We have seen Nifty IT outperforming the rest of the market this month. What is driving this sudden strength? Is it just pure sector rotation? Is it the churn that we are seeing or do you believe fundamentally this has merit in terms of the way Nifty IT has been outperforming?
Rahul Jain: A part of this could be related to the kind of correction that we saw in the February-March period when the expectation for the sector in terms of growth in earnings were much higher and subsequently the valuation corrected. When the earnings started, we got a mixed set of commentary where some companies saw a lot of impact related to the macro or the tariff kind of a thing, while many other companies said that they have seen very limited observation in terms of any deterioration related to that.
Since the earnings, one-and-a-half, two months have gone and we have not seen any further deterioration, rather on the tariff side, there is a lot of normalisation that has happened with many countries. Some bit of ambiguity will come into play as tariffs eventually come into picture. But for now, no bad news has acted as good news in the space. Valuations were low, growth expectations are low, and valuation can see some room for upside if the growth eventually improves.
The market is anticipating that as the year progresses and there is no incremental bad news shaping up in the sector. The growth assumption in the sector will eventually improve and will drive the valuation. So, that is something which is finding value in this space at this point and should continue as the year progresses.
The valuation comfort is still there, but also gives us some sense how the deal momentum is picking up. Is there anything incremental that you are picking up right now because back in the earning season, we have seen quite a mixed commentary coming in especially with respect to discretionary spending in the US. Has anything changed in terms of the pickup over there?
Rahul Jain: We keep getting those press releases by the respective companies where they announce important deals once in a while, so that is a usual activity. But we do not hear from our recent interaction with companies where they are seeing the stalling of the ramp up. Stalling of the ramp up has been a bigger pain point in the last two years, more than the deal gaps itself.
I agree that the deal win momentum is quite mixed across players and it is not very uniform. But we could also see that there was a lot of ambiguity in the mind of the spenders also in that period. Now those things are getting streamlined to some degree and may happen more in Q1 as tariffs eventually take into action. Then probably there could be an opportunity of pent-up demand coming starting from Q2, Q3 onwards.
There is also one very big trend on the Gen-AI side where the adoption is coming closer on, the timeline point of view, which itself could also be another round of trigger for tier I vendors to begin with in India. Those are the two triggers pending and whether they happen after Q1 or later in the year, is something that we need to work on. So far with the expectation coming into play, so far giving the opportunity that is available to us, we are in the bottom part and we would only see things improving here on.
What is your sense on how much the AI disruption is already in the price or how much of it is yet to be seen because it is such an evolving landscape out there?
Rahul Jain: It is very difficult to measure it in a very precise manner, but going by the past cycle of various technology trends that has always been perceived as a risk to the sector. So we have seen that when there was too much talk around blockchain in digital or many other technology trends in the early stage of adoption, there are a lot of boutique companies which play roles which are very tech savvy, very individual led, smaller setup, doing pilots for a lot of companies.
But once these global enterprises decide that they need a mass rollout, and scale this technology enterprise wide, then their key support vendors are the same top 10 companies. So, when the mass deployment of those technologies has to happen, they eventually rely on the likes of Accenture, TCS, Infosys, and the like. I think that is what will happen with AI also eventually. Are we six months away from that trend? Are we one-year away from the trend? We do not know. But the smartest people on the AI side talk about how we will see mega adoption within 12 to 24 months. Some of that early trend could happen in the next six months and it may scale up 18 months from now based on those understanding, but it is very difficult for any one of us to single out that this is when there will be a big shift.
Even when we are talking about the entire outperformance in the Nifty IT space, there is one basket in particular that is midcap IT which has outperformed the overall basket. Do you still see valuation comfort over here? If you had to place your bets in the entire IT space, would the midcaps be making it to your radar?
Rahul Jain: The whole logic of why IT midcap has been doing so well for so long over tier I names is the sheer difference in the growth rate of these companies and these companies are growing anywhere between 12% and 18% on organic basis and in some cases, there is inorganic element as well.
While the largecaps are at a very reasonable valuation, their growth in the last three-five years except for one year in between because of Covid – their 10-year CAGR – is in that high single to mid-single digit basis. So, for a lot of companies, the filtration of investment would only come if the growth can compound in early double digits at least and that is the reason people are seeing more value in stories that can become large and can grow faster.
So, the likes of Persistent, Coforce, KPITs – which are reasonable in terms of size with close to $500 million to $2 billion revenue band, are behaving like larger midcaps. They are not midcap or tier II as such, they are good in size on their own and where there is a lot of money can be deployed. So, those are the areas where people are parking money because of the growth rate differential.
Over a period of time, once the growth differential is also narrow, the valuation differential will narrow as well. That is something we are waiting for. Once we see a better IT cycle, the growth differential will narrow. In a troubled environment that we have seen in the last two, two-and-a-half years, companies with much higher execution and much smaller size become an advantage and that is what we have seen in some companies. While a largecap does take a hit because of the macro spending factors, that explains why that differentiation has happened.
Would you elaborate on that? What is your pecking order in terms of your preferred list from within it?
Rahul Jain: There are three-four names which we like and these have a lot of short-term as well as long-term reasoning behind. Within the larger caps, we like LTIM. Here the order book growth has been decent on the closing basis of FY25 and a CEO change can probably bring in some kind of stability on the top layer which has seen some attrition in the last 12-18 months. That is something which we like and the companies historically pre-Covid also have been doing better in terms of growth versus the tier I peers.
So, it is where a large business which can do well and is reporting below its potential for the last two-three years, has good potential to do better from here on. So, that is one largecap name that we like. We also like HCL Tech given its consistent, decent confident outlook for this year and we also see potential for Infosys to gradually scale up its guidance later in the year.
These are the two-three names that we like in the tier I pack. Other largecap companies we like less. On the midcap side, some of the good businesses are very expensively priced. So, leaving those aside, right now we like Mphasis, KPIT, eClerx. These are some of the companies where growth versus valuation provides an opportunity to make money even from this point. So, these are the names that we are liking within the mid-tier to smallcap.
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