But AI is a matter of national security and we have to think through what's the right balance of getting a national framework that can help us go fast but still respect, you know, sort of the local rights and values, and that's complicated. Legacy networks, they're just not big enough, fast enough, smart enough, or secure enough to support the needs of AI. The new corporate workforce includes these autonomous workers called AI agents and they live in data centers and they have to be connected to the rest of us.
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Welcome back to the Building America podcast, a show that explores how our nation is building better for the future. I'm James Hman, the deputy opinion editor, and over a series of episodes, we are examining how artificial intelligence is just as much a physical story as a digital one. In this episode, we're looking at how one legacy communications giant pivoted from traditional telecom to AI infrastructure, building what its CEO refers to as the nervous system of AI. That company is Lumen Technologies and joining us is its CEO, Kate Johnson. Kate, welcome.
Hi, it's great to be here.
For those who aren't immersed in this world of AI infrastructure, what do you mean when you say it's the nervous system of AI?
Well, I think networking was traditionally thought of as just pure plumbing, dumb pipes, you know, connecting point A to point B so that you could transport data. But in the world of AI, which is incredibly complex, you need to be able to transport data from anywhere to anywhere. And so you really need the ability to program the network to do that for you. And essentially, if you think about the nervous system as the conduit or the pipes connecting all the data centers and the brain is the digital platform for orchestration, basically the control plane or ability to do whatever you want the network to do in support of your AI ambition.
So what actually happens if the physical network that you're talking about doesn't have enough of this central nervous system?
Well, I think legacy networks don't have this capability. They don't have the intelligence layer that I'm talking about. They're simply static connections, you know, fixed point A to point B. And the reason why that doesn't suffice, James, is because AI is not operating in a single place. AI needs to operate in multiple places, right? It operates in buildings, it operates at edge points, it operates in data centers and in public clouds. And it thrives on ingesting data and it creates data when it makes insights, right? So, it's all about that data movement. The interesting thing is legacy networks, they're just not big enough, fast enough, smart enough, or secure enough to support the needs of AI. AI has to have the ability to call data in from anywhere, process it, and then send its insights to anywhere.
So, it's asking for that adaptability and flexibility from a network that traditional networks can't deliver. So, it's our hypothesis over the past couple years as we've been transforming the company that a programmable network is in support of the growth of AI and it's proving out to be on target.
I'm so glad that we're having this conversation because I think so many people when they think AI infrastructure they think like data centers but this is in many ways as or more important. You use the plumbing analogy but, you know, you think about your company's literally out there building thousands of miles of underground fiber routes and fiber huts. In practice, what does that look like? Help people visualize what it is that Lumen is doing.
So from I guess it's 2025 to 2030, we're going to have a 10 times growth of data centers in the United States alone. That is a massive expansion. And a data center sitting alone without being connected is useless. It's just a brick.
Right. So Lumen, we have the largest fiber network in the country. We are growing it very rapidly. We're currently a little bit north of 17 million fiber miles in our network and by the end of 2031 we will have 58 million fiber miles. So there's this massive expansion of fiber networking in support of connecting all of those data centers because those data centers are where the AI lives, right? The new corporate workforce includes these autonomous workers called AI agents and they live in data centers and they have to be connected to the rest of us. You've got people, data applications, and AI agents. All need to be connected. We've got the network to do that. But what's more, we've invested in this digital layer to make the whole thing programmable, which gives businesses optionality in terms of how they design their AI architecture and gives them flexibility to really be able to adjust to all the different factors in the environment.
What do you say to folks who worry that there's sort of like a boom and bust cycle, that you hear the word bubble, but you're building out just a breathtaking amount of infrastructure, obviously very capital intensive, but it is so important to the workforce of the future? How do you respond to people who say, wow, that's a lot of investment right now and what if it...
Yeah, what if all this stuff doesn't quite pan out as we hope?
Well, so the numbers are daunting because they're kind of bigger and coming at us faster than we've ever experienced in our lifetime. You know, trillions of dollars worth of infrastructure investment. And it's not just networking, obviously, it's the build out of the data center with GPUs and energy and networking. So there's a lot there, but I think there's kind of two angles. The first is we see traffic on the network and the composition of data is growing dramatically from AI agents itself. More than half of the traffic on the internet today is generated by these autonomous workers, which is really sort of staggering if you think about the fact that ChatGPT was just released for the first time November of 2022 and in the three and a half years AI agents are comprising more than half of internet traffic. That's pretty astonishing.
And a lot of that internet traffic is running on Lumen's networks.
That's right, that's right. So we see this huge growth in data traffic for sure. So we can validate that the demand's there for networking for sure. But I think also if you think about the hyperscalers and the neoclouds and the companies that are building the models, they also understand what AI needs in terms of ingesting and proliferating and generating data as well. And they're building ahead of the demand curve a little bit. They see the demand, but they're building that supply side for the AI economy because it takes so long. So, what we're seeing is these companies making these huge investments today so that tomorrow and beyond they're prepared to be able to support enterprises as they need to consume these services.
To what extent, bringing it back to sort of the focus of this series, is it then a physical story as much as a digital one?
Yeah. So the interesting thing is infrastructure just always triggers everybody's mind. Physical, physical, physical. Right, and you know in the ground it's something that I don't want to have to think about it, I only think about it if it doesn't work. But the truth is infrastructure needs to be smart now, it needs to be intelligent. So the table stakes for entry to play in this space is the physical part. And since I became CEO in '22 to now and then 2031 and beyond, we will have more than quadrupled our physical network, which is really kind of profound. It's the greatest expansion of the internet at large ever.
Right, and that's important because you have to be proximate to where those data centers are, right? You have to be right near it. We'll be covering more than 90% of data centers by the end of 2026, we'll be right there for direct on-ramps into those clouds, and the GPU capacity that is so precious.
It's funny. You started at Lumen, I guess, right before ChatGPT came out, right? I mean, this has been such a...
Yeah, I started the same month.
Three weeks before it came out was my first day. Yeah, I think they call it good timing. And the whole reason why I started was because of this physical asset. Because it was so impressive. But the real opportunity that I saw was digitizing that physical asset and having the hunch that the pipes need to be there, the fiber needs to be there, but if we can't make those pipes intelligent and able to respond to the needs of the environment above the ground, then that's not going to serve AI well. And AI needs all this data. So let's go after that. Just a couple of examples. As you build out data centers you need to go where the compute is. Compute is very precious, right? Those GPUs are very expensive. You want the data to wash over that as quickly as possible. You don't want anything sitting idle because that's just too expensive.
But if you're not able to build a data center in a certain area, or if you have a workload that is taking up more than its fair share of capacity, wouldn't it be great to be able to move the workload to wherever the GPU capacity is today? And that's what a programmable network allows you to do. The same holds true for energy. It's a quest for clean energy, affordable energy surplus, or at least availability. And when you have workloads that are consuming more than their fair share, wouldn't it be great to move those workloads to where there was a surplus? And in the legacy network where everything's static and it's fixed, you can't do that. But if you have a programmable network, which is basically digitizing that physical infrastructure we talked about, you have the ability to move the data wherever it needs to be economically, security-wise, or from a GPU capacity perspective.
I love your point that infrastructure is one of those things a lot of people only think about when it's not working or when it's broken. We hear a lot about how hard it is to build in America today. From where you sit, what is the one thing America needs to do to build better?
