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Daniel Ives: Trump’s Electricity Policy Could Be a ‘Bottleneck’ for Data Centers

AI is booming—but is the U.S. power grid keeping up?

By Muhammad HassanPublished a day ago 3 min read

If you’ve been following the AI boom lately, you know that it’s not just about clever algorithms or smart apps—it’s also about massive amounts of electricity. And according to Wall Street analyst Daniel Ives, the electricity policies being pushed by the Trump administration could become a serious bottleneck for U.S. data centers, the massive facilities that power everything from cloud storage to AI models like ChatGPT.
Ives warns that while the administration wants to protect consumers from higher electricity bills—which is understandable—the way these policies are being implemented may slow down the very infrastructure needed for America to stay competitive in AI and tech innovation.
Data Centers: More Than Just Big Computers
Think of a data center as a giant brain for the internet. These facilities run thousands of servers 24/7, processing the data behind social media, streaming video, cloud apps, and artificial intelligence.
Unlike your laptop or phone, data centers never power down, which means they use an incredible amount of electricity. In 2023, U.S. data centers used about 4.4% of all electricity in the country—roughly the same as major cities like New York or Chicago. And with AI becoming a bigger part of business and daily life, demand for power is expected to double or triple by 2030.
So when policies affect electricity pricing or availability, it hits data centers directly—and fast.
Trump’s Electricity Policy Explained
President Trump’s administration has been clear: Americans shouldn’t pay higher utility bills because of data centers. The plan encourages Big Tech to cover their own energy costs instead of relying on electricity rates that might indirectly affect households and small businesses.
In response, companies like Microsoft have pledged to pay more for electricity and make their operations more efficient. While this helps protect consumers, Daniel Ives says it could also slow down the growth of new data centers if companies decide the costs are too high or too uncertain.
Why Daniel Ives Calls It a Bottleneck
Ives calls this situation a “bottleneck” for several reasons:
Rising Costs for Tech Firms: If companies have to pay more for electricity, building new data centers becomes more expensive. That can slow expansion.
Infrastructure Limits: Many regions of the U.S. grid weren’t designed for the current surge in AI-powered data centers. Limited power availability can delay or block projects.
Global Competition: Ives warns that if U.S. policies make data center growth harder, other countries—like China—might pull ahead in AI infrastructure.
In short, protecting consumers is important, but it needs to be balanced with ensuring America can scale its AI and cloud capabilities quickly.
The Reality of Power Demands
This isn’t just about politics—it’s about practical energy challenges. The U.S. grid is already under pressure from data centers, electric vehicles, and growing industrial demand. In some hotspots, developers wait years just to get a power hookup.
Without careful planning, the electricity needed for AI innovation could hit a hard limit, delaying projects or pushing companies to relocate where energy is cheaper or more abundant.
Balancing Innovation and Consumer Protection
The Trump administration’s approach tries to strike a balance: protect household electricity bills while allowing tech growth. But Daniel Ives argues that if the balance isn’t right, it could unintentionally discourage investment and slow AI infrastructure development.
Companies are trying to adapt. Microsoft, for instance, has promised to cover energy costs and invest in efficiency. Utilities and lawmakers are also revisiting subsidies and incentives for energy-intensive projects, trying to find a way that keeps everyone happy.
Why This Matters for AI
The bottleneck isn’t just about data centers or corporate profits—it’s about the speed of AI development in the U.S. AI doesn’t just need processing power; it needs continuous, reliable electricity. If supply is limited or policies make energy too expensive, AI projects could slow down, affecting everything from business innovation to national competitiveness.
Ives’ warning is clear: electricity policy isn’t a small detail. It’s a strategic factor that could shape the future of AI in America.
Conclusion: Watching the Power Flow
Daniel Ives’ perspective highlights a key lesson: tech innovation depends on energy policy just as much as it does on talent or investment.
The U.S. needs policies that protect consumers but also allow data centers—and the AI revolution—to grow. Otherwise, we could see delays in AI infrastructure just as the world is racing to adopt new technologies.
For policymakers, companies, and consumers, the takeaway is clear: energy policy isn’t just about rates; it’s about the future of American technology.
The next few years will show whether Washington can balance consumer protection with the energy needs of AI—or if Daniel Ives’ bottleneck warning becomes reality.

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About the Creator

Muhammad Hassan

Muhammad Hassan | Content writer with 2 years of experience crafting engaging articles on world news, current affairs, and trending topics. I simplify complex stories to keep readers informed and connected.

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