Deloitte South Asia Chief Operating Officer Nitin Kini has downplayed concerns that Artificial Intelligence (AI) will lead to widespread job losses, emphasizing that the firm’s strategy is centered on upskilling employees to address more complex business challenges. In an interaction with PTI, Kini highlighted Deloitte’s plan to hire 50,000 professionals across India, with a strong focus on training talent in emerging technologies. He underscored that AI is being used to unlock efficiencies rather than replace jobs.
Upskilling at Scale: Training 30,000 Employees in AI
Deloitte has already trained nearly 30,000 employees in AI, while an additional 20,000 are being transitioned to work on the company’s in-house platforms. India currently accounts for nearly one-third of Deloitte’s global workforce, highlighting its strategic significance.
Kini also revealed plans to establish a Quantum Centre of Excellence, signaling increased investment in advanced technologies. He noted that Deloitte invests approximately 9 per cent of its revenue toward innovation, capability development, and expansion initiatives.
India’s Strategic Role in Deloitte’s Global Workforce
On challenges in AI adoption, Kini cited concerns related to data security and costs, particularly among public sector enterprises and large conglomerates. He added that India should position itself as both an “AI factory” and a “cyber shield,” balancing rapid technological advancement with robust safeguards.
Deloitte has outlined plans to hire 50,000 professionals in India as part of its expansion strategy, with a strong focus on Artificial Intelligence (AI) and emerging technologies, according to multiple publications, including Moneycontrol, News18, and People Matters, which reported the development on April 2, 2026.
Transcript of the COO’s Interaction with PTI
— Edited excerpts from the video interview published on March 30, 2026 —
Nitin: So ... I think a good perspective. And if I may say, how are we thinking about this? All of the infra needs to be protected at multiple layers, right? I mean, so whether it is, let's say, at the hardware layer, the network layer, the application layer, of course, the identity management, and all of that. So from that point of view, what we've done is—I mean, you would have seen our launch of the Connect Safe Lab—this lab actually allows for how we actually secure the security posture at all of these levels. Of course, we are covering multiple industries, whether it is from a manufacturing point of view, of course, like you mentioned, but also whether it is, let's say, medical devices or building technologies, connected vehicles, for example. So across all of these industries as well, and similarly across the journey that clients need to take, which means, let's say, for example, whether it is to do with trainings, whether it is to do with architectural reviews, if it is to do with hardware-related or, I mean, you know, the OT technology review, all the way up to building a SOC. So our approach to this to help Indian manufacturers is multi-pronged in that sense.
Interviewer: Nitin, India has been a hub of pilots for the last year. But a concerning majority of these AI and IoT projects never reach the production stage. What is the missing puzzle piece that you see for moving Indian PSUs and conglomerates past the proof of concept stage without them hitting the wall of exaggerated costs and integration hell?
Nitin: Good point again. And I realize you are talking about all the stuff that's happening around AI, GenAI, agentic... I look at it in three parts, if you see. I mean, you know, one of the things is about downside protection. I mean, you know, even beyond sovereign AI, companies want to ensure that their data, which is essentially IP, does not leave their perimeter. So which means how can, despite you using LLMs, etc., can you secure your data within your perimeter?
The second thing, I mean, you know, generally people ask for is: how do I scale with confidence that I'm not going to end up with a bill shock? Which essentially means that can we not necessarily use paid models where every token counts? So the dichotomy that people are trying to navigate is to ensure that we don't have to choose between democratizing this AI, GenAI, agentic, where everybody uses it, and therefore you're unlocking the whole enterprise, but you're not then having to worry about doing this at the cost of not being able to control the number of tokens, and therefore you could be in for a shock.
The third thing that people essentially want again is: you see that people are actually having a current install base. AI cannot suddenly come and say, or AI, GenAI, agentic cannot come and say that I'll be a parallel system. People have to mimic the way organizations work, and these have to actually interact very well with the existing tech estate.
So our own approach to the recently launched GenW.ai addresses all of these. So that, I mean, you know, when organizations actually want to secure their data, to be able to ensure that they don't have a bill shock so they can scale with confidence, that interacts with, I mean, their existing tech estate, we are covering all of these.
Interviewer: Nitin, in an era where fear of job losses looms large, Deloitte has announced its plan to hire 50,000 professionals across India. Do we see this as a muscle play or a brain play? Are you hiring 50,000 freshers to do manual SOC work, or are they here for a specific tier of senior AI architects who can actually outcode the bots?
Nitin: Good question again. I know in the context of AI, GenAI, etc., people always think saying that are we going to disintermediate some layer? Well, that's not how we think. I mean, you know, we always think that there are efficiencies that are going to get unlocked across the layer.
We have had the opportunity to train almost 30,000 of our people, I mean, you know, on AI, 20,000 people on the way we are changing our gears to work with a lot more inbuilt, I mean, in-house built platforms, I mean, you know, technologies, etc. So we are upskilling folks. And the way I think is, in this era of, I mean, you know, new tech coming into play, you will have people who will be involved in multiple things.
One is, of course, I mean, you know, people have to keep the lights on while the change happens. Second is we'll have people who will be helping our clients negotiate the journey of AI, GenAI, etc. Third is, of course, I mean, you know, problems that could have previously not been solved because, I mean, you know, people were otherwise stuck in the mundane, or the processing power wasn't there, or the kind of intelligence wasn't available at a fingertip or at a price point. With all of this coming together, there are new problems that become available to be solved, I mean, you know, the potential to be solved. So I do believe that—I don't think job losses really is the way. It is about upskilling and making sure that, I mean, you know, we can solve higher order of value problems, I mean, you know, with the emerging tech. So that's how I see it.
Interviewer: And what is the timeline for this hiring plan, and what roles and skill sets are you looking towards?
Nitin: Of course, I mean, the skills will be quite...it is not one skill or another, but broadly if I were to say, there are advisory skills, there are technology implementation skills, there are business process management skills which consume these technologies and change the way people work. So beyond grunt work. So we do expect to hire similar profiles that we have hired in the past across levels, but of course, we will upskill folks so that, I mean, you know, people can work in the new ways of working which today may not necessarily be right out of the box from a college, but I mean, that mantle we are owning.
Interviewer: Nitin, for India as a market for Deloitte, does the country rank in your priority markets, and what kind of investments and expansion plans can we expect from Deloitte in India?
Nitin: Well, that's a question for my CEO, but I mean, I would say at a very broad level, the way we are pursuing multiple, I mean, you know, pillars, I think India is home to almost a third of Deloitte's professionals globally. So in that sense, priority-wise, I presume very high up in the order. And if you were to say what kind of investments, etc., I mean, I can boldly say we are top tier in that sense. I think we've been consistently investing 9% on capability building, capacity building, on innovation, etc. So in that sense, 9% of top line consistently over the years is what brings us to the tip of spear being able to, I mean, you know, work on... and this is not money spent for the sake of spending money, right? I mean, you see we have a center of innovation and technology in Bangalore, now a new Connect Safe Lab that helps people, I mean, you know, secure their infra. We're coming up with a quantum COE very soon, and similarly, I mean, you know, how the future of government should, I mean, look like, so there is a lab coming up for that.
The entire intent is, I mean, you know, a little bit of a higher order of purpose kind of an intent, which means how do we create jobs in India? If AI were to disrupt, let's say, services jobs, how do we actually become more efficient as a country on manufacturing? So that is of interest to us. So like that, there are several topics of interest for us which of course, I mean, you know, is commercially viable but is also of national importance. So if I may say, I mean, you know, so these are all the areas which actually drive our growth and therefore our investment, and that connects then back to the kind of people that we want to hire, etc. So in that sense, I mean, you know, I would say that's the 360 of it.
Interviewer: Nitin, despite the focus and push on innovation by the Government of India, the country still stuck at 0.64% of GDP when it comes to spending on R&D. Is our digital sovereignty just a buzzword if we are still relying on global LLMs? Can India truly be a Vishwaguru, as we say it, in tech if the private sector continues to underinvest in core research?
Nitin: I think many questions bundled into one, so let me unravel the way I see it. 0.65% is probably not because people don't want to spend. I think we need to work on, I mean, you know, how do we up our total factor productivity? I mean, you know, so that's how I look at it.
So which means, let's say, for example, one of the problems we would love to solve is how do you, let's say, for example, squeeze value out of the logistics costs that the country spends on, right? I mean, and therefore, I mean, the manufacturers, etc., spend on. Because every 1% reduction there probably, I mean, you know, a significant portion of that can add to the R&D spend, right? I mean, why we are committed to this purpose? Because, I mean, it comes from a deep sense of the fact that India should capture value, and you rightly pointed out saying that, I mean, you know, R&D and of course, brands, these are the ones that actually capture value. So in that sense, this is an agenda that we would like to commit to. How do we commit to that? I mean, can you use, let's say, quantum or quantum-inspired algorithms to, I mean, you know, better do scheduling or better do your logistics, etc.? So from that point of view, I think the money saved there will create the space for people to spend on R&D, etc. So I don't think it's for want of intent; it is that as the physical infrastructure is getting built by the government, how do we help, I mean, you know, leverage that and unlock efficiencies that otherwise couldn't have been accessed.
Interviewer: Nitin, extending a little bit more on digital sovereignty, how is Deloitte navigating the dual-cloud reality that is maintaining global efficiency in terms with the global major players while satisfying the Indian government's need to have localized sovereign data clouds?
Nitin: Well, I mean, again, I know I missed answering a part of your previous question, and I think it dovetails into this one as well. If you see, for example, GenW.ai works with Sarvam as well, so we tested the integration, whether it works. So which means in that sense, it's a very Indian model; we love it. Apart from that, do we have the ability for our platforms, let's say, for example, things that Deloitte builds, can it reside in-country? Answer is yes.
I think we have lot of alliance partners who are putting up infra in-country, I mean, you know, so it lends itself to that. But also if, let's say, for example, our clients are pursuing on-prem, I mean, you know, their own data centers, etc., so some of the platforms we're building actually lend themselves to being hosted on-prem as well. So it is not just about on-cloud and therefore within country, but it could even be within the perimeter of an organization because we would love to cater to, say, PSUs or defense or somebody who says I want it in my air-gapped network. It has to lend itself to that as well. So it's a multi-pronged strategy to make sure that horses for courses, everybody can get these platforms exactly in the configuration and in the hosting environment that they would like.
Interviewer: Nitin, before we wrap up, if you had to choose between India becoming the AI factory of the world or the cyber shield of the world, which one provides a more long-term economic sovereignty perspective, and where is Deloitte placing its biggest bet and how?
Nitin: It's like you're asking me to choose between the accelerator and the brake, right? I mean, I would say let's be greedy and want them both. And I would always say, I mean, you know, a great car with a great engine with all the security features, with I mean, you know, keeping you safe—I think we want it all. I think we have the same kind of aspiration that Young India has, and the way the government is preparing for it. I mean, so in that sense, yeah, I mean, 'Dil Maange More,' if I may say.
