America Is 10x Behind China in AI Infrastructure — The CEO Building the Solution

**Hannan Happi** (0:02)
China adds 540 gigawatts of power to the group per year, so more than 10 times our capacity. So that means that China, if we consider China to be our rival in this AI dominance race, has 10 to 11 times more capability and capacity than we do to build infrastructure and bring that online.

**Rachel Warren** (0:31)
That was Hanan Happy, co-founder and CEO of Exowatt, on why the AI race is less about algorithms and more about electricity, and why the US is dramatically behind where it needs to be.
I'm Motley Fool analyst Rachel Warren. The conversation about AI almost always focuses on chips and models, but Hanan argues that the real bottleneck is something far more physical. He joined me to discuss why a single year of grid delays could cost a hyperscaler $12 billion in missed revenue, why communities across the country are pushing back hard on data center development, and what investors watching the AI build out should actually be tracking as the capital flows in. We hope you enjoy.
Hello, everyone, and welcome back to Motley Fool Conversations. I'm Motley Fool analyst Rachel Warren. Today, I'm joined by Hanan Happy, the co-founder and CEO of Exowatt. Hanan brings an incredible deep tech background to the table. He studied mechanical engineering at the Technical University of Munich, later attended the Stanford Graduate School of Business. Prior to launching Exowatt, he held key engineering and leadership roles at industrial and tech powerhouses like General Electric, Accenture, Tesla. He also co-founded Valancy, an autonomous hardware and logistics company. But now he's tackling one of the biggest challenges facing the tech sector right now, is company Exowatt, which has captured the backing of elite investors like Sam Altman, Andreessen Horowitz, is purpose-built to power AI, delivering dedicated renewable energy to the engines of modern intelligence. Exowatt calls its new energy generation category On-Site Firm Solar. It's designed to bypass the years long utility grid delays that are stalling the modern AI buildout. Hanan, welcome to the show.

**Hannan Happi** (2:07)
Thanks for having me, Rachel.

**Rachel Warren** (2:09)
Absolutely. The last few years when I think a lot of investors talk about AI, the conversation is very much focused on semiconductors, networking capabilities, but you've argued that the next massive phase of AI investment isn't actually happening in software, it's happening in that physical infrastructure. So walk us through that. Why has the biggest bottleneck in the AI boom suddenly shifted from the silicon to the raw physical infrastructure?

**Hannan Happi** (2:34)
Yeah, absolutely.
So if you think about just a couple years ago, the largest data center that we had in the United States was about 100 megawatts in capacity. And that was considered very large and the rack density was in tens of kilowatts, and a building block of a data center was maybe 10 to 20 megawatts. And fast forward just in the last couple of years, the building blocks for data centers have scaled up to in the order of 300 to 500 to even 700 megawatts, the building block. So you could argue the building block of a data center is now five times larger than the largest data center we had in the country a couple of years ago. And the data centers themselves are now on average about a gigawatt, and there are some that are in the order of 10 gigawatts. And to put that into context, a gigawatt data center essentially is consuming the equivalent of one million US households' worth of energy. So you're basically saying, I am building a city from scratch for a million people, and I'm trying to do that as fast as possible because I want to stay in the AI race, I want to have the best model, I want to be competitive. And this is where we're past the idea of like, how do I write the best LLM algorithms or models? How can we overcome the chip shortage? Because the chips have become better too and more powerful, even if they have become more energy efficient. But they're still consuming a lot more energy as a total.
And now we have to build power infrastructure. And as a country, we haven't had to build massive amounts of power infrastructure for the last couple of decades. We haven't had much of a load growth in the US. And now we do. And data centers are eventually going to contribute or be taking about 9% to 10% of total energy produced in the US, the grid capacity. So we are in a mad rush to build power infrastructure. Building power infrastructure is not trivial. It's not like software that you can write code and it just scales infinitely. You have to move metal. You have to move concrete. You have to move earth. You have to do all sorts of permitting and construction and move workers. And we just don't have those capabilities at scale in the country. And what we're trying to do at Exewat is come up with a formula that allows us to do something in a factory setting with tight control over cost, tight control over the speed of execution and try to scale that as fast as possible to address this power gap. But there's a massive, massive power gap. And I think everyone's scrambling to figure out how to cover it.