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Key Points
- Nearly 200 companies have signed a pledge introduced by President Donald Trump to help finance new electricity generation aimed at supporting AI growth while keeping power prices lower for consumers.
- The pledge is voluntary and nonbinding, meaning participating companies are not required to follow through if the costs become too high.
- Investors have multiple ways to benefit from the AI data-center buildout regardless of the pledge’s outcome, as demand for power infrastructure continues to accelerate.
Energy use at data centers used for artificial intelligence (“AI”) is surging, with stories sweeping the media about everyday families paying soaring utility bills as electricity prices rise. A “pledge” introduced in March by President Donald Trump and newly expanded in recent weeks promises to make the big companies behind the surging use pay up for the energy they consume.
The stated goal of Trump’s Ratepayer Protection Pledge is to protect consumers from rising electricity prices due to AI data centers, which use huge amounts of energy. These AI firms “will build, bring, or buy the new generation resources and electricity needed to satisfy their energy demands, and pay for all new power delivery infrastructure upgrades to service their data centers.”
Analysts expect more than $1 trillion in further investment to build out and operate AI data centers in 2027, on top of hundreds of billions being made in 2026. Rising electricity costs have led to consumers’ hostility toward AI data centers and growing pushback against their expansion.
The White House says the companies signing the pledge account for about 80% of all power provided to U.S. homes and companies. Nearly 200 entities have signed on, including utilities, Big Tech companies, data-center companies, and even many state governors.
The list includes heavyweights such as Alphabet (GOOGL), Microsoft (MSFT), Meta Platforms (META), Amazon (AMZN), and Oracle (ORCL). Also signing are data-center developers such as Digital Realty (DLR) and Equinix (EQIX), as well as utilities such as NextEra Energy (NEE), Southern Company (SO), and Duke Energy (DUK).
But in contrast to the pledge’s stated goal, the actual goal is pure public relations. It offers what’s likely to be a win-win-lose solution to the problem, with consumers coming up on the short end.
- Winner: President Trump gets to claim that he’s “doing something” about energy affordability, while potentially reducing public opposition to the AI data-center rollout.
- Winner: AI-related businesses and power companies also get to say they’re doing something while continuing their build-out. They’re probably no worse off in aggregate than they would have been otherwise, but may now appear more righteous about their actions.
- Losers: Consumers will still be on the hook for high electricity prices, which are set in many areas by public utility commissions, state regulators, and buyers and sellers of electricity. So, it can be difficult to enforce any pledge when companies don’t directly control prices.
Central to this properly cynical conclusion is that the pledge is nonbinding, leaving little-to-no consequences for companies that choose to walk away from the pledge as soon as it no longer benefits them. With electricity prices being set by regulators and buyers and sellers of power, it will be all but impossible to enforce any promise to act in a specific way, showing how the pledge is pure optics.
3 Alternative Ways to Invest in the AI Data-Center Boom
While the surge in energy use may sting consumers, pledge or no pledge, investors have several attractive options for playing the AI data-center build-out.
AI model companies such as OpenAI and Anthropic, or neoclouds such as CoreWeave (CRWV) and Nebius (NBIS), are often touted as ways to invest in the megatrend, as are hyperscalers, which are rapidly building new data centers.
The pace of data-center investment is rising. Earlier this year, the four largest hyperscalers – Amazon, Alphabet, Microsoft, and Meta – were projected to make $650 billion in capital investments in 2026 alone. That figure soon ballooned to $725 billion.
Next year should be even higher. Moody’s (MCO) estimates that hyperscaler spending should approach $1 trillion in 2027, while other analysts are projecting even higher capital investment.
But investors have alternative ways to ride the trend and still earn attractive risk-adjusted returns.
1. Top Utilities ETFs
If big hyperscalers are willing to pay up for their electricity consumption as part of Trump’s pledge, that’s a boon for utility companies. Utilities are set to spend hundreds of billions of dollars in the next few years to keep up with the expected surge in electricity demand.
Utilities are expanding their generating capacity, investing in transmission projects, and upgrading the grid, sometimes in collaboration with the companies powering the AI data-center build-out.
The megatrend of “power grid upgrade” may continue for years, creating billions in profits for investors. Utilities play the data-center trend, but do so with lower risk, as they benefit from many of the same drivers. Electricity use tends to grow over time, offering a recurring revenue stream.
Utilities benefit from regulations that permit them to earn a guaranteed return on their investment and boost prices regularly. That means a lower-risk revenue stream and the prospect of sizable dividends, so a good portion of the return is paid in cash.
An easy way for investors to ride the data-center wave is by buying one of the best utilities exchange-traded funds (“ETFs”) for the AI boom. These ETFs provide broad exposure to the sector, reducing risk, while allowing investors to play the trend without doing all the analysis needed to buy individual stocks.
2. Individual Energy Infrastructure Stocks
On the other hand, if you’re willing to analyze individual stocks, you could end up with better overall returns by picking individual utility stocks or other energy stocks that are well-positioned to thrive on the AI build-out.
For example, my colleague David Engle highlighted Eaton (ETN), a company that helps manage the power usage of data centers. Eaton has worked with Nvidia (NVDA) on a power architecture that boosts efficiency even while supporting AI workloads. Eaton’s “busbar technology” supplants traditional cables with more compact metal conductors that reduce power loss.
Eaton also produces power distribution units that manage electricity for AI data centers, provides liquid cooling services, and offers software that lets customers track data centers’ performance.
The big advantage of individual stocks over ETFs is that the right stock could outperform an ETF. The flip side is that individual stocks are riskier.
Here are two other electrical infrastructure stocks that benefit from massive AI investments.
3. Engineering and Construction Firms
It’s not all about power as the data-center build-out is being realized. Someone has to construct all those buildings – and that job goes to engineering and construction firms. One of the biggest and best players here is Sterling Infrastructure (STRL), which has turned in… um, sterling returns so far this year.
But sometimes the best investment is a stock that plays on the trend beneath the trend, since it allows you to ride multiple waves at once. And that’s the pitch for SOLV Energy (MWH).
SOLV is one of the largest engineering and construction firms focused on the build-out of solar energy, a trend that plays on the energy-hungry AI build-out but other trends, too. It installs solar energy, related battery systems, and grid hookups and provides monitoring services, too.
The growth potential in solar is utterly enormous. In fact, during 2025, solar accounted for 54% of all new electricity capacity in the U.S. It was the fifth straight year that solar achieved the feat, and there are likely many more years of growth on the way. Plus, solar facilities can be brought online much faster than conventional facilities – making it a great play for the rush in AI build-outs.
So, those are three alternative ways you can adjust your level of risk when investing in the AI data-center boom.
Regards,
James Royal, PhD
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