The AI Arms Race Gets Pricier

Editor's note: Big Tech companies can't afford to stop spending on AI. And while investors focus on chips and chatbots, a more overlooked opportunity is emerging behind the scenes. In this issue, Joel Litman, chief investment officer of our corporate affiliate Altimetry, explains why this "arms race" is creating a powerful opportunity in one overlooked corner of the market...

The biggest technology companies in the U.S. are still pouring cash into AI...

Bloomberg estimates the four largest hyperscalers now plan to spend as much as $725 billion on capital expenditures ("capex") this year. And most of it is tied to AI data-center equipment.

Google parent Alphabet (GOOGL) and software giant Microsoft (MSFT) are each targeting around $190 billion. E-commerce titan Amazon (AMZN) is planning nearly $200 billion. And Facebook owner Meta Platforms (META) is now guiding toward a range of $125 billion to $145 billion.

The spending narrative was clear... even if the stocks' reactions to their latest earnings weren't.

Meta sold off 8% after raising its capital-spending outlook. Alphabet rallied 15% after strong results. Microsoft and Amazon remained flat while pushing ahead with massive AI infrastructure budgets.

But while Wall Street debated the winners and losers on earnings night, the physical work of building all that infrastructure still has to get done.

And only a handful of companies are positioned right in the middle of it.

The big AI players need more infrastructure. And at the same time, the pieces going into that infrastructure keep getting more expensive...

Microsoft expects higher chip and memory prices to add roughly $25 billion to its full-year capex.

Meta raised the midpoint of its capex outlook by about $10 billion. The Big Tech giant pointed mostly to higher component costs, especially memory pricing.

Nvidia (NVDA) chips have become the workhorses of AI. They also carry gross margins near 75%, compared with rival Advanced Micro Devices' (AMD) roughly 52%.

So for every dollar hyperscalers spend on Nvidia chips, Nvidia pockets far more in profit than other chip suppliers. Investors have started calling this premium the "Nvidia tax."

That makes it harder for hyperscalers to keep up. But falling behind on AI infrastructure means falling behind on model training, cloud capacity, and revenue. So the spending continues.

No matter how expensive the chips get, every new data center still needs the same fundamentals: land, power, and the electrical infrastructure to run it all.

That's where Eaton (ETN) comes in...

Eaton is one of the biggest power-management companies in the world. It helps data centers manage power from grid to chip.

The company offers uninterruptible power supplies, battery storage, and even microgrids – which provide backup power that works off the grid.

Investors have noticed that Eaton is at the center of the data-center construction boom. Its stock has almost tripled over the past five years.

Uniform Accounting shows why that jump makes sense. At Altimetry, we analyze earnings with Uniform Accounting to avoid the distortions of traditional accounting methods.

Eaton's Uniform earnings surged from about $2.2 billion five years ago to nearly $5 billion last year.

And investors expect more where that came from. We can see this through our Embedded Expectations Analysis ("EEA") framework...

The EEA starts by looking at a company's current stock price. From there, we can calculate what the market expects from the company's future cash flows. We then compare that with our own cash-flow projections.

In short, it tells us how well a company has to perform in the future to be worth what the market is paying for it today.

As we mentioned, Uniform earnings were an impressive $5 billion last year. But investors are still plenty bullish.

They believe the AI infrastructure boom will translate to much higher Uniform earnings... nearly doubling again to more than $8 billion by 2030.

Check it out...

Those are some lofty expectations. The good news is that the spending backdrop is moving in Eaton's favor.

Hyperscalers are locked into a competitive cycle. If one of them slows down, it risks falling behind in model training, cloud capacity, and AI services.

Said another way, every major player is under pressure to keep building.

And the more these companies spend, the more the physical bottlenecks benefit businesses like Eaton.

And Eaton isn't the only company positioned to win as the infrastructure race accelerates...

We've been tracking this trend closely... And we've found a hidden "powder keg" that could send a handful of stocks soaring as soon as May 28.

Learn the details – plus two stocks to buy and two to sell – in this urgent, limited-time briefing.

Keep an eye on hyperscaler spending. When leaders like Microsoft, Alphabet, Amazon, and Meta keep raising budgets, it tells us the physical bottleneck isn't going anywhere.

Regards,

Joel Litman

Editor's note: Investors spent years chasing the companies designing AI chips. But the next wave of winners may be built far away from Silicon Valley. Behind the scenes, tech giants are racing to secure the infrastructure needed to keep AI systems running. That's why our corporate affiliates Altimetry and Chaikin Analytics teamed up to unveil the little-known group of companies emerging at the center of this transformation.