Name: Chris Stansbury, Lumen
Uploaded: 2026-08-01T07:00:00.000Z
Duration: 33 min 31 s

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More from theCUBE + NYSE Wired: C-Suite Business Transformation

Chris Stansbury

President & CFO

Lumen

play_circle_outline Lumen earnings: strategic portfolio now 53% of revenue

play_circle_outline Massive fiber expansion: target 58 million miles by 2031

play_circle_outline North-south vs east-west traffic: prem‑cloud versus cloud‑to‑cloud

play_circle_outline NaaS growth strong; east‑west TAM expanding from ~$20B to over $70B

play_circle_outline Hybrid/multi-cloud (Supercloud) as distributed computing substrate

play_circle_outline Resilience and cost savings; faster M&A integration via cloud-native networking

play_circle_outline Alkira acquisition accelerates programmable east-west multi-cloud networking

Info

Chris Stansbury, Lumen

Chris Stansbury

President & CFO Lumen

(INTRO)

John Furrier

>> John Furrier with theCUBE here at theCUBE's NYSE studio. Of course, we have our Palo Alto studio connecting Silicon Valley to Wall Street, bringing deep tech coverage to Wall Street and Wall Street to Silicon Valley. This is our business transformation series. we talk to leaders who are leading the era of modernization around AI infrastructure, AI intelligence, as the transition to businesses who are transforming and driving revenue, of course, taking the cost out and using AI. Chris Stansbury here, president and CFO of Lumen. It's great to have you on. We all know Lumen Field in Seattle. We see that all the time. Of course, we've covered you guys on theCUBE. Thanks for coming on.

John Furrier

>> Great to be here.

John Furrier

>> networking is so hot right now. This is your DNA. You guys just had your earnings. You had an acquisition.

John Furrier

>> Yeah.

John Furrier

>> Alkira, a company we've covered on theCUBE. You're starting to see the role of networking change. Let's get into the news first, the acquisition and earnings. Take us through the earnings and then the acquisition after.

Chris Stansbury

>> Yeah, to your point, the landscape is changing rapidly and one of the big pieces of data that we shared in earnings is that the strategic part of our portfolio, the growing part, the part that customers want today, is now more than half the company. It's about 53 % of revenue. And we see that continuing to grow in a really significant way as more customers are adopting NaaS, and to your point, we'll get into Alkira, which just accelerates that. And there's a shift going on because networking historically has just been largely dumb pipes that others then had to figure out and innovate around so they were secure and they worked, and that just doesn't work anymore. There's too much sprawl, too much complexity, especially with data now being geographically everywhere. We don't even know where our own data geographically sits. And so you've got to have access. It's got to be on demand. You've got to have low latency. And it's a totally different networking environment today to meet those demands.

John Furrier

>> Yeah, it's interesting. I'd love to get your thoughts, and we'll get to the Alkira thing. I want to go into that a little further. But what's changed is the intelligence. Moving packets from point A to point B, been there, done that. The role of storage, networking, and compute, and even database has changed so much. If you look at how the best AI systems are being built, it's those three elements, but they've changed. The role of storage has changed, HBM memory, how important that is, the density of these large scale rack scale clusters, and you now have a distributed computing environment at the edge. You've got robotics, you see autonomous vehicles, physical AI is certainly going to become super fast. It changes the role of networking. How do you guys see that? Because as you mentioned the dumb pipes, that was the old model. Yeah, you put the intelligence at the edge, that's just where it goes. Now you have to know that. If you look at the rise of the importance of KVCache and NVIDIA, everyone's looking at that saying, okay, tied to a software model, CUDA, networking. Moving data around tokens makes it really important. So networking now is front and center. It's the operating layer of AI.

Chris Stansbury

>> It is.And we like to refer to it as the nervous system for AI. If you think about the GPUs as the brain, The brain can only function with a nervous system that can alert it, that can help the body react, and in this case, AI's body react. So we see a world where the network has intelligence built in to know, hey, wait a minute, those GPU clusters are nearing capacity or there's an energy limitation in that geographic location. Let's just reroute the traffic to a different location where there is energy, where there is capacity. But to do that, you have to have a programmable layer that lets you do that with little to no latency, on demand, from anywhere to anywhere. And that's what we're building.

John Furrier

>> Yeah, I like that approach. And seeing other people vertically integrating on the NeoCloud side, Nscale just bought, Anyscale for over a billion dollars, privately held company, that points to this, I got to know the resource, I got to know where to route things, and cost is too important. finally, as we heard from the leaders here in New York this week. Jensen came out and said, hey, here's a half a billion dollars. Here's KKR, Blackstone, Goldman Sachs CEO. They're all saying, hey, we're going to invest in AI infrastructure.

John Furrier

>> Yes.

John Furrier

>> And that is a huge signal to the market that this is not a bubble. It is not a bubble.

Chris Stansbury

>> There is massive demand. Right. I totally agree. And look, we don't know who the winners and the losers are going to be. What we do know is that whoever wins in the space is going to need a programmable network layer. And that's been our vision now for a number of years as we've turned the company around and now we're really transforming it because ultimately the only way AI is going to work is if the network that supports a very dynamic environment is dynamic itself. The network cannot remain static to support a very dynamic AI world.

John Furrier

>> I've been covering Lumen for a long time. Love the networking approach. You guys have a great business. Talk about the assets and the strategic asset sets that you guys have because we're predicting that after the AI factory era, where all the scarcity is still going to continue to be with HBM memory, but you're going to have the monster data centers, the AI factories you see in the big places in Texas, all this big build-out, that's going to continue to grow. Okay, if you believe that to be true, which everyone does, the distributed computing nature of AI means that there's going to be other nodes.

John Furrier

>> That's right.

John Furrier

>> The edge, metro areas. When I hear people talk about metro POPs or metro factories, it kind of has that same trajectory of networking.

John Furrier

>> That's it.

John Furrier

>> You guys have a huge asset base. Share just some general stats on Lumen's position, because if distributed computing comes full throttle, that's going to make AI factories everywhere.

John Furrier

>> Yeah.

John Furrier

>> That means they're just nodes on a distributed computing network. Talk about that and the role of networking.

Chris Stansbury

>> Yeah, and we think about it really in a couple of different ways. And to us, it's a three-layered cake. And at the base, the foundation, is that physical layer of fiber, the most modern fiber in the world. And we are on track to deliver about 58 million miles by 2031. When Kate joined the company just four years ago, we were at about 12 million miles. So a massive investment has taken place, and we've done that very efficiently because as we built network to support LLM development for the hyperscalers, we've been able to deploy additional network to support broader AI for the inference phase.

Chris Stansbury

>> You guys have been digging the trenches,

Chris Stansbury

>> paving the roads,

John Furrier

>> pouring the concrete of AI.

Chris Stansbury

>> Not most of it actually, but most of it has actually been the utilization of underutilized conduit that was put in the ground 25 years ago.

John Furrier

>> Yeah, so you're not digging, you're just connecting.

Chris Stansbury

>> And so we're not digging, we're deploying, but that's not the unlock. The unlock is the programmable layer. So think about all those pipes and the way we traditionally do it, frankly, is a lot of north-south traffic. It's prem to cloud. And because of our proximity with the hyperscalers and because of our new multi -cloud gateways that sit physically in our network, we can get direct cloud access with super low latency, super high speed, much lower cost than going through.

John Furrier

>> What's the impact to customers on that?

Chris Stansbury

>> What does that mean for the customer? Well, what it means for the customer is lower cost, much faster ability to connect into the cloud. What it means to the hyperscalers is faster time to revenue in terms of that cloud uptake. And what Alkira brings us when you connect that in is the programmable layer for east -west traffic, where you're now moving data cloud to cloud, cloud to DC, to the edge, with it never having to touch the prem. And that layer is actually agnostic to carrier and cloud. It touches every cloud. It'll ride on any network. So as others are building trenches, we can control that traffic that ultimately rides on those.

John Furrier

>> So you have north, south, east, west, and what that means is you can go anywhere.

John Furrier

>> Anywhere.

John Furrier

>> Based upon what workloads, what the infrastructure's doing. Talk about the demand, because I've heard, I love when people talk about the bubble, because I've been through bubbles before, and especially the dot -com bubble. I lived that, I got a lot of scar tissue from that one. But at that time, there was not a lot of demand for the fiber.

John Furrier

>> That's it.

John Furrier

>> And so people compare a lot of the AI bubble to the early days of the internet.

John Furrier

>> Yeah.

John Furrier

>> And I think that's a false premise, because if you look at the online population at that time, it was just ramping. Now the demand curve for AI is off the charts. The demand for intelligence is off the charts.

Chris Stansbury

>> That's it.

John Furrier

>> So share your thoughts on the demand curve for intelligence and why you're investing so much in the fiber.

Chris Stansbury

>> Absolutely. So when you think about the dot-com bubble, it was a solution looking for a problem, right? And ultimately, industries grew and found a way to consume that and utilize it. This is totally the opposite. This is a situation where there's demand today. Obviously you need fiber, people are building fiber, deploying fiber, but you need a way to program it and consume it easily. And so, for too long, networking has been about deploying the capacity. it's now about enabling easy consumption. And so you've got to have the capacity, yes, but you've got to have a pathway to easy consumption. And that's where we really see the growth. And a couple of data points, if we look at our own growth trajectory, again, over half the company's now growing, if you think about our NaaS product, which is really north-south lanes, it's growing high 20s, low 30s, quarter on quarter, in a market where the dollar TAM growth is under 1% per annum. So you've got an explosion of data, huge data consumption, but very little dollar growth because that north-south traffic is commoditized. When we move to east -west, we're talking about growing our TAM from 20 -ish billion to over 70. And in a market that's growing at 13 % in real dollar growth because the need now with data centers being everywhere, and quite frankly we don't even know where the next one's going to be.

Chris Stansbury

>> Yeah.

Chris Stansbury

>> And there's huge backlog by the way.

John Furrier

>> There's orders waiting to be fulfilled.

Chris Stansbury

>> That's exactly right. And so that'll all sort itself out and when you watch the markets and it's like, oh is it a memory thing, is it a GPU thing, is it an energy thing? Those are long lead items, that will sort itself out. But what is very clear is that we're moving to a much more distributed data environment, and we have to have an access layer that allows you on demand to move traffic anywhere. think about a regulated industry, financial, healthcare, where you've got data sitting in a private data center in an area that's about to be hit with a hurricane. Well, if you need to rely on traditional networking to go build a pipe to the new data center location, it's going to be too late. But if you can access that in a very programmatic way on demand and move that through software, these are networking fundamentals.

John Furrier

>> That's powerful.It's not new, but the techniques are new.

Chris Stansbury

>> That's it.

John Furrier

>> The programmability and routing and policy, it's been around since networking was around.

Chris Stansbury

>> That's it, and quite simply, what are we doing? We're doing what other industries have done, we're cloudifying networking.

John Furrier

>> Yeah, I think the demand thing is huge, and one thing I want to get your thoughts on, because I think you brought this up and I think it's worth unpacking. The demand on the east, west, and north, south are continuing to thrive because of the cloud. Now, if you go back two years, the number one conversation in the pundit circles was repatriation. Moving workloads off the cloud back to on -prem. But what's happening now is the cloud's still growing. So you have cloud growth. You have on -prem growth. Now, what happens? You have a demand for intelligence. First, it was like marketing, search. We saw the first wave. Now you've got coding. agents are coming in, physical AI right behind it. The on -premises activity has nothing to do with mutually exclusive solutions on the cloud because cloud's growing. So to me, that's distributed computing. So share your thoughts on this because a lot of people are trying to squint through. Data center growth on -prem is because the cloud's slowing down. That's not true. It is not true. The cloud is still growing, but it's just all connected. So north -south, you meant hyperscale. There's more hyperscale demand because people have workloads on there.

Chris Stansbury

>> People have workloads on there. And by the way, what does on -prem mean anymore? Because on -prem doesn't mean that it's physically in the building that you're sitting in. It may be in your footprint, in your corporate footprint, but it's still geographically dispersed. And so you still have to have that access. So you're seeing growth in both, and what does that mean? It means that the environment is getting more complex. It means that there's more network sprawl using traditional methods to try to get all that connected. And so for us, complexity is our friend.

John Furrier

>> Well, the demand for data growth, that's private data. the frontier models are public data. Let's face it, on premise data center, enterprise data is locked. So the unlock there is, how do I leverage that? Well, I want to have either VPCs in the cloud and or a controlled managed service on a workload end to end. That's the demand that we're seeing.

Chris Stansbury

>> Exactly, and look, if we go way back to when cloud first originated, there was the doomsayers who said, oh, it's going to wipe out all on-prem. And the reality is, where have we landed? We've landed with a hybrid model. And a hybrid model, private cloud, public cloud, on-prem, what it means is more points of connectivity that have to be secure, that have to be fast, that have to be accessible on demand, and that's where we fit in.

John Furrier

>> I think you're hitting on the perfect storm of innovation because if you look at Alkira acquisition, Now let's talk about that because you're essentially seeing cloud native growth, rise of the cloud, we saw that generation. The rise of AI native together with distributed computing that's hybrid.

Chris Stansbury

>> That's right.

John Furrier

>> Okay, that's a fact. It's interesting, Alkira was on our SuperCloud program that we ran. At that time we called it SuperCloud, we didn't like the term multi -cloud because we predicted that SuperCloud was essentially workloads running across clouds as a resource, not I'm running my Teams and Office on Azure, it was, I want to use Azure for compute and now AI. So you're starting to see that play out. In a way, the multi -cloud is just a substrate of resource and networking. So that played out. So it kind of, SuperCloud name was just kind of, didn't really take, but call it distributed computing. Now you have AI layering on top. You have the systems of intelligence. And that's going to be key. A term that we coined here on theCUBE was, underneath system of intelligence is systems of adaptability.

John Furrier

>> Yes.

John Furrier

>> And that's what you're kind of getting at on programmability. So talk about that piece because I think Alkira fits into that adaptability piece because it really does. You got to have the data, it's got to be adaptable, real time, available, horizontal, harmonized, contextualized, context graphs, but then that produces the intelligence, the super intelligence, specialized intelligence, general intelligence, that sits on top because I think this is a new layer of the infrastructure.

Chris Stansbury

>> It totally is because again, historically the network has been slow to adapt. Again, very static. And so we're now in a dynamic environment where the hyperscalers want to control the movement within their own clouds. But what the customer wants to do, very few customers are in one public cloud. They've got data in multiple clouds, and in multiple DCs, and they want the ability to move from anywhere to anywhere in a dynamic way. And so that's where we see the growth. And by the way, let's expand that more broadly just in terms of business use cases. So think about the world of M &A where historically, oh, I've got to integrate these two compute and network environments. It's going to take me 18 months and 100 million bucks after I buy the company because their equipment doesn't match my equipment. Well, when that's all in the cloud, Koch Industries uses Alkira to integrate M &A because it happens in days because it's cloud native. Now think about real time resilience. There's a situation, a large customer of Alkira's that I can't name in the Middle East where a data center was flattened by Iran and the customer never knew it happened because you had resiliency built into that cloud layer that let their business just keep on running. So when we think about the number of problems that it can solve.

John Furrier

>> That's autonomous.Exactly. Exactly. That's autonomous behavior. That is it. That's agentic like adaptability and resilience.

Chris Stansbury

>> That's right. So the more, back to your point, the intelligence that can exist in that kind of a programmable layer is exactly what AI needs to function. And by the way, you know this probably better than I do, but what's the rule of thumb on AI's intelligence level? Is it doubling like every three to six months? So with that is coming more business use cases, more data consumption. And this situation is only going to need that layer more.

John Furrier

>> You're the president and CFO, so scope the cost. You mentioned the acquisition on the M &A side. I like those numbers. Let's take that example of the data center in Bahrain or wherever it was. The cost scope of the old way versus having that adaptability and resilience. What would that have cost? Just order of magnitude, sense of cost. How big of a savings does that yield?

Chris Stansbury

>> When you think about it, you almost can't compute it because there's reputational damage. There's the amount of time the business is going to be down. And, again, with that capability, it just didn't exist. So you go from a situation of massive recovery efforts, PR, everything else, to, oh, we didn't know that happened. I mean, just the risk management pays for itself. It's huge. And so now, with a programmable layer that is cloud agnostic and carrier agnostic, well what does that mean? It means it's also geographically agnostic. So we can create a global environment for a multinational corporation. Well that's going to come in very handy.

John Furrier

>> You talk about sovereignty because sovereign cloud was more about privacy and regulation stuff. Now with AI sovereignty, you're talking about residency in say geographies, regions, or countries. So now you've got people leaning in saying, whoa, whoa, whoa, I love the privacy for users and data that maybe specifically has certain parameters. Now you talk about residency. So sovereignty will be very much programmable.

John Furrier

>> Exactly.

John Furrier

>> That becomes, talk about your vision and how you guys see the sovereign AI playing out.

Chris Stansbury

>> Yeah, so think about a use case financial sector, right? Big global banks. They're going to want one thing for sure. They need privacy, they need high -speed pipes, and they need it not to be over public Internet. And the reality is that can be stitched together with partners who build infrastructure. But what allows that to work is that programmable layer that makes those underlying pipes look like one network and the ability to move in and out of cloud environments. So to your point, you can program in the sovereignty to make sure that you're complying with whatever the regulations are locally, but you're given a global view and one pane of glass to manage that network environment.

John Furrier

>> And sovereignty is not country specific. It might be from a geography standpoint, but because of the nature of the hyperscale, it's a global footprint. That's what you're saying.

Chris Stansbury

>> Exactly.

John Furrier

>> All right, let's talk about the transaction. You guys closed the deal. Take us through what was attractive on Alkira. You mentioned some of the multi -cloud, about domain specific advantages. How did it all come together? How'd it go down? How's it going to play into the future?

Chris Stansbury

>> Yeah, so we had our investor day in New York back in February, and we laid out a vision for what north-south and east-west traffic could look like, and the network that we were building and aspiring to build. And about the same time, Alkira came into our view, and we said, hey, wait a minute. They've already built this east -west capability, and we can accelerate our transformation by two to three years and save the capital involved. But the bigger point was the ability to move immediately. And so we engaged in that conversation, moved quickly, and the deal closed in July. And I would say importantly, in a lot of acquisitions, you've got competing views between the acquirer and the acquiree. The Alkira team is absolutely phenomenal. We knew that they were bringing a skill set to Lumen that we didn't have. We've actually plugged Lumen's innovation into Alkira rather than the opposite. And the Alkira leadership team, the founders, were thrilled that it was Lumen's network and Lumen's connectivity to the hyperscalers that really unlocked value in their programmable layer.

John Furrier

>> they got the keys to the kingdom because I interviewed the founders, very strong tech team, very excellent software layer. But you bring the network piece at scale.

John Furrier

>> That's it.

John Furrier

>> That's a huge deal for them because now they didn't have to do the biz dev on their side to lock in relationships with the hyperscalers and also the edge is coming on strong for them.

Chris Stansbury

>> That's it.

John Furrier

>> How did they factor into the plans going forward? It sounds very strategic.

Chris Stansbury

>> Yeah, so.

John Furrier

>> You organized around them?

Chris Stansbury

>> Yeah, so we obviously had to be careful with gun jumping and whatnot. We had to wait until the deal closed, but day one, as soon as that deal was closed, we had teams on the ground working together on how we first quickly deploy things that can be sold today but then very quickly started to integrate Roadmap so that there's an ongoing selling motion here because this is really about scale.

Chris Stansbury

>> Yeah.

Chris Stansbury

>> It's a new capability, but customers can choose how much they layer into that relationship. And it can be through ecosystem partners that add additional value that we're working with. So it's about making sure that roadmap is unified and consistent. And we're going as fast to the hoop and as hard as we can so that when we guide next year, the desire is for the first time in many, many years to actually guide revenue because we think this pulls in our inflection back to revenue growth more quickly.

John Furrier

>> And by the way, their multi -cloud fabric and what they're doing for the hyperscale works beautifully on edge.

John Furrier

>> It does.

John Furrier

>> Edge is going to be, we're very bullish on the intelligence at the edge. We think AI factories are going to move to the edge very quickly. That's going to change the game on what happens at the edge, even from telecom providers becoming more service oriented.

John Furrier

>> Absolutely.

John Furrier

>> And you guys, as a network, you have points of presence all over.

Chris Stansbury

>> We do, and we do have some edge environments all over. And so the reality is that, again, complexity is our friend. Compute at the edge, I think, is real, to your point. And what we're going to have to do is make sure that for that to work, the data gets to where it needs to go when they need it to go there. And that's what we're enabling.

John Furrier

>> Well, I'm super excited for this chat. One of the things I would like to chat with you briefly is the transformation journey you mentioned earlier in our series on Business Transformation Edge. It's about the competitive edge of the future. Most IT projects that I've seen in my career over the past 30 plus years it's, hey, do the pilot out in the hinterlands of the environment, let's get it going. Months go by, hands are in there, multiple fiefdoms are playing with it, and then it's like, okay, did it work, and there's no production. Now, it's much more rapid.

Chris Stansbury

>> It is.

John Furrier

>> It's business oriented, it's business model. How has your transformation journey gone? Take us through the transformation and how you as president and CFO look at that, directing capital, does it change how you look at capital? Does it change how you look at the personnel? How's the M &A's factoring in? Take us through your vision on the transformation.

Chris Stansbury

>> Sure.You know, there's a lot of history here, so I'll keep it short. But I would say the most critical thing that happened was the change in leadership when Kate Johnson joined the company. And her number one objective was to change the culture. And this is an industry that was really defined by playing to not lose. And so I actually met with someone this week who's a huge Cleveland Cavaliers fan, and he talked about the NBA playoffs game where the Cavs had a huge lead over the Knicks, and then they just watched it slip away because they got overly defensive. And that's how this industry worked. And so we had to change the mindset. But at the same time, we had to build a foundation that didn't have cracks in it. And our capital structure was a mess. And so really there was coordination but a division of labor. Kate was very focused on driving the culture change, moving us to a more digital future. While I was focused on, all right, we've got $20 billion in debt with half of it due in 2027. It's an existential threat. We had creditors that were upset, and we had to deal with that. And so we did it in a very transparent public way. We sold non-strategic assets. We monetized underutilized conduit with these large hyperscaler deals, which allowed us to de-lever the company. It allowed us to fix the capital structure and put us in a position, really importantly, to have a balance sheet that could become a strategic asset rather than a liability. So you've got to clean house a little bit. And that's what allowed us to buy Alkira.

Chris Stansbury

>> Yeah.

Chris Stansbury

>> And that's what puts us here now. So in many ways, the turnaround was getting us to the starting line. We weren't even at the starting line. We had to get to the starting line, and now we've got a business that is, last quarter grew 14 % year over year, that's now more than half the company that's really starting to pull the company forward. We'll inflect EBITDA this year, and we will inflect revenue soon thereafter.

John Furrier

>> Well, congratulations, I love that. If you had to answer the question, now that you have this strategic asset, this foundation set, cleaned house a little bit on some of the loose ends, you're in position, you're going to take an offensive approach.

John Furrier

>> Absolutely.

John Furrier

>> How are you going to leverage that strategic asset?

Chris Stansbury

>> Yeah.

Chris Stansbury

>> What's the plan, what's the focus?

Chris Stansbury

>> It's a great question, and we've actually started to be public about the fact that, look, this company, like every company, needs to have a product lifecycle approach. And so what we're doing with a pathway now to a much bigger growth company inside of Lumen that is our digital future, is to de -emphasize and candidly starve the products that customers aren't buying anymore of resources that it takes to support them so we can plow that into the innovation engine and get even more aggressive on the digital side. So to your point on how we think about deploying capital, it really is about driving a return now. It's less and less about fixed pipes. again, 58 million miles is our target, and it's more about that digital layer. So it's about redeploying resources from the past into the future and being super aggressive about it.

John Furrier

>> You know, I've been very vocal on the whole AI factory distributed computing thing we were just kind of riffing on, but I said the secret sauce, as I say to Dave Vellante, the secret sauce is connecting the factories. That's it. So how do you view the AI infrastructure build out that's going on now, because we predict that the scarcity thing will sort itself out probably in the next 12 months. In that 12 months, enterprises and neoclouds are in a discovery phase of monetization. We think agents will come in quickly.

John Furrier

>> Yep.

John Furrier

>> Offer deterministic workloads, clear. But I think 2027, 2028 will be a massive discovery of, wow, this is how we monetize intelligence. That's it. What's your view of that?

Chris Stansbury

>> So, it's so interesting that you say that because this week, when I've been in New York, I've met with customers, I've met with investors, and I've had a couple of great conversations. And that timeline is aligning with, I think, what that community is starting to see, which is a lot of the speculation around shortages and limitations, that's going to resolve itself, to your point, in the next 12 to 24 months. What I think enterprise is really starting to discover is that you can't use AI to replace a really lousy process. You've got to actually have an AI first business process where you're rewiring your company around AI. And that's how you invest in AI in a responsible way. And that is really starting to ramp. We're seeing it in the financial sector, in healthcare, largely regulated industries first, but I think we're just going to see it explode from there.

John Furrier

>> You know, I'm kind of a nerd on competitive advantage, competitive strategy, so I have to ask, the Transformation Edge is about competitive edge. How do you view that, because when you're getting words like operating leverage, those are words that have been kicked around. We're talking about the ultimate dream scenario for operating leverage with AI.

John Furrier

>> Yeah.

John Furrier

>> So you have that coming into play. What does the competitive advantage of the future look like for companies that do take that approach, people who are watching or formulating plans for their business model transformation, and they all want to have a competitive edge. They want to drive revenue, keep happy customers, and what is that leverage, what is the key secret sauce?

Chris Stansbury

>> If I were to summarize it down to one word, I would say scalability. And so the network has been a huge limiting factor because it hasn't been scalable. Oh, I need another fixed pipe. Oh, I need another layer of security around all that. So to the extent that we can deliver that programmable layer that has that intelligence built into the network, you now, as the customer, we now, as the provider, have a network that's very scalable, that isn't capital intensive, that allows you to add more, add more, add more in a very digital efficient way.

John Furrier

>> So you love the AI infrastructure build out.

Chris Stansbury

>> We love it. More data centers, more connection points, more demand. More complexity, more demand for a programmable layer that allows you to consume that in a way that is on demand and digital.

John Furrier

>> So, Alkira is a strategic layer, not only to connect to the hyperscales today, but tomorrow connect to the other resource centers.

Chris Stansbury

>> Data centers, edge, all of it. It's really the unifying layer that pulls all of that together to one pane of glass for the customer. It's really magic.

John Furrier

>> Chris, it's interesting, in the past two years, I probably said the word computer science operating system on theCUBE more than in the 17 years we've been doing theCUBE. because what you just said is, when you have that layer of control plane, it's essentially scheduling resource management and routing. That's it. Okay, that's an operating system.

John Furrier

>> Yeah.

John Furrier

>> You're building an operating system layer on the network side.

John Furrier

>> That's right.

John Furrier

>> That kind of mirrors what we're seeing on KV cache, the importance. That's the darling in NVIDIA circles, KV cache, but it's inside the cluster.

John Furrier

>> That's right.

John Furrier

>> You're everywhere else.

Chris Stansbury

>> That's right, and again, historically, it was dumb pipes that other tech companies built around to enable those pipes to be secure and connect to each other. But it's inefficient. It's created just a lot of complexity. And so what we're doing is cleaning that up by saying, no, no, no, that should be native in the network. And we go from here.

John Furrier

>> And your customers are getting more demanding because they can have quantifiable reasons to see lag, latency.

John Furrier

>> Absolutely.

John Furrier

>> They can see it. We all know, when we see dot, dot, dot, thinking on our AI prompts, that's just slow. No one likes slow. No one wants a slower product.

Chris Stansbury

>> And AI, think about the early kind of AI engagements that we have as consumers. We're engaging with AI in a customer service agent at any particular company. If that agent has to go and look for data to answer your question, and that's a three -minute response time because you've got a slow network underneath it that's clunky and stitched together, that's not going to work. You've got to have that immediacy so that the AI works.

John Furrier

>> Yeah, and if the data's not available, you get the wrong reasoning engine. Then hallucinations can start, drift happens.

John Furrier

>> That's it.

John Furrier

>> A zillion things go wrong.

Chris Stansbury

>> A zillion things go wrong. So it's imperative that latency is kept to the minimum.

John Furrier

>> Well, Chris, great to have you on. I'm glad we went extra time on the transformation piece and congratulations on the earnings and the closing of the deal. We'll be keeping an eye on it. Thanks for coming in and sharing.

John Furrier

>> Thank you. It was a great conversation.

John Furrier

>> I'm John Furrier. This is the Business Transformation Edge series, this is also where the AI factory kicks in. Distributed computing is coming into the AI era. It's kind of the same, but it's different mechanisms. Low latency, the role of the network as an operating principle is becoming front and center. We're already seeing with NVIDIA every day on the mainstream GPU and AI infrastructure side, but as it moves to the edge, as it moves everywhere, the role of the network is critical. More of this is coming, we're doing our part. I'm John Furrier, host of theCUBE. Thanks for watching. Thank you.

Chris Stansbury, Lumen

(INTRO)

John Furrier

>> Great to be here.

John Furrier

>> networking is so hot right now. This is your DNA. You guys just had your earnings. You had an acquisition.

John Furrier

>> Yeah.

John Furrier

Chris Stansbury

John Furrier

Chris Stansbury

John Furrier

>> Yes.

John Furrier

>> And that is a huge signal to the market that this is not a bubble. It is not a bubble.

Chris Stansbury

John Furrier

>> That's right.

John Furrier

>> The edge, metro areas. When I hear people talk about metro POPs or metro factories, it kind of has that same trajectory of networking.

John Furrier

>> That's it.

John Furrier

>> You guys have a huge asset base. Share just some general stats on Lumen's position, because if distributed computing comes full throttle, that's going to make AI factories everywhere.

John Furrier

>> Yeah.

John Furrier

>> That means they're just nodes on a distributed computing network. Talk about that and the role of networking.

Chris Stansbury

>> You guys have been digging the trenches,

Chris Stansbury

>> paving the roads,

John Furrier

>> pouring the concrete of AI.

Chris Stansbury

>> Not most of it actually, but most of it has actually been the utilization of underutilized conduit that was put in the ground 25 years ago.

John Furrier

>> Yeah, so you're not digging, you're just connecting.

Chris Stansbury

John Furrier

>> What's the impact to customers on that?

Chris Stansbury

John Furrier

>> So you have north, south, east, west, and what that means is you can go anywhere.

John Furrier

>> Anywhere.

John Furrier

>> That's it.

John Furrier

>> And so people compare a lot of the AI bubble to the early days of the internet.

John Furrier

>> Yeah.

John Furrier

Chris Stansbury

>> That's it.

John Furrier

>> So share your thoughts on the demand curve for intelligence and why you're investing so much in the fiber.

Chris Stansbury

>> Yeah.

Chris Stansbury

>> And there's huge backlog by the way.

John Furrier

>> There's orders waiting to be fulfilled.

Chris Stansbury

John Furrier

>> That's powerful.It's not new, but the techniques are new.

Chris Stansbury

>> That's it.

John Furrier

>> The programmability and routing and policy, it's been around since networking was around.

Chris Stansbury

>> That's it, and quite simply, what are we doing? We're doing what other industries have done, we're cloudifying networking.

John Furrier

Chris Stansbury

John Furrier

Chris Stansbury

John Furrier

Chris Stansbury

>> That's right.

John Furrier

>> Yes.

John Furrier

Chris Stansbury

John Furrier

>> That's autonomous.Exactly. Exactly. That's autonomous behavior. That is it. That's agentic like adaptability and resilience.

Chris Stansbury

John Furrier

Chris Stansbury

John Furrier

>> Exactly.

John Furrier

>> That becomes, talk about your vision and how you guys see the sovereign AI playing out.

Chris Stansbury

John Furrier

>> And sovereignty is not country specific. It might be from a geography standpoint, but because of the nature of the hyperscale, it's a global footprint. That's what you're saying.

Chris Stansbury

>> Exactly.

John Furrier

Chris Stansbury

John Furrier

>> they got the keys to the kingdom because I interviewed the founders, very strong tech team, very excellent software layer. But you bring the network piece at scale.

John Furrier

>> That's it.

John Furrier

>> That's a huge deal for them because now they didn't have to do the biz dev on their side to lock in relationships with the hyperscalers and also the edge is coming on strong for them.

Chris Stansbury

>> That's it.

John Furrier

>> How did they factor into the plans going forward? It sounds very strategic.

Chris Stansbury

>> Yeah, so.

John Furrier

>> You organized around them?

Chris Stansbury

>> Yeah.

Chris Stansbury

John Furrier

>> And by the way, their multi -cloud fabric and what they're doing for the hyperscale works beautifully on edge.

John Furrier

>> It does.

John Furrier

>> Absolutely.

John Furrier

>> And you guys, as a network, you have points of presence all over.

Chris Stansbury

John Furrier

Chris Stansbury

>> It is.

John Furrier

Chris Stansbury

>> Yeah.

Chris Stansbury

John Furrier

>> Absolutely.

John Furrier

>> How are you going to leverage that strategic asset?

Chris Stansbury

>> Yeah.

Chris Stansbury

>> What's the plan, what's the focus?

Chris Stansbury

John Furrier

>> Yep.

John Furrier

>> Offer deterministic workloads, clear. But I think 2027, 2028 will be a massive discovery of, wow, this is how we monetize intelligence. That's it. What's your view of that?

Chris Stansbury

John Furrier

>> Yeah.

John Furrier

Chris Stansbury

John Furrier

>> So you love the AI infrastructure build out.

Chris Stansbury

>> We love it. More data centers, more connection points, more demand. More complexity, more demand for a programmable layer that allows you to consume that in a way that is on demand and digital.

John Furrier

>> So, Alkira is a strategic layer, not only to connect to the hyperscales today, but tomorrow connect to the other resource centers.

Chris Stansbury

>> Data centers, edge, all of it. It's really the unifying layer that pulls all of that together to one pane of glass for the customer. It's really magic.

John Furrier

>> Yeah.

John Furrier

>> You're building an operating system layer on the network side.

John Furrier

>> That's right.

John Furrier

>> That kind of mirrors what we're seeing on KV cache, the importance. That's the darling in NVIDIA circles, KV cache, but it's inside the cluster.

John Furrier

>> That's right.

John Furrier

>> You're everywhere else.

Chris Stansbury

John Furrier

>> And your customers are getting more demanding because they can have quantifiable reasons to see lag, latency.

John Furrier

>> Absolutely.

John Furrier

>> They can see it. We all know, when we see dot, dot, dot, thinking on our AI prompts, that's just slow. No one likes slow. No one wants a slower product.

Chris Stansbury

John Furrier

>> Yeah, and if the data's not available, you get the wrong reasoning engine. Then hallucinations can start, drift happens.

John Furrier

>> That's it.

John Furrier

>> A zillion things go wrong.

Chris Stansbury

>> A zillion things go wrong. So it's imperative that latency is kept to the minimum.

John Furrier

>> Thank you. It was a great conversation.

John Furrier