Phil Fersht — CEO, HFS Research[00:11]
You and me, good to catch up again. Let’s just jump straight into the matter of, you know, the flavor of the year supposedly, which is GenAI and AI in general. Is this something you think we should be enthusiastic or scared about? What’s your real deep view on this?
Nitin Rakesh — CEO and Executive Director[00:31]
Morning, Phil. Thanks for having me. It’s a double-edged sword, right? Like all new disruptive tech, this is definitely something that you have to be excited about. And at the same time, if you’re not acting with urgency — either as a business owner, enterprise, tech company — you have to be scared of it as well, because it definitely has the potential of reshaping, rewiring, and resetting the way we think about a lot of things that we do in business today, not unlike a lot of other disruptive tech, you know, inflection moments that came about in the last 30, 40 years as well. So I think it’s an exciting time, but it’s also a scary time if you’re not taking action around it.
Phil Fersht — CEO, HFS Research[01:17]
How would you think then, with a lot of the developments we’ve seen in GenAI for example, how do you see the value for the enterprise as we start to evaluate how they really exploit these technologies?
Nitin Rakesh — CEO and Executive Director[01:17]
I think, firstly, AI is something that has been in the works for the better part of the last 50 years, maybe even longer. So this isn’t something that crept up on us with no notice, no warning. I think this is a congruence of many things that have been under development, from compute power to availability of large data sets to, in general, the ability to start throwing a lot of resources at solving these problems. So to me, I think we are undergoing a pretty significant enterprise pivot across pretty much every business line, where if you play this right, you have the opportunity and the potential to take a very large chunk of productivity back into the business. Now that doesn’t mean that you don’t have to work for it, or align a lot of your resources to be able to harness the power of this tech, but at a very high level, I think this is definitely something that will have a much bigger impact from a productivity standpoint. And by definition that means that we’ll see a reshaping of a lot of things as they’re done today — skill sets, jobs, you know, people who do manual operations, even software engineers. Almost every aspect of the value chain has the potential to adopt AI and really do things in a different manner.
Phil Fersht — CEO, HFS Research[02:46]
So if we look at a year from now, what do you expect from GenAI in terms of reaching any type of scale, and further advancements or breakthroughs that you’re anticipating that are going to change this as well? And finally, what do you think may have disappointed us if we look back in a year?
Nitin Rakesh — CEO and Executive Director[03:20]
So I think, Phil, we have to play the long game here. It’s very hard to pinpoint what happens in 12 months or 18 months, but I think this is the start of a major journey. Democratization of AI is probably the biggest theme of 2023. But let’s also not forget that, as human beings, we tend to overestimate the impact of tech in the short run and underestimate in the long run, right? That’s Amara’s law. I think, as much as the impact is visible, it will take time for enterprises to set up the data pipelines, have clean availability of data, have model-management platforms. And by the way, do it in a manner that is traceable, secure, ethical. So I think this is the start of a journey. While we’re excited about it, this isn’t something that will reshape and rewind the world in 2024, but definitely every year you will see the impact play out in some part of the enterprise or another.
Phil Fersht — CEO, HFS Research[03:59]
So, you know, the conversations you’re having with your clients and other folks in the industry, what are they overly concerned about, and what are they not concerned enough about?
Nitin Rakesh — CEO and Executive Director[04:29]
I think everyone’s in a discovery kind of phase right now, and the good news is that this is now a board conversation topic. So almost every enterprise has a point of view on what they’ve taken back to the board and the exec team, and this is being driven really top down. I think the general consensus seems to be, let’s find at least two or three really large impact areas versus doing small pilots and proofs of concept. Of course, a lot of our clients have been doing that for the last few months. So the first instinct always was, this isn’t secure, you know, we don’t want ChatGPT to get access to our data. So I think security is probably the number one concern, both in terms of security of data as well as privacy concerns, because remember a lot of industries are highly regulated — banking, healthcare, insurance. I think there’s a fair degree of focus right now on making sure that the infrastructure is available. You know, the answer isn’t to start setting up private stacks in every enterprise, and you just lose the power of something that is highly scalable. So I think the next 6 to 12 months, the focus really will be all on making sure we have the right infrastructure in place, we have the right pipelines in place, we have the right relationships in place with the right providers of this capability. Then of course there is this open debate around, do I really want to use a public LLM, or should we start thinking about industry-specific LLMs, right? Banking should have its own LLM, insurance should have its own LLM. So I think that debate will go on for a while until the right answer emerges, and the right answer will probably be somewhere in the middle. And I think finally, the ability to really start re-skilling people is probably the other third big area that every enterprise is talking about. I mean, if you really think about the debate between AI replacing jobs, I think where the consensus is now narrowing down to is, it’s not that AI will replace humans, it’ll replace humans who don’t use AI. So let’s just reskill our people and make sure that they understand how to use this technology. This is still early days, and I think if you just stay forward leaning and make sure that you’re finding the right application areas without getting very focused on small use cases, I think ’24 will be a very exciting year.
Phil Fersht — CEO, HFS Research[06:53]
OK, so a broader perspective and not just tinkering at the edges. Interesting. So in terms of your own business, how fast do you feel you have to move, particularly in the services industry, with skilling up and reskilling a lot of your people? And, you know, can you share some insights on how you’re doing it?
Nitin Rakesh — CEO and Executive Director[07:17]
I think we’re taking a very forward leaning approach. We are being very bold, and as you know, business is always relative. We have to be faster than the next guy, and hence I think agility and the ability to construct solutions fast is something that we’re really, really focused on. I think the other thing to keep in mind is, we have seen these kinds of pivots before. Of course this is a much bigger one, but whether it was adoption of all things public cloud, like virtualization of applications — effectively the bet we made in 2016-2017 was that the data center of the future will be an empty room, and again, you know, we’ve seen the impact of that in the last five, six years. We’re taking a very similar approach here in terms of really forward focusing on how we can solve more complex problems that accelerate the entire tech transformation agenda for a number of enterprises, because they’re dealing with a plethora of legacy issues. This is not RPA. This is really super turbo boosting a lot of manual operations that happen in the back office.
Phil Fersht — CEO, HFS Research[08:00]
As we look at it, the broader society, how things are impacted, and the arms races with who’s going to take the lead here. Obviously India’s been incredible in terms of building up such a hotbed of tech talent over the last 30 years or so. How is this going to impact India? Do you think that this will further accelerate development, or do you think there’s going to be some period of rebalancing as other providers, other countries, may try and get ahead with tech development here?
Nitin Rakesh — CEO and Executive Director[08:55]
Coming to India, I think we’re probably one of the best placed, both in terms of our local economy and, more importantly, in our ability to actually really create a large pool of talent almost in any new skill that is required. Primarily because of the way we’ve embedded this industry, our industry, into the educational ecosystem from an engineering and design standpoint. So I think the grassroot foundation level, in connection with our industry, is very strong. We have the ability to start creating large pools of talent. We’ve seen that before. We’ve seen that around Y2K, we’ve seen that with digital, we’ve seen that with cloud, we’ve seen that of course with IT operations, we’ve seen that with business process operations. So I think, as long as we are very clear as to where those large application areas are, and how do we make sure that we are able to align solutions to skills, I think you’ll see three or five years from now we’ll probably have the largest AI workforce on the planet.
Phil Fersht — CEO, HFS Research[10:05]
Well, on that note, largest AI workforce coming from India, that’s tremendous. This has been awesome, I really enjoyed a lot of your insights — humans under threat from AI, and those not doing AI, I’ll take that away very much. And the way industries are evolving, we’ve just got to keep moving forward. So I really appreciate your time. I look forward to sharing this with everyone.
