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The Shadow Grid: Big Tech’s Quiet Takeover of America’s Power

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AI data centers are forcing hyperscalers to build their own energy infrastructure

On February 28, 2026, the United States and Israel launched Operation Epic Fury: a joint military campaign that struck more than 1,000 Iranian targets in the first 24 hours, killed Supreme Leader Ali Khamenei – and demonstrated that artificial intelligence is now part of the operational backbone of modern warfare.

The AI system most closely linked to U.S. operational support was Claude. Reporting indicates Anthropic‘s model was used through the Pentagon’s Maven Smart System, aided by Palantir (PLTR) in the broader defense-AI stack, to help process imagery, communications, and other intelligence inputs at machine speed. The result was a compressed kill chain: targets were analyzed, prioritized, and acted on faster than traditional human-only workflows could manage. 

Five days later, on March 4, the same country staged a very different kind of event. 

President Trump gathered the CEOs of Alphabet (GOOGL), Microsoft (MSFT), Meta (META), Amazon (AMZN), Oracle (ORCL), xAI, and OpenAI at the White House for a signing ceremony. They signed something called the Ratepayer Protection Pledge – a commitment, the administration said, to keep AI-driven data center expansion from raising household electricity bills by pushing hyperscalers to build, bring, or buy the power and infrastructure they need themselves. Some observers have started calling that emerging system the “shadow grid.”

The press covered both events, and not many people connected them. But they should have… 

Because Operation Epic Fury and the Ratepayer Protection Pledge are two chapters of the same story. And together, they may have just changed the investment calculus on energy, infrastructure, and national security more than most investors appreciate.

Why AI Data Centers Need Their Own Power

Start with what the conflict revealed about AI, because it changes the stakes of everything that follows.

The U.S. military used Anthropic’s Claude, through the Maven Smart System, to support intelligence analysis, target identification, and operational simulations during the strikes. In practice, that meant ingesting intelligence inputs, ranking targets, and helping assess strike effects once operations were underway.

In other words, AI is moving beyond the role of productivity tool or chatbot. It is now being used to process battlefields and compress kill chains. In this case, it appears to have helped accelerate the chain of analysis behind one of the most consequential strikes of the decade.

Now ask the question almost every financial analyst is failing to ask: what does that mean for the AI infrastructure build-out?

It means the shadow grid isn’t just a commercial infrastructure story anymore. It’s a national security story. The compute capacity that enables AI is now powering the operational backbone of U.S. military dominance. And the energy that powers that compute is, as of this week, as strategically critical as an aircraft carrier.

Meanwhile, the war is doing something else that directly accelerates the shadow grid thesis. 

A Shadow Grid In Overdrive

Iran launched retaliatory missile and drone strikes targeting U.S. embassies, military installations, and oil infrastructure – including vessels in the Strait of Hormuz – throughout the Middle East. The strait is now effectively blocked for normal commercial traffic, and oil prices have surged sharply as markets price in a major supply disruption.

Translation: the global energy system just became less reliable and more expensive precisely when America is trying to power the largest technology buildout in its history. That is a pressure cooker.

And the hyperscalers – who were already planning to build private energy infrastructure before the war – now have an argument that goes far beyond cost management. They have an argument that goes to the survival of the American technological advantage itself.

That brings us back to the public grid – the one your home is connected to. 

The Energy Demands of the AI Economy

Power demand from U.S. data centers doubled between 2018 and 2024 and could triple by 2028. There are roughly 680 data centers currently being planned in the United States, collectively requiring the energy equivalent of 186 large nuclear power plants. The public grid was not designed for this. Capacity prices in PJM Interconnection – the largest U.S. power market, spanning 13 states and D.C. – have surged to record highs, with recent auctions clearing around $329 to $333 per megawatt-day. That is a system under mounting strain.

So, what do you do if you’re Microsoft or Google and you need absolute power reliability for a campus consuming as much electricity as a small city – a campus that is now, demonstrably, part of America’s national defense infrastructure? 

You don’t wait for the utility to figure it out. You build your own.

Private natural gas plants. Long-term nuclear power purchase agreements. Small modular reactors built directly into the data center footprint. Independent transmission lines, substations, and switching infrastructure.

One grid for the AI economy. One grid for everyone else. 

This bifurcation is underway. And the Iran War just turbocharged it.

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