrial, where we can showcase our AI capabilities and make them AI-based.

So, we are actually already recognized as a leader in AI training, right, and Well, yes, you're right, the largest part of our business comes from these two areas, but we are working with customers in the auto, telecom, India enterprise side, and some of the work we are doing also involves AI. In fact, we've developed some interesting new AI-based tools, which we are deploying with some of the customers from these industries and helping them improve their capability on sales, on service, etc. So we are working with customers beyond these two sectors as well, and specifically with AI as the main thrust of our offering in these areas.

Okay, sir, my third question is regarding the opportunity in university sector. As we, there are hundreds of universities, deemed universities in India, but they are lacking, I think, AI compatibility, and we are having IMU as a special division where we can easily collaborate with institutions or universities apart from placement services. for giving them content for AI training, for their in-house capabilities. So, are we trying for these type of businesses right now? Is there anything like that in our pipeline, sir?

So, Amneo is focused on university's business, and they will continue to expand in that area. And we will build our presence through the IMNEO go-to-market that we have. AI is, of course, a large part of IMNEO's tool set as well. And they launched a couple of new offerings in the last quarter, which are very AI-centric for the university segment. And we are seeing good traction from that also. Vijay, anything you want to add to that, to the university segment?

No, I think, yes, you are absolutely right. The universities are very hungry to add AI in their curriculum. However, I think different universities have different level of commitment for that. The solution that we are offering from AI... You know, is a very, very superior solution and would be suitable only for maybe top 500 or so. And then we are looking at solutions which the other universities would like to have. So, for example, engineering colleges, the level of AI solutions that they need are very different or curriculum that they need is very different from What, let's say, a commerce or a liberal arts university would look at, or a science university would look at. So I think defining a curriculum, which is for each segment, is the next issue. AI is not a magic wand by itself. AI has to be used in specific situations, in a specific manner for best. And that's what I think our focus is.

Sir, can I ask one more question?

Yes, sir.

The macro has been very challenging for last entire year. Coming back to our own business, whether we can see that whether the macro they improved from the last quarter or it has deteriorated this quarter or whether we are in the same mode and there is no improvement in macros and the business is as easy. That's all for me. Thank you very much.

Well, I think you understand macros better than we do, and we all get swayed by the macros, by statements of one leader or the other, and by some actions. I think the situation, I would tend to feel the situation remains the same. There are days when it looks about to be very, very bright enough a lot, but there are days when... It just goes back to, and nowadays, the current days that we are going through are not pointing in the right direction. So I think we have to, we have to look at the opportunities ahead of us rather than we get concerned by the macros a lot. Of course, we have to be conscious of that. So for us, the AI opportunity. We are very dependent on how the environment works. We will. We are also opening.

Thank you very much, sir, and all the best.

Thank you very much. Ladies and gentlemen, that was the last question. And with that concludes the question and answer session. I now hand the conference back to the management for the closing comments. Thank you and over to you, sir.

Okay. Thank you very much for joining us this afternoon or this evening for this session. This is the first time we have switched to the timing of the call to be such. We would love to receive your feedback on how you found it in terms of convenience and, of course, on content, your questions always educate us and open new windows or doors in our mind of the opportunities ahead of us. And we remain grateful to you for giving us your time for your support and for your guidance from time to time. Thank you very much and wishing you the best.

Thank you members of the management. On behalf of NIT Limited, we conclude this conference. Thank you everyone for joining with us today and you may now disconnect your lives. Thank you.