Expect strong revenue growth on stabilizing tech spends: C Vijayakumar, CEO, HCLTech

Even as most of the top Indian information technology (IT) services companies reported slowdowns in the March quarter, large-cap firm HCLTech beat analyst expectations in its FY23 earnings and projected a revenue growth rate of 6-8% for FY24. While this is lower than the 12-14% revenue growth that the company had projected for the previous financial year, HCLTech outperformed fellow IT services firm Infosys, and remained in line with industry expectations. In an interview following the earnings call, C. Vijayakumar, managing director and chief executive of HCLTech, said that the company expects strong revenue growth in 2024, on the back of already-stabilizing tech spends in sectors such as BFSI. He also discussed how generative AI applications are being built into the company’s already existing suite of software platforms. Edited excerpts:

For FY24, do you expect BFSI and other strong sectors to stabilize in the near term?

We are already seeing several business verticals stabilizing, and others should stabilize soon as well. This should help us drive strong revenue growth, despite the projections.

Going forward, one important factor to note is our software business — it has done exceedingly well, specifically in the previous two quarters that are seasonally weak. This drove our software segment to cross an annual recurring revenue (ARR) of $1 billion in the March quarter. Our revenue from the software segment grew 3-5% annually at the end of each of the past four quarters of FY23.

Are there any specific verticals that you’d be focusing on in FY24, taking the macroeconomic projections into account?

There are two or three areas that we are focusing on. The first is ESG and sustainability, which offers tremendous business opportunities. We already have several minimum viable products within the ESG and sustainability paradigm, and in the coming year we plan to incubate and significantly scale this segment.

Our second segmental focus is to understand how we can get generative AI as an important solution component in all of our businesses. We’re still incubating this as a business segment, to see how we can leverage it.

But are you seeing any projection of caution and cutback in discretionary tech spending among clients?

Yes — technically. Some clients will consider spending in new technologies, such as generative AI, as discretionary. However, they are also aware of being left behind, if they don’t at least start investing in new tech areas. This is the same thought process that we’ve seen in our digital services business.

AI and sustainability are areas that customers want to invest in, so that they don’t fall behind the rest of their industries. Some of the spends can technically be avoided in the short term, but this comes at the cost of creating differentiation in the long run from a business standpoint.

Would pursuing these new verticals require significant cost and effort in terms of upskilling your workforce?

If we take generative AI as an example, we already have sets of people who are fairly strong in programming, and even in specific languages such as Python and others. They can be upskilled fairly easily in order to help us build some of the generative AI solutions that we’re looking at.

But, more than a technical aspect, there is also the role of a business analyst, which we need to bring in for such roles. They’d be important in order to look at a business, evaluate which are the most labor-intensive operations, and how some of that can be enabled through generative AI. That is one area that we’ll specifically look at, alongside technical skills.

Beyond generative AI, are niche new tech applications like quantum computing generating any client interest?

It’s still very early days for quantum computing, at least for service providers. This is a field that is a stronger area of interest for technology infrastructure builders and tech-specific companies. But, it’s important to understand that even in the case of generative AI, one of the impediments is the amount of compute power and cloud capacity in order to learn and apply the AI models, which restrict the development and applicability of a lot of applications on this technology right now. At some point, quantum applications could factor into businesses the way generative AI has.