Debo Dutta, chief AI officer at Nutanix, and Jason Langone, senior director of global AI business development at Nutanix, join theCUBE’s John Furrier and Bob Laliberte at Nutanix .NEXT 2025 to unpack the company’s AI strategy. The conversation explores how Nutanix is approaching enterprise AI with a focus on governance, scalability and operational control.
Dutta and Langone share insights on top-down AI adoption and the need to untangle what they call “AI spaghetti.” They also explain Nutanix’s three-part framework: AI on Nutanix, AI in Nutanix and AI at Nutanix.
With infrastructure demands shifting rapidly, Dutta and Langone emphasize the importance of centralized AI platforms that empower teams without compromising agility. The interview offers a grounded look at how AI is being embedded across enterprise architecture.
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Debojyoti Dutta & Jason Langone, Nutanix
Debo Dutta, chief AI officer at Nutanix, and Jason Langone, senior director of global AI business development at Nutanix, join theCUBE��s John Furrier and Bob Laliberte at Nutanix .NEXT 2025 to unpack the company’s AI strategy. The conversation explores how Nutanix is approaching enterprise AI with a focus on governance, scalability and operational control.
Dutta and Langone share insights on top-down AI adoption and the need to untangle what they call “AI spaghetti.” They also explain Nutanix’s three-part framework: AI on Nutanix, AI in Nutanix and AI at Nutanix.
With infrastructure demands shifting rapidly, Dutta and Langone emphasize the importance of centralized AI platforms that empower teams without compromising agility. The interview offers a grounded look at how AI is being embedded across enterprise architecture.
Debo Dutta, chief AI officer at Nutanix, and Jason Langone, senior director of global AI business development at Nutanix, join theCUBE’s John Furrier and Bob Laliberte at Nutanix .NEXT 2025 to unpack the company’s AI strategy. The conversation explores how Nutanix is approaching enterprise AI with a focus on governance, scalability and operational control.
Dutta and Langone share insights on top-down AI adoption and the need to untangle what they call “AI spaghetti.” They also explain Nutanix’s three-part framework: AI on Nutanix, AI in Nutanix and AI ...Read more
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What is the approach to incorporating AI on Nutanix and how does it benefit the infrastructure and product improvement process?add
What is the value proposition statement for adding Nutanix Enterprise AI to an enterprise workload?add
>> Welcome back everyone, to theCUBE's live coverage in Washington DC for Nutanix NEXT 2025. I'm John Furrier, host of theCUBE with Bob Laliberte and Paul Nashawaty is out doing briefings, getting all the data for you here. Wall-to-wall coverage, about to go on to the live keynote on day one. Debo Dutta is here, Chief AI officer for Nutanix. Love the new position also in engineering side, we'll get into that. Jason Langoni, Senior Director of Global AI Business Development. Gentlemen, you guys are the AI czars of Nutanix. We were talking before we came on camera. The customer action is enthusiastic beyond recognition, the hype cycle's in, but there's a lot of action going on right now in the AI side. So welcome to theCUBE and thanks for sharing. What's on everyone's mind? Everyone's re-architecting and re-platforming, security. Everything's a do-over, right?
Debojyoti (Debo) Dutta
>> Yep. Actually, on that note, people are beginning to realize that they have to get into AI soon, yesterday. So they're trying to scramble, they're trying to do their POCs and figuring out how to bring that POC close to their private data.
Jason Langone
>> Yeah, I mean, I would add, and then how do we operationalize all this? That's great we stood up a capability in a lab, but now we got to turn it over to IT to care and feed and maintain for the next three to five, seven years.>> Yeah, I was kind of talking about the hype cycle, which by the way, it is. But all kidding aside, there's some real action going on and it's an exciting wave because there's infrastructure, I call it the middleware, which is cloud-native Kubernetes, and then the whole app cycle. Some are saying that the agentic wave will be either 10X to maybe 100X the size of SaaS in terms of valuation, but it's not yesterday's SaaS where you just build an app, put it in the cloud, put it in the app store. No, no, no, it's an engineering by default enterprise.
Debojyoti (Debo) Dutta
>> Yes.>> This is the difference.
Debojyoti (Debo) Dutta
>> It's a new architecture.>> It's a new architecture, everyone's rethinking it. So AI is forcing everyone to go, "Okay, what does our business look like?" That's what you guys are seeing right now. Do you agree with that? And what observations would you say is in that scope?
Debojyoti (Debo) Dutta
>> I think what we are seeing is a top-down movement. People at the top of the enterprise, they see the value of AI this time around because AI is not new, it's been there for many decades. But there is this amazing thing about the current wave of AI where you can actually get some productivity improvements with AI. So now when you go top-down, you have to figure out people, process, tech, and how do you put this into production within the guardrails of the enterprise? Jason?
Jason Langone
>> Agentic is the talk, right? And if you think about it, now you've got an app not just talking to a large language model, it's talking to a guardrail and a reasoning and maybe something you've tuned. So you start to imagine many, many apps, you've got AI spaghetti. To me, that's one of the interesting things that we're addressing, is how do we give an organization centralized governance and control and serving of these models?>> You guys mentioned a couple of things that really ticked a few boxes for me. One, you talked about the people process and technology, you talked about it being top-down. One of the things that I see is the organizations, the actual operations teams being a little bit reluctant to adopt the technology, or maybe there's a time to comfort for them to get used to it. What do you guys think about AI adoption? Obviously, the executives want to see it. When you're in the field with the teams who are actually the people who are doing it that have to do the processes, what are you starting to see?
Debojyoti (Debo) Dutta
>> When I talk to our customers, I see that they're very excited, they want to adopt it, but they don't know where to start because they've done their POCs, their data scientists have done their POC, but the IT team is trying to figure out how to bring that POC back into production. And that's where I think there's a lot of learning. Because again, they have to figure out the people and the training and the processes. They have to re-architect a little bit and they have to go cloud data first. Those are the challenges that I see on an engineering side.
Jason Langone
>> I'm stealing time to comfort, I like it a lot. And to me, that's one of the anchors of the value Nutanix brings with enterprise AI, is we could pull it up right now. Three clicks, you've authorized the model of Hugging Face, Nvidia, imported your own. Three more clicks, you're serving it up. This is the simplified operations we need to deliver.>> You can steal time to comfort, I'm going to steal AI spaghetti.
Jason Langone
>> Deal.>> Because AI spaghetti is interesting because we all talk about spaghetti code, which means it's a mess. Throwing spaghetti against the wall, we've heard those cliches in tech. But what's happening though, is there's a lot of shadow IT-like patterns we're seeing, so remember the old shadow IT days. They'd go around IT and go to the cloud. AI, same pattern, going around, so we're seeing the same movie again. And so what comes out of that? One, innovation. Hey, slap your hand. Okay, good job. How do you rein that chaos in as Andy Grove would say? So what do you guys do, how do you make AI better? Because you kind of want to let the market run a little bit, let that shadow AI go on. We don't want spaghetti, we want to rein it in. How are you guys balancing that? Because you're in the middle of the action, because you're enabling with the platform some of those innovations. And again, it's coming out of the platform engineering side, as well as the consumer side of the enterprise, which is the analytics teams.
Debojyoti (Debo) Dutta
>> For sure.>> So how do you resolve that? Do you agree and what's your thoughts?
Debojyoti (Debo) Dutta
>> We have a threefold strategy to deal with the rapid pace of innovation. The way we look at it is AI on Nutanix, so we want to have the best agentic platform we're running on Nutanix, our whole infrastructure so that we can speed up things. Then AI at Nutanix, so we're using the same platform to optimize Nutanix. And then AI in Nutanix is we're trying to improve our products with AI. So basically by doing this in a three-dimensional way, we can actually take care of the innovation, but at the same time, the AI platform that we're building, as Jason mentioned, it gives you very simple ways to do day-to-day operations. It helps the IT manage it with a centralized management point of view.>> Three things were, what were they again?
Debojyoti (Debo) Dutta
>> AI on Nutanix.>> On Nutanix.
Debojyoti (Debo) Dutta
>> AI in Nutanix and AI at Nutanix. And our platform gives you simplicity and gives you control.>> Jason, do you agree that the customers are also adopting this? I'm seeing the same pattern going on at the end users. It used to be vendors would provide supply solutions to the end user to consume it, but we're seeing almost a mirror image of what customers are doing to what the platform is doing. Do you see that same picture? Because I'm seeing large enterprises kind of doing the same thing. I use AI for in, at and on.
Jason Langone
>> Spot on, spot on. And I just came out of a partner session, one of the main talk tracks, I go back 15, 20 years to VDI. It was like, all right, there was this technology a long time ago. I think last time I was here, that's what we were talking about. But one of the important things of being successful then was engaging the end user community, getting them comfortable ,hearing what works, what doesn't work. It's the exact same thing here. Everyone wants to use it, many people are using it in some shadow form, but there's a lot to do around enablement, removing the barriers of being comfortable with it and also getting this feedback loop because this stuff is changing every other day, every week.
Bob Laliberte
>> Yeah. And how do you leverage the insights you've gained from it being in and on, I guess, with your customers who are trying to deploy it? Because obviously, John talked about the hype cycle, AI, everything's AI these days, but the actual skills and resources for people out in the field, your end users aren't necessarily all fully up to speed. So how do you help leverage what you've learned inside of Nutanix to help accelerate the adoption at your customers?
Jason Langone
>> That's a great question. I would say two things to come to mind for me. One is how you can get IT operationally ready, because ultimately they need to be operationally ready to receive this and again, run these workloads if this is really going to impact an organization and continue their competitive advantage. The other is how do you quantify the value? I mean, we've got some great internal success stories we've done and has helped us build out a methodology in helping customers quantify the business value of overcoming a challenge.
Debojyoti (Debo) Dutta
>> Customers always want to see how we've done it before they actually bet on this technology, so we are seeing that.>> Got it. You guys are about to have the keynote come in. I want to ask about how customers are transforming. We've been talking about digital transformation for a decade, but there's a real business model transformation going on. Again, this kind of speaks to what's going on with the AI side. You're seeing business logic in the models and in the apps, but it's powered by the infrastructure and the platform. You've got to orchestrate, you've got to scale. You guys talk about global scale as a differentiator. That's going to come from the platform side. I don't see a lot of predictive analytics groups scaling globally, although they use data globally. I don't think the forcing function is going to come from the top in the app side, I think it's going to come up from the bottom. Your thoughts on that piece?
Debojyoti (Debo) Dutta
>> I think what's happening is people are using large language models to actually talk to their own data. For example, every enterprise has private data, whether it's docs, whether it's spreadsheets, databases, video streams, images. They're using large language models to extract meaningful information and then feed it into their analytics systems. And we will see the re-imagination of the analytics, enterprise analytics.>> All right, so I'm going to ask you guys a question. Pretend I'm a customer, okay? I'm sold on Nutanix culture, I've known you guys for years. HCI and Evolution, you've got Cisco, you've got Intel, you've got Dell, all these partners. I get the HCI story, but I've got all these people pitching me all kinds of things, AI factories, all this stuff coming at me. Why Nutanix? Aren't you just infrastructure? What is the current pitch to the customer? I don't mean sales pitch, I'm talking about value proposition. Why Nutanix? Now, how do I integrate you into my re-architecting global infrastructure of our business?
Debojyoti (Debo) Dutta
>> Actually, I will take an engineering view and you can do a field view of this. The value prop of Nutanix AI is that we will give you a shared control point for your IT to run large agentic endpoints and large language models, which is the most expensive part of your new enterprise workload with simplicity, control, predictable cost, so that you can really drive your AI adoption and I mean, get away from shadow it.>> Yeah, rein it in.
Debojyoti (Debo) Dutta
>> Yeah, rein it in.>> How would you see? You're in the customers all the time, what was your value proposition statement?
Jason Langone
>> It bridges the gap. The AI factory is typically consumed and it intrigues the ML team, the data science team for good reason. Adding Nutanix Enterprise AI, NKP as well to that story means that we can cross that bridge from it's a successful POC, it's successful in the lab, successful over here, to now we can move this fully into production with our production IT team support, et cetera. Because if you can't bridge that, it stays over here as this really, really interesting science project.>> So basically, the pitch is, "We don't slow you down."
Debojyoti (Debo) Dutta
>> Yes, that, and I'll summarize what Jason said. With Nutanix AI, you can run an AI factory in production.>> Yeah, I like it. And no one wants to slow down.
Bob Laliberte
>> Yeah, right. And then the other piece of it though is we talked about, you started talking about the shadow AI and things like that. How do you, once you're deployed, help the teams with a little bit of compliance to ensure that the data's not going out to the cloud, it's not going out? Are there any things that you're doing around governance and compliance with your AI as well?
Debojyoti (Debo) Dutta
>> Absolutely. The whole product is centered around control and governance and compliance. For example, we give access controls. Enterprise IT can give very detailed access controls of who owns what model and who has access. Then we have audit logs, we have telemetry. So with a combination of these technology features, we give the enterprise IT complete control of the infrastructure running large language models and endpoints.
Bob Laliberte
>> Excellent.>> Guys, thanks so much. I know we had to cut this short because of the keynote's kicking off, we've got a hard stop. We're going to cut the stream and go to the keynote. I'd love to do a deeper dive on your role as Chief AI Officer and certainly we could do probably another hour, it's a super important topic. But let's just end with what you guys think, the show vibe here. What's happening at NEXT? I know we're in day one, but you've had some dinners, you had a session with partners. You know what the content looks like. What is the vibe for NEXT 25 for the folks watching, who didn't make it here on-premise, on site? On premise, look at me talk about on-premise, if they're in the cloud. Okay, what's going on, what's the big story here?
Debojyoti (Debo) Dutta
>> I think the big story over here is that Nutanix is a transformed company that is also going to help you for your next 10 years of your IT transformation with modern workloads and AI.
Jason Langone
>> Any app, any model, anywhere.
Debojyoti (Debo) Dutta
>> Yeah.
Jason Langone
>> Buzz is great.>> You guys are great, you've got the bet on containers, you've got Kubernetes growing like a weed, agentic wave growth coming. Productivity gains, by the way, great point on that. That's where the economics are going to kick in. theCUBE bringing all the data here real time on the show floor here at Nutanix NEXT 2025. I'm John Furrier, Bob Laliberte, Paul Nashawaty is also here. He'll be on, but he's out doing briefings, getting all the data for you. Check out Siliconangle.com. Of course, cube.net and thecuberesearch.com. Thanks for watching.
Jason Langone
Bob Laliberte