Mon, Jun 29, 2026|Chris Igou

U.S. Regulators Pave the Way for AI Data Centers

This essay was originally published in DailyWealth Trader, a daily trading advisory, and has been adapted. To learn more about this service, click here.

John Steinbach is part of a growing group of frustrated Americans...

He recently shared with Consumer Reports that his energy bill more than doubled in a single month... rising from $100 in December to roughly $280 in January.

Kevin Stanley is experiencing a similar situation. The 57-year-old Maryland resident is blind, relying on disability payments. And he recently shared with Bloomberg that his energy bill is 80% higher than it was three years ago.

Stories like these are becoming more common as data centers pop up around the U.S. Steinbach lives in Virginia, which has more than 600 operational data centers.

These facilities are partially responsible for these spikes. Just one can require as much power as a midsized city. And that growing demand is putting new strain on the power grid.

Now, U.S. regulators are stepping in to help. They just laid the groundwork to limit the stress data centers put on the power grid... while also speeding up the time it takes to get new facilities on line.

Importantly for investors, these new rules will create a tailwind for one overlooked corner of the energy market...

The Federal Energy Regulatory Commission ("FERC") regulates nearly all things electricity, natural gas, and oil in the U.S. On June 18, FERC announced a plan with new rules to help guide the AI energy boom.

Here are the three main takeaways...

1. Data centers could connect to the grid much faster.

Regulators want to shorten the time it takes a data center to connect to the grid to 90 days.

Previously, that process could take a year or longer. Cutting it to three months would remove a key bottleneck slowing the AI build-out.

2. Hyperscalers will have to become more flexible with their power use.

To reduce pressure on the grid during peak hours, these companies will have to either cut electricity usage or provide their own supplemental power.

That helps prevent spikes in electricity demand, ideally reducing costs for end users. And it's pushing AI companies to equip data centers with battery storage and other backup energy systems.

Microsoft (MSFT), Meta Platforms (META), and Amazon (AMZN) all use solar and battery power in their data centers. These systems can store extra power and release it when it's needed most.

And we're going to need as many of these backup storage options as possible as AI expands...

That's because AI could make up nearly 12% of total U.S. power demand by 2030 – up from just 5% last year. Take a look...

3. Hyperscalers will pay for any necessary grid upgrades.

Data centers and large power users will have to foot the bill for any upgrades needed to connect to the grid.

That increases the cost to AI companies. But it also reduces the pressure on utility companies to make the upgrades themselves... lowering costs for utilities and their customers.

These might seem like small changes in the grand scheme of the megatrend. But together, these rules show that the government sees AI infrastructure as a permanent part of the U.S. economy.

As Robert Montejo of law firm Duane Morris put it...

We're out of the wild era west of data-center development. This order may be remembered for less of its technical reforms and more for recognizing that large-load interconnection is now a core political, planning, and economic issue.

In short, the AI build-out is still in its early stages.

In order to keep it humming along, we need better rules for getting data centers on line without stressing the grid. That means battery storage and alternative energy will become an even bigger part of the story.

That's not going to change anytime soon... especially as regulators pressure AI companies on their power use.

If you haven't gotten on board yet, consider battery stocks today. Plenty of upside is likely from here.

Good investing,

Chris Igou

U.S. Regulators Pave the Way for AI Data Centers

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