How have client priorities evolved when it comes to technology and AI?

They are more thoughtful of their landing zones, what stays on-premise, what goes to one cloud, considering what’s happening around concentration risk of big hyperscalers, sovereignty and protection of assets within a market, and what’s fuelled by AI. I find clients to be more thoughtful now versus just saying the answer is public cloud. Clients actually think through their app estate, landing zones and design it correctly, get faster acceleration on both their hybrid cloud journeys and their AI journeys. So, I find that’s changed since the 2018-19 timeframe.

Everyone wants to go sovereign. How does it impact the idea of putting your data on cloud? Are there valid concerns of data being geopolitically gated?

I find sovereignty to be a highly overloaded domain. I want to break it up a little bit. I think of sovereignty as a design choice. Everything around data governance — data privacy, data sovereignty, is it within region. The biggest question clients ask is: can you not access the client data? So, enable clients to load their key encryptions so that IBM can never access that data. There’s also operational sovereignty — do you have local citizens managing the data? The third is technological sovereignty: Are you building on open technologies? Are you building on things that are portable and doesn’t lock you down against concentration risk? If I pick a particular hyperscaler, can I get out? With hybrid cloud platform, if a client chose our cloud today and another tomorrow, day after, they have the portability choice.

What I advise clients is make sure you have control over data, operational aspects. Can you pinpoint who is accessing your services and where? Then build on an open portable platform. If you want a kill switch and not use our cloud, move it on-prem to your data centre, go at it. That’s why we’re so obsessed with open.

Do you see that understanding among the clients themselves?

It’s improving. it is not as pervasively known but some markets are more mature. India is getting there. in all the CIO conversations I had, it’s definitely a boardroom topic of sovereignty and what is your point of view. what is your sovereignty point of view. I encourage the industry to really break down the problem versus use the buzzword of sovereignty.

So, when you say they’re discussing it, are they trying to pick among the three pillars?

They’re trying to figure out where is their data, is it secure in market, who’s operating it, what kind of flexibility do they have with that data, who’s running it, is it with a local provider, what’s the supply chain. So, there are broader conversations, but they’re all trying to figure out their point of view. So, it is definitely a topic. Getting specific on details I think is important.

Indian companies are still lagging in the proof-of-concept to execution shift. What is the hurdle in that jump?

I definitely see AI taking off in certain clients. The differentiation factor of those clients who’ve made progress is a well-thought-out hybrid cloud strategy. Our CIO has a well-defined hybrid cloud platform. It is on-premise in their data centres. Thinking through infrastructure, data strategy, automation strategy – once you’ve done that, AI becomes easier. Then you apply AI to a specific problem or a domain. Focus on the basics of leading with the right architecture for hybrid cloud, and then applying it to a domain specific use case to get the acceleration of AI.

Where does India rank in the global market?

India is super innovative. The majority are thinking of cloud. AI is a little early but we’re investing heavily into India. India is right there among the top markets to get acceleration on AI. India as a market has had significant skill growth. The policies are fuelling the acceleration, which is why you’re seeing all the investments from all the global companies.

For a while,IBM prioritised hybrid cloud, Agentic AI and quantum. Are we going to see a merging of the technologies?

It as a continuum. We’ve invested heavily in the hybrid cloud software layer. We’ve also done extensive partnerships with AMD, with Nvidia, and with Intel. Since AI is shifting to more agentic, we see a combination of GPUs and CPUs being needed for you to fuel agentic. We’re primed for hybrid cloud and AI. On quantum specifically, we just announced a big investment in quantum fabs with the US government. We think of that as the next continuation of a domain called ‘Performance Intensive Workloads’. So, quantum is the next crank. We’ve got superior technology there and it’s an area we need to focus over the next few years.

How has that changed things for IBM itself?

I run an R&D engine. My team’s running a global scale cloud that makes a change every eight seconds, across 16 regions around the world. So, we’ve had to upskill in automation. We have built out an industry cloud. Our hyper focus is the service value proposition we provide to clients. What AI has enabled is upskilling on coding. My product management team is upskilling on using AI for requirements management, or competitive analysis, etc. Then in the design team, we are upskilling on user research, security and compliance. But that’s the fun. My team embraces the learning and AI is an accelerant to that learning.

How does that impact your team size?

We are expanding. We’re investing heavily in the regions across Chennai and Mumbai. So, we’re growing because we see enough double, triple-digit demand in the areas we do well. It comes down to not replacing, but productivity. The people who are productive are people who use AI to their benefit.