Red Hat Summit 2026 | John Hampton, AMD

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John Hampton

Corporate Vice President, WW Enterprise Technical Sales

AMD

play_circle_outline From Thousands to Hundreds: Server Consolidation Eases Budget, Power, and Space Constraints for Data Center Modernization

play_circle_outline AMD and Red Hat partnership simplifies hybrid stacks across virtualization, Kubernetes, and AI.

play_circle_outline Tokenomics and Rising GPU Costs: AMD Pushes CPUs and Low-Cost GPUs, Advocates Open Ecosystem

play_circle_outline Few enterprises show positive AI ROI; need proper assessment and ROI measurement.

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John Hampton, AMD

John Hampton

Corporate Vice President, WW Enterprise Technical Sales AMD

In this interview from Red Hat Summit 2026, John Hampton, corporate vice president of global enterprise technical sales at AMD, joins theCUBE's Rebecca Knight to discuss how AMD is helping enterprises modernize their infrastructure and optimize AI spending through a framework he calls "tokenomics." Drawing on nearly 25 years at AMD, Hampton describes the two challenges dominating enterprise conversations: the urgent need to consolidate aging data centers and the spiraling cost of AI compute. He explains how rightsizing legacy server fleets — in some cases fro... Read more

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What are enterprises saying are their biggest challenges in adopting AI, and how is your company addressing those challenges? add

How is AMD partnering with Red Hat to simplify AI deployments and drive enterprise growth? add

What are these customers struggling with, and how do you help them evaluate and decide on the right AI infrastructure and cost‑effective solutions? add

What is the current state of enterprise AI investment and what steps should enterprises take to achieve positive ROI? add

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John Hampton, AMD

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Rebecca Knight

>> Hello everyone and welcome back to theCUBE's live coverage of the Red Hat Summit here in Atlanta, Georgia. I'm your host, Rebecca Knight. I would like to welcome to the show a Cube veteran, John Hampton, Corporate Vice President Global Enterprise Technical Sales at AMD. Welcome back, John.

John Hampton

>> Thank you, Rebecca. So good to be back.

Rebecca Knight

>> So good to have you. You are approaching a quarter of a century at AMD. That's quite a milestone. Talk a little bit about, from your vantage point, what you're seeing in the industry right now and past inflection points, does this feel markedly different?

John Hampton

>> It really does. It feels so different right now. It's incredible to have been at AMD for 25 years now. What a ride it's been, but right now is incredible. Just to be this pace of innovation that we're seeing in the AI space, it's like nothing we've ever seen before. It's extremely dynamic. I think it's so important that we're out at these events and sharing all of the exciting new innovation in the data center and the PC and of course in AI. So that's what we're here to talk about today and just let them know all the exciting ways we can partner together.

Rebecca Knight

>> Let's start with the fact that you are in the kind of job where you're talking to enterprise customers day in and day out. What are the conversations that keep coming up over and over? What's keeping them up at night?

John Hampton

>> That is such a good question and I have the privilege of traveling around the world and meeting with large enterprise. And there's really two things that I hear more than anything else. The first is we need help modernizing our infrastructure for AI. A lot of these enterprise organizations are struggling to find the budget, the power for sure is a huge challenge and even physical space in their data center. But they're all in these hybrid environments and dealing with all this complexity and we're working with Red Hat to help them modernize those data centers. It's really incredible how much consolidation they can do. Imagine taking 1,000 servers down to 150 and imagine all the budget and power that you can free up by doing that. And Red Hat has such a fantastic solution with their tools across virtualization, Kubernetes and AMD's industry leading total cost of ownership. So that's really the first thing that is keeping them up at night that we're helping them with. But it's about then taking that budget and that power and reinvesting it into AI. And what we're really excited about now is bringing most optimal tokenomics is what we're talking about, tokens per dollar. This is what every enterprise is struggling with today and they're looking for some help. They're looking for some alternatives that AMD can now bring and we're excited, this is really a new company than it was when I started. Now we're offering CPUs in the data center, in the cloud, on the edge, the PC and into the AI space. So imagine this spectrum of AI solutions that we can bring to enterprise to deliver for them most optimal tokenomics.

Rebecca Knight

>> Well, those are two areas that I really want to dig into with you here today, because even just a few years ago, AMD was a bit of an underdog in this conversation and now it's a real player in AI infrastructure. Your partnership with Red Hat goes back a long time. Talk a little bit about how your organizations are working together to help companies modernize their data centers.

John Hampton

>> Yeah, that's what it's all about. And AMD really has been on an incredible rise. What a run, a privilege to be a part of it. I will say this, we haven't lost that underdog spirit though, Rebecca. We want to be aggressive and continue to drive growth and we're going to do that by solving these enterprise outcomes. And how are we doing that with Red Hat? Well, there's a few things that are very, very important that we're bringing. With Red Hat AI in particular, they have such an established, stable stack, so AMD's hardware and our software stack combined with a very well-known stack from Red Hat really gives customers the simplicity they need. I mean, there's so much noise out there, a lot of complexity that they have to deal with in the world of AI, so AMD and Red Hat just cut through that noise and simplify it down. You can have a common set of tools that span from your on-prem data center into cloud and now into AI and really just simplify that, get into your agentic workflows and find very efficient ways of approaching that, again, on the most optimal solutions that we can now bring them. So it's really exciting, we just actually had a couple of recent announcements as well that we launched to bring new exciting technology together to the market.

Rebecca Knight

>> Well, we're going to talk about that too but before we do, I want to get into tokenomics because this is a phrase that you have coined and it's really about helping companies make smarter decisions around AI, particularly around compute and the budget as you say. Talk a little bit about what these customers are really struggling with and how you help them walk through those decisions.

John Hampton

>> Yeah, that really is the multimillion-dollar question. And what we see happening is so many of these enterprises just ran out and bought big GPU clusters because they knew they had to solve for AI and now they're really struggling with tokenomics. And imagine they're running all these models, I mean, I think I'm running three or four agents just myself now in my daily work and that's where we're headed. All these agentic workflows are just soaking up more and more tokens, more and more compute and so enterprises are coming to us and they're saying, "This is exploding. It's good that we're using AI, but we can't afford this anymore. How are we going to deal with this? We went out and bought these huge GPU clusters and now what are we going to do?" So we're really out there building awareness and education. What we want to do is an assessment of their AI use cases and help them, advise them, be that trusted advisor that helps them understand these AI use cases are mapped to these most optimal solutions. It doesn't always have to be the same GPU cluster that our competition's been offering. And again, every day I'm hearing, "I need an alternative, I need choice," so with Red Hat and AMD, we're bringing that choice in a very open environment versus like a proprietary closed approach. So we're all doing this together as an open ecosystem, but imagine being able to map some of these AI use cases to CPUs or lower power, lower cost GPUs. The good news for AMD is that we have a full spectrum of solutions across that inferencing that enterprise is focused on now so we can map them to the most optimal solution for them and that really starts to help them solve for that tokenomics equation, most optimal tokens per dollar or tokens per watt that they're spending.

Rebecca Knight

>> And it would have an enormous financial and technological-

John Hampton

>> Huge financial impact....

Rebecca Knight

>> impact on their bottom lines.

John Hampton

>> That's right. That's right.

Rebecca Knight

>> So there were some announcements that IBM Think and you brought a little show and tell here for us.

John Hampton

>> Yes. We're very excited about this.

Rebecca Knight

>> Tell us about what this is. Yeah.

John Hampton

>> This is fresh news. We've just launched a new AMD Instinct MI350P. This is a new PCI GPU solution that was just announced and now available with Red Hat 3.5 EA, so we're very excited about that. And this GPU really does help now complete that tokenomic spectrum. So this is a much more aggressively positioned GPU for lower price points and lower power. So many use cases out there, this is really perfect for what enterprise is looking for and this really completes that inferencing spectrum that AMD is offering. So on one hand, you might be able to map some of these AI use cases to AMD EPYC CPUs or this MI350P may be the perfect GPU solution for your use cases. And then of course we can scale on up to as high as you want to go with massive compute. We have this solution we launched earlier this year called Helios that now has AMD CPUs, GPUs, AI Nix. Again, this is a new AMD, so the point here is that we want to bring the most optimal solution for these AI use cases across the hardware, the software, the models, and the stack that Red Hat AI brings them.

Rebecca Knight

>> Enterprise customers are really everywhere on the maturity curve. Some are really running serious AI workloads. Others are still figuring out where to start. What would you say is the difference between the people, the organizations who are really ahead, the leaders and the laggards? What's making the difference?

John Hampton

>> Real great question.

Rebecca Knight

>> Yeah.

John Hampton

>> And if you look at the stats, they're not pretty. What I've seen consistently is there's really only been single digit enterprises that have successfully invested in AI and seen positive results, positive ROI and moved into production. There's still a lot of experimentation going on out there, but I would encourage enterprise to really sit down and really, first of all, make sure that you know how to measure your ROI. A lot of folks just jumped right in and it's a ready, fire, aim approach to things. We want to sit down with you, AMD Red Hat in the enterprise and really look at the infrastructure, see if we can't help them modernize, like we talked about, help free up budget and power that they can reinvest in AI. A lot of the successful ones really have been on the bleeding edge and really leverage the full open ecosystem that AMD, Red Hat, and many others can bring and really push the envelope, make sure that everyone is learning how to use AI. AMD is a good example, like our employees, we have I think now over 150 internal AI use cases. Everyone's getting comfortable being more productive but again, while you're pushing the boundaries, you have to do it in the right way. And so that's what we're really encouraging them to do is let's make sure that we do a full assessment and we really look at the overall financial impact, the technology impact of your decisions and be there by your side to help you go through that, work through that complexity. So I think just to answer your question, you really do need to invest in AI now. You want to start taking advantage of it internally, but do it in the most optimal way, do it the right way with your partners like AMD and Red Hat.

Rebecca Knight

>> Along with that, what are some of the misconceptions that you hear in terms of enterprise customers talking about their need for AI infrastructure? Is it the people versus the technical issues? What are some of the things that you're hearing that you think, "Eh, maybe not"?

John Hampton

>> Yeah, there's still an ongoing concern in the industry, really in the world now of will AI replace people? Will it replace my job? And I think that we really believe that AI should be for everyone, AI everywhere for everyone is actually something that Dr. Lisa Su, our CEO talks a lot about. We want to use our technology to help solve the world's most important challenges. Now I think that there will be a balance here. There's certainly a lot of automation that can happen. One of the killer apps right now, as an example, in enterprise is just coding. It's incredible the coding assistance that AI can bring, but what that's done for AMD coders and engineers has really allowed them to be so much more productive, our faster time to market. You still need those humans to do it, but they're enabled beyond anything we've ever seen. Again, coming back to this question, it's so different now. It's so exciting now to leverage technology like we've never done before and it makes us all so much more productive as humans. It helps us scale. I think the reality is some jobs could be replaced, but there's so many other new, exciting jobs that are opening up at the same time to leverage all this new innovation. And that's what we're encouraging enterprise to do, let's sit down and talk about all those exciting use cases that you could be considering and let's help you figure out the right software stack, the right models. Again, the most optimal solutions that we can serve up for those use cases that you should be running and let's do it together. So I really think that that's the answer. It is a challenging and evolving topic, but I think there's every reason to be very excited about what AI brings us now.

Rebecca Knight

>> And optimistic from your perspective.

John Hampton

>> Oh, for sure. A ton of optimism.

Rebecca Knight

>> I want to ask you about leadership because you've been a technology leader for a long time now and you said earlier in this conversation that you yourself manage three or four agents in addition to the humans who are on your team and consider you their boss. How is that changing your approach in terms of how you think about leading a group and thinking about strategy and vision and also maybe even your approach as a manager to the humans?

John Hampton

>> Rebecca, I love that question, I really do. My leadership philosophy that I've tried to embody is people first leadership. I got that starting from our original CEO, Jerry Sanders. He was famous for being quoted, "People first, products and profits will follow." And I've tried to always embody that myself with the individuals that I lead. I think that the people remain our most important resource, but now we can leverage AI to enable and empower those people like never before. And so I think that that's really the answer is when we're making big decisions, when we're thinking about how we operate on a daily basis and how it impacts things. We have to think about the people first and foremost and I think that we have to lead them in that way, just completely revolving around those people as the resource that brings all of this to life, but now we can enable them and truly empower them like I've never seen across my career and that excites me as a leader. Am I going to have a few agents that I run and my team runs? Absolutely. And we're all learning on a daily basis about more that we can do together as people sharing these learnings. So really exciting to think about where we're going as people in the industry.

Rebecca Knight

>> Speaking of where we're going as we wrap up this conversation, we're here at the Red Hat Summit 2026, what is one thing you would like to be able to say at Red Hat 2027, the story you want to be telling next year about the progress you've made?

John Hampton

>> Yeah, I think that the story is all about choice. It's always about what's new and exciting in technology. I'm coming to this summit to hear about new things. Well, AMD is becoming, as you said, an incredible alternative in the industry and we just want to talk about it. We want to be there as a trusted advisor to work through all these challenging topics, all the complexity and that's really the main message I would give is try it out. And that's an open invitation to those that are listening. Let's go and run a POC together. Let's figure out what it can do for you, the financial impact it brings your enterprise, and the technology impact that it brings as well. So very excited about being here at Red Hat Summit 2026 and having those conversations.

Rebecca Knight

>> Let's do this thing, John.

John Hampton

>> Let's go.

Rebecca Knight

>> Great having you on theCUBE again.

John Hampton

>> Thanks for having me, Rebecca.

Rebecca Knight

>> I'm Rebecca Knight 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.