Hyperscalers Face Data-Center Backlash and Calls for Rules

By Amara Osei

U.S. data-center demand will rise from 25 GW in 2024 to more than 80 GW by 2030, nearly quadrupling as McKinsey tracks the infrastructure buildout required by artificial intelligence.

The economic pull runs ahead of public consent. In the first half of 2025, AI-related spending added almost one percentage point to real U.S. GDP growth, Goldman Sachs said: “Without it, U.S. GDP growth would have almost flatlined.”

Against that backdrop, a September Pew Research study found that Americans viewed data centers more negatively. Environmental concerns led the objections, followed by home energy costs and quality of life for nearby residents.

Can data-center growth coexist with local consent?

On the sidelines of Web Summit in Lisbon, Stavros Gadinis, a UC Berkeley law professor, faculty director of the Berkeley Center for Law and Business and author of Corporate Ordering, argued that history already supplies a workable model. He called it a “playbook” and a “better way.”

Gadinis laid out the first step: “So, that playbook involves, first off, outreach to impacted parties and impacted communities. I don’t mean just the local [communities]—although obviously these are key—but also nonprofits, academics.”

Concerned parties must receive a stake in development, Gadinis said. Large investors should set those conditions before committing capital, and builders can “get the ball rolling” once investors meet the terms.

Accountability should close the process. “The final part, I think, has to come through accountability from these companies to try to show how they respected the policies and the goals, and how they’re moving ahead and what they’re contributing,” he said.

Jeremy Siegel, emeritus finance professor at Wharton, sees a market-led balancing force. He said: “If one community rejects a data center, another will welcome the investment, jobs, and tax revenues.”

That adjustment may not arrive evenly. Public opposition is spreading rapidly across the United States, including Texas, home to Elon Musk’s SpaceX, which merged with his AI-focused company xAI earlier in 2026.

Permit conflicts and delays already building in Texas could become “possible everywhere,” Gadinis warned.

He said neither AI companies nor the White House wants a breakdown: “The biggest advantage that we have against our global competitors is our ability to build compute, of which data centers are a very important part. So we actually need to take some steps to bring everyone closer together in that question.”

Takeaway: Market demand may outrun local resistance, but outreach, enforceable investor conditions and consistent permitting rules can prevent gridlock.

Who bears the risk when AI becomes systemic?

Regulation now carries a larger financial consequence. A Democratic landslide at the midterms is likely to bring more scrutiny to AI companies that operated with significant freedoms under the Trump administration, and analysts said the market slid last week on those prospects.

The policy dispute already runs between hyperscaler founders and Washington. Some founders want government regulation, while Treasury Secretary Scott Bessent has said the government will not become a “liability shield” for technology giants.

Gadinis said the order of action matters less than the basis for the rules. The framework must be “built on the right foundations,” and he predicted: “My prediction would be that once practice is crystallized, then the government is going to say: ‘OK, we found it, now do this, and everybody does it.’”

The liability question has already outrun the policy choice, he argued. “The investment we have is so huge as a percentage of the [U.S.] GDP that they’re already too big to fail. They became too big to fail almost instantly in 2023.”

A government backstop remains hard to avoid. It is “very hard” to imagine otherwise, Gadinis said, “especially in an issue that the government itself has elevated into a national security concern. If a batch of subprime mortgages can cause a financial crisis, AI is looming large.”

His conclusion was blunt: “So I think it’s too late, and I think that realization also explains why people are asking for more regulation, because to some extent we’re all in it—whether we want it or not.”

Takeaway: Once AI investment becomes systemic, regulation and a government backstop are likely to arrive together.