Transcript

Judah Sanchez: You’re listening to Futureproof, a Pod on the Quad production. My name is Judah Sanchez.

William Burger: And I’m William Burger.

Judah: Together we’ll be discussing emerging technology, modern business strategy, finance, and the global economy, all in relation to the future jobs and careers we’ll be stepping into. This is Episode One. Welcome, and enjoy the show.

————————————————————————————————————————————

Judah: Today we’re talking about data centers. In the U.S. alone, over 4,700 data centers have been built in the last year, mainly to support the massive demand for AI computing power. Here to talk with us about them is our guest Ann Davis Vaughan. Ms. Vaughan is a former Wall Street Journal energy reporter, a columnist for the Silicon Valley news publication, The Information, and author of the forthcoming book Gigawatt. Welcome, Ms. Vaughan.

Ann Davis Vaughan: Thank you, Judah and William. I’m happy to be here.

William: All right, we’ll get straight into it. Recently for your book Gigawatt, which is about energy and data centers, you went on a road trip through West Texas and the panhandle researching these huge mega-projects. Can you paint a picture of what you saw in places like Hereford and Castro County that surprised you?

Vaughan: Yeah, absolutely. To take a step back and describe my book a little bit, it’s about the rise of artificial intelligence and what it takes on a physical level to really produce it. AI is not a technology that happens in the cloud in the sky. It’s in big, heavy, capital-intensive supercomputers that are data centers. The kinds of data centers we’ve had in the past for email and computing and cloud are pretty big and they’ve been popping up all over the country. But what we’re looking at for artificial intelligence is so much bigger, astronomically more energy-hungry and resource-intensive, taking up land masses approximately the size of Central Park.

If you wonder where there is a lot of energy, where there is a lot of land, and where there is a willingness to build fast, you need to look no further than Texas. This state is not the only place where AI is being built, but it is quickly emerging as one of the largest magnets for AI computing development as well as energy development. There are some estimates that Texas is going to end up getting about 30% of the future AI supercomputing data centers that are coming. I’ve been traveling the country to see what it looks like where a lot of them are being built, but the trip that you’re describing I took just about three weeks ago through West Texas and up north to the Texas panhandle.

***

Judah: Awesome. You know, there’s a saying everything is bigger in Texas and it seems like a lot of these companies that are developing these data centers are really taking advantage of the open land. You actually previously said that Texas is attracting about a third of all AI data center investments. Why do you think Texas is the “Disneyland of energy” for AI companies?

Vaughan: The person who said Texas can provide the “Disneyland of energy” is a renewables developer, Sheldon Kimber of Intersect, and I just wrote a column about him for The Information. His company Intersect has just been acquired by Google for $4.75 billion in cash; it was a remarkable deal and quite a bit of what he’s doing is in the state of Texas. The reason that he calls Texas the Disneyland of energy is because we have really become an “all of the above” energy state. It’s a huge state with its own self-contained power grid. Texas has always been about providing Texas-sized electricity, too. It is an ideal laboratory to try almost any form of energy and there are a few reasons for that which become vital to technology companies that are in what they deem to be a race to be among the winners in AI.

William: That’s fascinating how major of a scale all this is happening. I think a lot of people are hearing about these mega-projects all over these rural areas, and I know something that’s also been in the news is their usage of energy and water, especially in these rural locations, and how they could be straining local infrastructure. Can you describe some of the conflicts between these major data centers and their rural communities and how that affects everything from agriculture to just the lights that people have in their houses?

Vaughan: For sure. A data center is like a refiner of electricity. It takes electricity, runs it through circuits, and produces data. If you use a very large quantity of very powerful AI chips and you put them under one roof, they work together and process data in parallel. They share information from one chip to the other and act like a single brain. That is conceptually why an AI data center is so energy intensive. Over time, data centers are getting a lot more efficient with how they use water. To put it into context, the water in American data centers that we have built today only uses about 8% of the water consumed by the U.S. golf industry.

Of course, the buildings we are putting out there in the future are more like gigantic clusters of huge computers. Even if they’re more water-efficient, they’re bigger. So there is a big question about how we manage water, but it doesn’t necessarily always fall right at the site of these big data centers. The reason it’s more efficient is they’re figuring out how to do what’s called closed-loop cooling to manage the heat that comes off of all the chips. That does not release the water; it recirculates it.

***

Judah: Okay, we’re going to shift to the jobs. When these massive complexes get built, what kinds of jobs are created?

Vaughan: There’s a boom in jobs for skilled trades. These are carpenters, electricians, mechanical professionals, and jobs like pipefitters. There is a huge amount of unionized labor actually going into a lot of these data centers. There is a shortage of this skilled labor because the demand all of a sudden is so great. In Abilene, Texas, at the data center where I was visiting, there are about 7,000 skilled workers there every single day. You need very skilled labor to build the power electrical infrastructure that goes inside these complex facilities or the cooling piping. This is skilled, highly engineered infrastructure.

The aspect of the hiring boom that people don’t see is how many other jobs are getting created in the broader set of companies that are supplying everything AI is consuming. AI is consuming steel, fiber, gas turbine equipment, and cooling equipment. All those companies are now expanding their facilities to meet this moment. There’s a pretty durable runway for a while.

William: There’s definitely an irony there with the AI data centers creating jobs while AI itself is eliminating jobs elsewhere. More personally, what was your take on this trade-off in the next decade or two as AI continues to develop at this exponential rate?

Vaughan: I think that we will see new jobs get created that we can’t even have imagined. That is scary for people because you don’t really know how it’s all going to turn out. We’re at a place right now where we can’t quite imagine who it might replace. As much as everybody wants to go fast on AI, and things are going blindingly fast in terms of money being spent, there are also shortages of equipment, shortages of electricity in some places, and shortages of people to build it. There are also just a lot of kinks to be worked out in the product of AI itself.

Judah: For high school students thinking about careers, whether in energy, tech, or trades, what opportunities are emerging from this transformation?

Vaughan: I think it’s a really exciting time for your generation. The big picture is that we are probably entering an electricity supercycle. If you want to solve problems, you could jump into the engineering and technology space. You could help people understand it by giving these trends more scrutiny in policy or journalism. There’s also a lot of startup activity out there in sectors that have been through some tougher times.

William: All right, thank you so much. Those were the main questions. We’re going to leave it open to you. Is there anything else that you’d personally like to say to people or want people to know about the future?

Vaughan: I think one of the things I’m trying to do with the book is to give people a high-level view of all the different parts of the economy that are changing as a result of the AI boom. There’s a lot of misinformation out there about exactly what is happening. People kind of look at their own world and they see things that could go wrong. We need that attention to what’s happening in our world because it is a big transformative time. But I would ask questions if I were you. When somebody gives you just an all-doom or all-positive picture that AI can either ruin or save the world, ask if there might be some nuances in between that would be worth keeping the conversation a little bit more fact-based to cool the temperature down. There are a lot of different ways that we can contribute to this phenomenon and make it work better for us.

Judah: Is there anything else you’d want to talk about?

Vaughan: No, I just think it’s great that St. John’s is looking at some of these forward-facing industries and that you’re asking a lot of questions so that you can figure out opportunities that are right there in front of you.

——————————————————————————————————————————————Judah: Music and sound effects for this episode were provided by Pixabay, featuring the work of Dimmysad, Dragon Studio, and Universfield. Special thanks to our guest Ann Davis Vaughan of The Information. Futureproof is a production of the St. John’s Review. Copyright 2026, Houston, Texas. I’m Judah Sanchez. Thanks for listening.

[/sidebar]

This story was originally published on The Review on April 7, 2026.