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AI’s hunger for compute is sparking a global surge in data center investment—but the real story is what’s happening underground. In Malaysia and across Southeast Asia, sovereign ambitions, grid pressure,and ESG scrutiny are colliding with hyperscale demand. We’ll explore how the data center gold rush is playing out on the ground—and what it takes to stay ahead in the age of AI-fueled infrastructure.

Data Centers: The New Global Arms Race

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In this episode of Leadership Next, cohosts Diane Brady and Kristin Stoller speak with Kate Johnson, CEO of Lumen, about her bold effort to reinvent a legacy telecom as the digital backbone of the AI era. Johnson shares how Lumen is capitalizing on its vast fiber network to support the explosive data demands of artificial intelligence—and how partnerships with innovators like Corning are helping supercharge that capacity. 

Johnson opens up about the cultural overhaul she led inside the company, shifting Lumen’s mindset from “play not to lose” to “play to win,” and implementing leadership frameworks like Brené Brown’s Dare to Lead across tens of thousands of employees. 

She also reflects on her personal evolution as a leader, the phases of AI adoption she sees ahead, and why she believes human creativity and empathy will remain central in an AI-driven world. 

The CEO Turning a "Sleepy Telecom" Into AI’s Fiber Backbone

Photo Courtesy of Kate Johnson; Graphics by Fortune

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Lumen’s Kate Johnson on redefining infrastructure for the AI economy—and the cultural rewiring that made it possible. 

When no one was looking, the global semiconductor business became a smash-mouth, no-tariffs-barred affair. But in an age of AI, business is still (very) good. The founder and CEO of one of SoftBank's newest multibillion-dollar acquisitions weighs in on the future of AI compute, the changing cast of industry power players, and the shifting geopolitical landscape ahead.

Iron in the Fire

Peter and Daniel. So there's a lot of excitement about what AI can do, right? That's why we're here. But none of it's possible without the right infrastructure and the right chips. The competition to build the next generation of AI hardware isn't just a business story, it's a strategic one touching on everything from investment and innovation to geopolitics. Today we're joined by one of the most respected leaders in technology and semiconductors to help us understand what's at stake and where the future is heading. So please welcome Renee James, chairman and CEO of Ampere. Hi Renee. Good to see you. All right. Thank you for joining us. So You worked at Intel for a very long time, um, and you worked with the great Andy Grove. You were for a long time, you were first as chief of staff, is that right? And then you, you know, right before you left Intel, you were the president of Intel. So, When you look at that, I promise I will ask you questions about your company Ape, which was acquired by SoftBank for $6.5 billion earlier this year, but I promise we'll get there, but I have to know as an, as an Intel vet. What would Andy Groves say about the state of Intel today? Thanks. Yes, um. He would be very disappointed. Why? Because it's an industry that Intel um invented literally invented the means by which you fabricate modern semiconductors, um, the what we think of as fabs that everyone likes to talk about and weirdly wants to build everywhere. Uh, and the process that goes into them was pioneered by Intel, developed by Intel. The modern transistor technology was invented by Intel, um, the first modern CPU that powered, you know, computing and the entire PC mobile, everything. Was Intel. So when you think about that, and these were people who left Fairchild because they had a different view of how the future could be and started with venture capital, if you can believe it, in the late 60s, 6869, this is, you know, their life's work and then to see Intel fall behind. Um, a company that was a great partner, has been a great partner, still is, I think of Intel forever, my supplier TSMC was started in collaboration with Intel, um, because we needed an additional source. So you look at it and you think, wow. That's kind of scary and sad. And Intel is not that sort of enzymatic uh uh uh actor that it was in in its heyday is, is kind of what you're inferring. And a lot of the technology that we use today, I mean, the Mellanox interconnect technology of Nvidia was invented at Intel and spun out there, you know, my company, uh, not just me but several of the key leaders, we're X Intel, we built every server product that built every data center. it started, you know, all of this cloud stuff. So, you know, a lot of good came out of it and a lot of spinoff companies, you know, the modern way that we think about building silicon and semiconductors that we all take for granted like a miracle occurs. You turn something on and it just works and like, you know, 70 billion of something you don't even know what they are is going on and on a little piece of silicon and we don't know, you know, it just works it it truly is miraculous, but then you think about the state of the company today and And I, I wish them recovery. I really do. I think they're super important to global semiconductors. They're super important to the future of where we're going because at its base Intel is the company that invents the future of transistor. still today, even in their current situation, super important. We will come back to the sort of global implications of that in a second, but I do want to, I do want to talk about Amper for a second. So Renee, you're one of two women who run semiconductor companies. It's extraordinary. And then you I'm happy that there's someone else now. That's right. That's right. And you went even further because you said, I'm going to start one. Like that isn't exactly how that went, but yeah, I think Andy said, what are you doing with your life? Why don't you start the next one? So what what what leads one to start a semiconductor company because I've always gotten the sense that um sort of like an automaker, you can't just turn around and it's not exactly a software company, you know, you can't just spin it up overnight. You need a lot of capital. Yes, um, well, so first of all you have to have a passion and a vision for where you think things are going because you, you know, you're not, you wouldn't start a company at the kind of the scale of a CPU company or GPU company, um, from the ground up at this point in the history of semis given the the hurdle rate and the investment rate and costs, um, unless you had a passion for doing something that hadn't been done before because you know you're not gonna start a company to like compete with Nvidia. That's ridiculous. Um, so we said the problem that we hadn't solved, the thing I was passionate about after 30 years of building microprocessors, was we have always, whenever we got into trouble we would just say like, oh, you know what we can do, we'll just put more power onto it. We can just release the power and I'll get higher performance or we'll put down more transistors. I mean, we did a lot of things that at the time it didn't matter. It didn't cost as much. It was, you know, no one was going to freak out that we went from 350 watts to 400 watts to, you know, whatever. I mean these were conscious decisions to change because you have to change the spec on what the server is and what goes into the data center and all that stuff, but more was more, more was more and you could get paid for it. Um, so the thing we didn't do was something that we knew about. I mean, good and physicists know that at some point, you know, you need to constrain the power and figure out how to improve the performance through other techniques, and that's a lot of R&D and a lot of thinking. About thinking differently, thinking differently about how we designed the architecture of X86 for the last 20 years that we had been working on it, um, before I was president until I ran R&D for a long time, so we spent a lot of time thinking about this, so we, um. I said, you know what, that's what I want to work on. I want to work on how we build out what comes next, knowing that not AI in the way that we think of it today, but we were working on machine learning and everything already. We knew that was the next big thing. We knew that cloud computing, the way that the cloud used software was different than the way that the enterprise consumed software, like in this linear scaling, always on, always on demand. Um, and, and the microprocessors that we had built were meant to turn on and off in a way to be efficient for different workloads but not for the cloud, so that was our thesis and um. I gathered around people that were retired or that had worked for me before and I said we should do this and they're all like, you've lost your mind because we had built like 80 microprocessors, 80, and they were like, really, are you sure? I'm like, we can do this. If not us, then who? And then Andy says. He was still alive and not really that helpful in the sense that he was like, we taught you everything, you know, this is what we what Bob and Gordon and I did. This is what, you know, this is, this is the history of Silicon Valley. Someone has to do it, so that's what we did and I was really fortunate because the Carlisle Group, who doesn't. Usually do venture um back to us in our first round um and then we had a couple of strategic, our largest strategic being Oracle over time um and we ended up raising billions of dollars over the course of the last 8 years and um last month announced that, um, SoftBank Group is buying the company for $6.5 billion. In cash. So let's talk, let's talk a little bit about that. So what. Some folks were scratching their heads when that deal was, was, was announced. What does SoftBank give Ape? What does Ampere give SoftBank? Um, well, of course the deal isn't closed, right, so we're in the regulatory period, but in general, um, we've pioneered, we have a lot of patents and a lot of technology we've built, um, 5 generations of product already that have been deployed into major hyper scale data centers, um, how to build very, very high performance in an air cooled, meaning 500 watts or less envelope, um, and we could release the power and use liquid cooling. And go even, but the performance is that of like an AMD leading edge processor today we have integrated AI acceleration inside of that envelope. We can add additional functionality on and only release the power, you know, 50, 100 watts. So I think that that whole thing allows you to build out a vision of AI, you know, scale data centers that are more efficient over time. Um, we were, we are an arm architecture licensee, so a sister company in the SoftBank Group, um, so we had taken an architecture that's inherently low power but had not been known for the highest performance, and we had, um, invented ways to bring it up to. The level of, you know, that kind of performance, and I think that it's very synergistic with their overall vision and the mission that Masasan has for Stargate. For sure, for sure, and, and we will get to that in a second. I, I wanna ask you, I want to come back to the, the geopolitics question so. When you and I were talking about Intel previously, um, you were expressing to me kind of the importance of that company in the overall ecosystem, um, honestly, in the US, but, but in as as outdated the terms as it is with the West. Um, we are in a very US versus China moment in time right now and you're very concerned. Um, what is the future of SEI right now and What's it look like if we don't get it right here in the UK? In the UK, um, what do you mean by don't get it right in the UK? What, what is the landscape, right? What is the playing field given these tensions and you know what, how do we remain competitive given that sort of binary choice, you know, semiconductors historically have been a global product that have been available globally, um. That you know the predominance of semi semiconductor business is distributed around the world both in supply chain and design. Um, some of the great design teams in different segments of semiconductors are in Europe, and many of the industrial companies in Europe do their own semiconductors, so super important. Um, the predominant and and currently an EUV only lithography equipment is from Europe, so I think we have a long history of a very open design design and manufacturing ecosystem. I, I do think that there is, you know. An importance in the global nature that this business has always been, it was never just a US business that went global. It was global from day one. So I think we have to think about where the people are who do this, how, how the, you know, how it moves, how it affects every segment of the economy in all these different countries, because computing is not just about people doing office work anymore, it's how we live our lives. It's everywhere, right? So, um, I think as long as we're conscientious about open market and and how we move forward on that I think that's important. The China thing is a separate situation because China has capabilities that are self-contained and to some extent I don't know what direction that will go it, you know, I have always participated in a global market, so it's hard for me to speculate on what that would look like, but it's the US and. Um, Taiwan, Southeast Asia, European, you know, design capability for global semiconductors is profound. I mean, it is hard to imagine doing, you know, some level of networking and mobility and everything without teams in France, for example, right? Like there's just specialties around the world, Poland. Right, right, I will come to the audience for a question in just a moment. I wanna just quickly ask you to tell me, you know, does AP have a role in the Stargate project? And if so, what? Um, well, I can't comment too much on that, um, but as we said in the press release, we, we do have a role in that, so yeah. All right. All right, let's go to the audience for questions. Questions for Renee James. They're all wishing they were in semiconductors, like, really? All right, well, I have, oh yes, right here up in the front, just wait, wait for the mic to reach you. Way up here. It's on the couch. And as always, your name and who you're with when it comes to you, OK? Thank you. I'm Doctor Shiva, I bank, and like I said yesterday, we're building a data center and also I'm from Sri Lanka. I don't know whether you all know Bain graphite, the pure graphite is in Sri Lanka and only 1% is exported. And now there are people looking at graphene, which is the GPU. Uh, you know, for graphene chips, you need graphite. Is there any, you know, experiments that you are doing or what's the plan? Yeah, so we don't do base level. Um, Ampere is a fabulous semiconductor company unlike Intel. We don't do um base level metallurgic, um, material science at MPR. We do design, advanced design and IP um development, um. So I am sure there are people looking at that, but most of that work is done in process fabrication, um, in conjunction with that. So at TSMC and Intel and places like that. Yeah. We have a question. Thank you for your question. We have one right back here, yes, your name and who you're with. Uh, I like, yes a business school. So I had a question about the overall ecosystem around CPUs and GPUs. So where do you see this going? Nvidia is now very dominant in the GPUs. Um, you know, X86 is still powerful in the CPUs. Where, where do you see this in 5 years, you know, Nvidia, ARM, everything. Yeah, thanks for the question. Um, in the, in the, you know. GPUs, as you know, grew out of gaming. So a large portion of the GPU, you know, the shaders and the things you need for rendering and gaming aren't used to um train large language models. So, Um, while it's a lot of horsepower, it isn't the only way that you can do the computation required for AI. And in fact, um, as we've discussed in multiple roundtables here, um, as we go to smaller models, as we use, let me say the appropriate AI technology or machine learning technology for the job at hand, you might just run it on an enhanced CPU. In fact, that's probably the most efficient way. So all the CPUs are being enhanced with AI acceleration, and we have a product that we've talked about Ampeer1 Aurora, that actually has um the AI functionality because we have 512 cores you can put, you know, AI cores and compute cores and into that's one of the great innovations that we've been working on. Um, so I think that 5 years from now what we're going to see is a convergence of AI and compute and architecturally there's an underlying thing that is super insular, uh, Silicon Valley Wars kind of thing which is the micro architecture of computing. Will it be X86 or will it be something else? Um, Nvidia is an ARM licensee. Nvidia builds their things on ARM as well. I do think given the progress we've made and now under our new ownership that um our proposed ownership that that arm is looking like a long term it's the architecture that Apple uses they're in a licensee that Samsung uses that Qualcomm uses that Broadcom uses. And um because of the developer community being on phones, laptops, you see, you get this bulk of developers that know that environment so I, I, I think the future is relatively bright there. And of course, SoftBank owns arm. Yes, right here. Hi Seth Dober in Quantum AI and Infinity Adventures. Hi Renee. Um, so one of the biggest challenges in, in AI, especially training is not necessarily compute, it's the distance between compute and memory. Are you guys doing anything in that space? That's my favorite topic. Oh my God. See, I, yesterday at lunch I was like, I love that guy. I, uh. Yes, Seth, of course we're working on that problem that we've had for the last 30 years. Um, if it exists, if it, if it was a problem in mainframes, it's still a problem. Um, of course there's high speed memories, but one of the things, of course I, I'm not gonna reveal how we're doing it, but all of us have been working on moving memory closer, staging memories, uh, flexible different kinds of memories that you might want to put in and out depending on costs, so there's a bunch of things that we're doing to, um. Deal with moving the workload in and out more efficiently. It's not just memory, it's a lot of the die to die interconnect as well, as you know, right? So we've done a lot of innovation. We have patents in it and die to die and how you move things across, but you know, the other thing that's quite fascinating only to me but probably not the rest of this room, but maybe to you, the way you lay out the chip where you put computation versus IO actually matters because it determines some of the. Length of travel and so we've been very attentive to that as well. Thank you for your question. I feel like I saw one more. Yes, was just my memory. I wanna talk about semiconductors. Come on now. Oh yes, right up here. Oh yes, your co-host. Yes, that's right. Just wait for it right here, Maddie. Thank you. Hi Renee, Jason Del Ray from Fortune. Um, I spent a lot of time, probably too much time thinking and reporting about Amazon, and I'm curious what you see as their potential future in the chip space. Um, I know they've made a lot of investments and are you bullish, bearish on them in the future, and either way, where, where do you see them fitting in? Yeah, so, um. Thank you for that question. It's, it's Amazon uniquely has an outstanding team that they've had together for years, and one of the hallmarks of a successful semiconductors is how many generations has a team done together, and the answer to Amazon is a lot, and they also use ARM architecture and have been quite successful in building chips, as has Google, by the way, um, that are specific to the pathology. They have a really unique way of accelerating data inside their own network and they're and they have an outstanding silicon team that's been able to build, you know, really great products that for their own use. I think given you know their their might and their team and everything that they'll continue to be very successful with that strategy. I, you know, the hyper scalers have the wherewithal to. Do that kind of thing, but the other half of the market is the enterprises of the world that need to use AI that don't have it, and that's where I think, you know, commercial chips have to fill that gap and they're not all gonna build out massive Nvidia infrastructure either, right? So there's still an enormous market opportunity and let us not forget, despite the fact that we never talk about it. Pure computational data, non-AI is growing as well at a double-digit kegger. So there's kind of a, there's other stuff going on as well. Thank you. Everyone, the fantastic Renee James.

AI-powered software development is evolving fast, but how far are we really from AGI, artificial general intelligence? Poolside CEO Jason Warner will discuss the limits of current AI technologies, the use cases most likely to change our world, and we’ll ask the question: What will it take to get to AGI—and is poolside ahead of the curve?

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