Red Hat Summit 2026 | Sumit Kapoor & Kowdinya Dharmavarapu, HCLTech

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Kowdinya Dharmavarapu

VP & Global Head, IBM & Red Hat Ecosystem

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Sumit Kapoor

Associate Vice President & Global Head IBM&RedHat Ecosystem GTM

HCLTech

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Sumit Kapoor & Kowdinya Dharmavarapu, HCLTech

Kowdinya Dharmavarapu

VP & Global Head, IBM & Red Hat Ecosystem HCLTech

SK

Sumit Kapoor

Associate Vice President & Global Head IBM&RedHat Ecosystem GTM HCLTech

In this interview from Red Hat Summit 2026, Sumit Kapoor, associate vice president and global head of IBM and Red Hat ecosystem GTM of HCL Technologies, joins Kowdinya Dharmavarapu, vice president and global head of IBM and Red Hat ecosystem of HCL Technologies, to talk with theCUBE's Rob Strechay and Rebecca Knight about how enterprises can bridge the gap between AI experimentation and full-scale production. Dharmavarapu frames the current moment as the fourth major tectonic shift in technology history — following the mainframe, client-server and internet er... Read more

explore Keep Exploring

How does open source fit into your AI strategy, how do you address vendor lock‑in and enterprise deployment challenges, and what role does the HCLTech–Red Hat partnership play? add

What real-world use cases of the HCLTech–Red Hat collaboration have shown the most traction in helping customers make their solutions repeatable, scalable, and secure? add

How do HCLTech and Red Hat address concerns about AI sovereignty, provenance, trust, governance, and end-to-end control over models and data for enterprises? add

Over the next one to two years, what will separate organizations that succeed with AI from those that fail to capitalize on it? add

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Sumit Kapoor & Kowdinya Dharmavarapu, HCLTech

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Rebecca Knight

>> Good afternoon, everyone, and welcome back to theCUBE's live coverage of the Red Hat Summit here in Atlanta, Georgia. I'm your host, Rebecca Knight, alongside Rob Strechay. Rob, companies are now experimenting with AI, but they really want to see their, as you say, ROAI.

Rob Strechay

>> Exactly. They have to be able to see the return on AI, and that's a lot of where the rubber meets the road, as we were talking about earlier.

Rebecca Knight

>> Indeed. And here to talk more about that, we have two fantastic guests, Kowdinya Dharmavarapu, GP and Global Head - IBM and Red Hat Ecosystem, HCLTech. Welcome, DK.

Kowdinya Dharmavarapu

>> Thanks, Rebecca.

Rebecca Knight

>> And Sumit Kapoor, Associate Vice President and Global Head - IBM and Red Hat Ecosystem, GTM at HCLTech. Thank you so much.

>> Thank you. Thank you for having us here.

Rebecca Knight

>> Those are very long titles, but it shows how important you are. So DK, you are at the center of the HCLTech AI ecosystem. Why don't you start the conversation by talking a little bit about what you are hearing from customers right now in terms of where their head is atn terms of experimenting with AI and where they're thinking about right now.

Kowdinya Dharmavarapu

>> Oh, sure, Rebecca. Thanks. Thanks a lot for that interview. See, we have passed that phase in the whole IT environment from where having if to be having is a must. It's an essential part of an organization, an enterprise way of looking the business. That's the technic shift we are going through. As I was today attending a couple of sessions, there's one important element caught my attention. Every 20 years we are seeing a major transformational changes in the world in the technology industry. And we started with the mainframe type of environment, to client server, to the internet hyperscalers coming in. This is the most phenomenal shift like an industry organization, what we are all absorbing actually. It's become essential part of the organization's growth strategy. That's a big change we are seeing. As we try to look at, the initial conversation is all about experimentation, pilots. Today we changed. Organizations are coming back and asking us that, "How do you help us to scale? How do we reap the best of the benefits from this whole environment you are speaking?" And it's all moving at a space where initially we thought models are the complexity. But if you've seen in the last 12 months, the models are not the complexities, models are mature. Models are really, really sophisticated. The complete element around the models is where the challenge lies for us to help the clients through this transformation journey, the data part of it, the platforms part of it, the governance part of it. And how do you ensure that this whole models gets embedded into the organization's business systems action? So we are now moving from a change of pilots towards a scale type of environment. That's a big tectonic shift. And as today, one of the analysts was mentioning, as the shift happens, the people who adopt and trying to have the best competitive advantage will able to survive this whole tectonic shift. So it's becoming essential as a corporate, both decisions actually. The second element is that from an experimentation as we visualize, it all has become ... It's a combination of three vectors, vector of open source, vectors of hybrid cloud, and vectors of ecosystem. That's where this whole integrated approach needs to come in because we are now moving from pilots to scale. Scale is all about partnership. Scale requires you need to bring hyperscalers, you have to bring traditional software vendors, you have to build a huge amount of ecosystems to make it happen so that it helps the clients to achieve their set of goals. Hence, it is so important we are moving from pilots to scale. That's what we are observing, Rebecca.

Rob Strechay

>> Yeah. And Sumit, when you look at this, because I was just having this conversation at lunch with a very large telco, and one of the things that they said is, hey, the path we had been going down was very interesting, but wasn't as open as now my seeing of what is going on with their AI deployments and things. How do you see the coming together of AI and open source, and how are you helping with that as well?

>> Oh, absolutely. Thanks. Thanks for this question. And this is very interesting. To be honest, open source is something which is extremely important for the clients for faster innovation. And at the same time, how do they avoid the vendor lock-in? You'd ask, why does it, the generate, why does it really go with the faster innovation? This is something we're in. Because all of this is community-driven, but when something is community-driven, for the clients to adopt, scale, and deploy, it needs to be harder and it needs to be supported. It needs to be all the ringfencing to be done if it is to be deployed at an enterprise level. Now, this is where at HCLTech and Red Hat come together. And if you look at the number of services and the solutions which we have on our entire AI strategy, we have our AI strategy carved into multiple buckets. First definitely happens on the services which we have here, and we are transforming our own services, and that's where we also help clients in terms of transforming their services, putting AI right at the forefront of everything that we do. Second is a number of AI products and the IPs which we have created, whether it's around SDLC or ITOps, or even the industry solutions. Third is the new set of AI services which we are creating or created on with the physical AI, with the stuff which we are doing on Sovereign, AI Factory, and also the AI Advisory. And this is where we're building a lot of partnerships, and Red Hat plays a very critical role in this entire ecosystem. So if you look at this offering, we have AI Factory, which is based on Red Hat Enterprise AI. We have AI Force, which is a service transformation piece based on Red Hat OpenShift and SmartPaaS, which is on OpenShift Virtualization. So all these come together to really drive the value for the clients.

Kowdinya Dharmavarapu

>> Sorry. It's an integrated model, if you'll see. It's a weaving of multiple elements of value transformation, service transformation, and then how you get the data model pipes integrated? The bigger challenge, if you'll see, is that how we can get it agentic in nature. It means that, how do we get a flow from all these things, the data gets connected so you'll have a better way of the agentic environment running.

Rob Strechay

>> So just to kind of ... For both of you. This question's for both of you, because I'm rattling around in the back of my mind and I'm asking a couple people this, is really around, do you start with the existing process or do you look to change the process to fit the technology as you go through? What's your advice to people who are just getting started on their journey here and are looking at, "Hey, I want to take this process and I want to make it agentic now"?

Kowdinya Dharmavarapu

>> You want to take it, Sumit? You should do it.

>> Yeah, sure. See, when we look at customers today, they're moving the stage of experimentation. We want to really take them from moving beyond experimentation to the production grade. Now, how do we do that? All of this happens through a very ... All the services I spoke about, you look at the service transformation, you look at the agentic services that we have, and Red Hat plays a very, very crucial role when it comes to creating these offerings.

Rob Strechay

>> So they're leveraging your experience in these different processes to be able to help them shortcut that whole ideation?

Kowdinya Dharmavarapu

>> Valid point you brought up. It's so important. AI shouldn't become an isolated environment. It should become part of your existing systems, processes, and business models. It's so important. If not, what will happen is that we will still navigate towards a pilot, we'll never become an enterprise scale. What clients are asking is that, how do you help us to bring this whole AI story, GenAI story, part of my business processes so that it starts building value for the organization? And it means that you have the models, how do you get the models more efficient? How do you get the enterprise connected? That's very, very important. That's why your point is very important. Then the other is a unified AI platform, and how do you get an inferencing which will be more pragmatic in the existing systems? So it's so important that we have to ensure that the AI part of the story becomes part of your existing systems to derive the maximum value and return on investment and benefit to the client, actually.

Rebecca Knight

>> And that might mean rethinking your old KPIs and your old metrics, because they might no longer apply to what you're trying to do. So in terms of the HCLTech and Red Hat collaboration, as you've said, the goal is to help customers make it repeatable, scalable, and secure. Do you want to talk a little bit about some real world use cases where you've seen the most traction in terms of making this work?

Kowdinya Dharmavarapu

>> Sumit, it's your area. Jump in.

>> Right. I'm glad you touched upon the HCL and Red Hat partnership. So when we look at HCL-Red Hat partnership, this goes back to long back and HCLTech happens to be a premier partner of Red Hat, which happens to their top lever of partnership. We have over 20,000 resources that are skilled on Red Hat, which is a unique feat in itself. In addition, just to add, there are over 200 clients which we support on Red Hat technologies. And as I said earlier, we are moving a lot of customers from experimentation to AI, and the areas that we are looking at, we are looking at the IT operations, wherein the Ansible from Red Hat comes into picture. We are looking at a lot of customers which are looking at OpenShift Virtualization, the Hypervisor exit or Hypervisor strategy. That's where OpenShift Virtualization is playing a great role. And we have our expertise which we are driving with the clients. And then definitely the hybrid platform, which really makes it kind of a foolproof solution for customers who run it on-prem as well as on the hyperscalers. And I think we heard it this morning also during the keynote, how the clients are able to take it from on-prem to cloud and run both together at the same time. So that's where our collaboration with Red Hat is really helping us out.

Kowdinya Dharmavarapu

>> And adding to Sumit, the other important element from a Red Hat perspective is that we built a deep competency, capability, capacity around the Red Hat as an environment for us. So what it brought to us was our ability quickly adopt Red Hat OpenShift AI or Ansible part of it into our core AI strategy as partner. And what is a benefit for it? As we went to, for example, went to Euro, we realized the clients are asking for sovereign stuff. And what is happening with whatever Red Hat is announcing now is going to become a core part of what we are going to do in Europe with the sovereign part of it, because some of our large manufacturing clients, automobile clients, this is what they're asking. Now, when I see what Red Hat is trying to do, it closely aligns to our strategy of helping the clients through journey. And if you're trying to look at how you're helping in the North America once again, same scenario comes across in BFSA vertical or you take LSH1 where we have done the journeys of taking the clients through the hybrid cloud with Kubernetes and OpenShift. So we have strong layers got created, and that is going to move towards the AI plus automation plus open source. This whole combination is what we are going to offer to this client section. I think it's one of the most compelling transformative technology change from Red Hat with us into our scheme of things actually.

Rob Strechay

>> So how does that play with organizations around the world, not even just ... The sovereignty is a big thing in Europe, and I think it's coming to the US, by the way, and not just because of regulation and stuff like that, because sovereignty doesn't necessarily mean where. It means understanding provenance and things of that nature around AI. And AI sovereignty, I think is going to be a big thing for companies to worry about, not just sovereignty in general from the country level. But one of the things that comes along with sovereignty is trust, and really, trust and being able to be reliable. How do you see this playing into what HCLTech and Red Hat are bringing to the table?

Kowdinya Dharmavarapu

>> I'll start and I think you're going to add, Sumit. I think it's a very important point. As we went through this journey in the last 18 months, it's very interesting element we have seen with the clients. That's where we built these guardrails. We create a chief trust and compliance officer for this situation at HCLTechnologies. And our IBM and Red Hat ecosystem, the Red Hat ecosystem, it's really led this whole thing from the front where we launched responsible AI. So you need to have a governance, a guardrails, and structure which builds and breeds a lot of trust, integrity, and compliance onto that one. So that becomes another important element of what is the difference between the regular open source AI models and Red Hat. The open source community helps us to build a huge amount of capabilities, but the big difference we will get is when an organization like Red Hat comes into, is that we're able to build these whole structures around it. That's a quite defining moment, defining structure when you go back to the top Fortune 500 clients actually. And so it's very, very important. We are at the front of it. We went through a good amount of consultative approaches with various Fortune 500 clients. Now, once again I'm saying they're also going to move from pilots to scale, and we are at the right time at this moment actually. Sumit, you want to add?

>> Yeah, and just to add, I think very well said, but I think sovereignty as we see it and based on our engagements with the clients, we are also looking at, it's not only about the data or staying to a local level. It's all about whether you have your sovereign control over end-to-end stuff at across all the layers. So it's not only your data, but most importantly about your models. And that's where I think our partnership with Red Hat comes in and how we are able to run those models, providing the full control over their models and data and everything to the clients.

Rebecca Knight

>> Final question. When you look out over the next year to two to two years, what is it that will separate the companies, the organizations that win on AI from those who are just not capitalizing? Want to go first?

Kowdinya Dharmavarapu

>> It's a very, very important point. As I said, it's like an industrial revolution, what we are going through. This is the fourth big tectonical shift in the technology industry is going. Where the most important things as the clients adapt to it, how do we industrialize this whole AI adoption becomes the most important thing? The adoption at an industry level and scale will differentiate the human mankind itself, because it's going to improve the services back to the citizens, back to the clients, back to the way of doing business actually. So you're going to see a lot of industriation to build a scale is going to happen on this AI part of the story. At the same time, you will see clients coming in demanding at the same time, the earlier discussion we had about the sovereign part of the story and the security considerations around this whole model actually. Sumit?

>> No, I think you said it already.

Rebecca Knight

>> Excellent. Sumit and DK, thank you both so much for joining us. A great conversation.

>> Thank you, it's our pleasure.

Kowdinya Dharmavarapu

>> Thanks a lot. I appreciate the opportunity.

Rebecca Knight

>> I'm Rebecca Knight for Rob Strechay. Stay tuned for more of theCUBE's live coverage of the Red Hat Summit. You're watching theCUBE, the leader in enterprise tech news and analysis.