Jensen Huang Says AI Needs "1,000 Times More Power Than We Currently Have." These 3 Industrial Stocks Will Deliver It.

Speaking to a Stanford University computer science class in May, Nvidia (NASDAQ: NVDA) CEO Jensen Huang raised eyebrows by saying, "The amount of energy that we need for [AI] computing is likely probably 1,000 times more than we currently have." He didn't add any additional detail to his mental math and even conceded, "I wouldn't be surprised if we're off by a couple orders of magnitude." If his goal was simply to provide some tangible perspective -- for effect -- on what the energy industry needs to accomplish in the foreseeable future, then mission accomplished.

The projected scope makes sense. Also in May, Goldman Sachs predicted that the power U.S. data centers alone would need would more than double between 2025 and 2027, from 31 gigawatts (GW) to 66 GW. At peak usage, this would push the domestic AI industry's consumption from just over 4% of the nation's total power output to well over 8%. Extending this trend, Bloom Energy predicts artificial intelligence could be using up to 12% of the United States' produced electricity by 2030, and it would still just be getting started.

The same dynamics are taking shape outside of the U.S. as well, of course.

It's an opportunity, to be sure, but only for companies already ready to capitalize on it. To this end, here's a closer look at three industrial names already seeing the upside of the surge in power demand.

1. GE Vernova

GE Vernova (NYSE: GEV) is the former power-generation arm of industrial titan General Electric, which began splitting itself into smaller, more manageable pieces in 2021. This particular offshoot makes everything from wind turbines to nuclear reactors to hydropower systems to power grid solutions.Its red-hot equipment right now, however, is natural gas turbines.

Originally intended for utility companies, these power plants -- capable of producing anywhere from 34.5 megawatts to 571 megawatts of power -- are ideally suited to power data centers due to their scalability, ability to be throttled as needed, and relatively small footprint. Just as important, on-premises power generation means AI data center owners/operators don't need to wait for time-consuming (and often costly) connections to a power grid. That's why PwC believes the United States' data center-driven demand for natural gas could easily quintuple between last year and 2035, with an outside chance of further growth taking shape even sooner.

GE Vernova won't supply all the turbines linked to this surge in demand for natural gas. With a companywide backlog of $176 billion (nearly two-thirds of which is gas turbine-related) versus 2026's expected revenue of about $46 billion, however -- and a gas power equipment backlog that grew from 100 GW to 116 GW in Q2 alone - this company's certainly going to meet a huge chunk of this demand.

2. Vistra

Technically speaking, Vistra (NYSE: VST) isn't an industrial company. It's categorized as a power utility, though even by utility-stock standards, it's not exactly your typical power company. While it does directly provide electricity to about 5 million residential and business customers, Vistra's core business is generating and then selling electricity on a wholesale basis to other utility companies sharing the same grid.

The company's now making the most of this flexibility too. For instance, rather than merely connecting new artificial intelligence data centers to existing grid infrastructure and treating them like any other customer, Vistra is now entering long-term power purchase agreements directly with institutions. Early this year, the company announced it had inked long-term deals with Amazon and Facebook parent Meta Platforms to supply both tech companies with the electricity needed for existing and new AI data centers.

Nvidia CEO Jensen Huang. Image source: Nvidia.

Such arrangements still account for only a relatively small part of the company's total business. In that these long-term agreements allow Vistra to make capital investments -- particularly in nuclear power -- with a reasonably assured return on the investment, the company can add power production capacity with the confidence that ultimately allows it to build more efficient infrastructure.

In other words, it's a win-win. That's why you shouldn't be surprised to see more such dealmaking in the future, particularly from Vistra, which has already shown its interest in custom-designed power provision solutions.

3. Caterpillar

Finally, add Caterpillar (NYSE: CAT) -- yes, the construction equipment company -- to your list of stocks that will benefit from the AI industry's exploding demand for electricity. It's already benefiting, in fact.

You know it best as a maker of bulldozers, backhoes, and dump trucks. And that's still a huge part of its business to be sure. Largely overlooked, though, is that Caterpillar also manufactures high-capacity mobile diesel and gas generators, battery-based energy storage systems, and more, all of which are proving to be much-needed stopgap solutions while data center owners and operators are waiting on more permanent equipment. Outfits including Space Exploration Technologies and Microsoft (through Nscale) are utilizing off-grid generators to power some of their AI data centers.

To this end, while all of Caterpillar's business lines grew last year, its power generation arm, which provides these generators, experienced company-leading growth of roughly 30%. The company expects this business to double between 2025 and 2030, and S&P Global doesn't exactly disagree with this outlook. It's looking for Caterpillar's power and energy division to grow another 17% this year -- from last year's revenue of $33.4 billion -- en route to $54.8 billion in annual revenue by 2030.

James Brumley has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Bloom Energy, Caterpillar, GE Vernova, Goldman Sachs Group, Meta Platforms, Microsoft, Nvidia, S&P Global, and Vistra. The Motley Fool has a disclosure policy.