A stunning upset in the Texas governor race and sweeping Democratic victories across the country threaten to curtail the biggest-ever spending boom in US history.

That could disrupt a key growth engine for America’s economy.

Come January, states controlled by Democrats who support expanding or extending AI construction moratoriums will account for 45% of America’s planned data center capacity, according to Goldman Sachs. A quarter of America’s planned AI infrastructure buildout is set to take place in Texas alone.

That doesn’t mean half of America’s planned data centers are on hold. Demand for AI is off the charts. Donald Trump is still president, and he’s already waving around his veto hat. And Democratic governors couldn’t stop every data center from being constructed even if they wanted to.

But Tuesday’s election nevertheless represents a paradigm shift that could alter the pace and path of America’s nonstop AI spending spree – an investment boom that has, according to ING economists, accounted for as much as a quarter of total US economic growth this year.

Those economic benefits are already real, supporting thousands of jobs. And AI has the potential to revolutionize the way we work.

But an AI data center slowdown could come with important silver linings. It could rein in unfettered growth that has contributed to rebounding inflation and led to widespread public antipathy toward the technology and the data centers that house it. It could also curtail some questionable business models that have raised serious skepticism on Wall Street.

Tapping the brakes could ultimately put AI – and the US economy – on a more sustainable path.

People protest against data center development outside the Austin Marriott Downtown on September 2, 2026. Jay Janner/The Austin American-Statesman/Getty Images

What’s $1 trillion between friends?

AI infrastructure spending is expected to approach $1 trillion a year, every year, for the foreseeable future, according to Columbia Business School economist Stijn Van Nieuwerburgh. As a percentage of America’s gross domestic product, that would outpace every other investment boom in modern US history – including the construction of the railroads.

The outcome of Tuesday’s elections could slow that spending, with vast consequences for the thousands of jobs and massive amounts of economic development that AI supports.

Democrats gained gubernatorial seats in Nevada, Georgia, Ohio and Texas, where candidates campaigned on tightening data center regulations. Proposals from the governors-elect include ending tax breaks, tightening climate and electricity restrictions and allowing local governments to impose their own moratoriums on data center construction.

Construction equipment at the Nscale data center project in Barstow, Texas, on October 15, 2026. Eli Hartman/Bloomberg/Getty Images

But Texas is the big kahuna. Wells Fargo estimates that for every 10% reduction in planned Texas data center capacity, Big Tech companies will reduce their AI infrastructure spending by a stunning 1.6% (a lot of money when you’re measuring spending in the trillions of dollars).

State and local politicians have a lot of jurisdiction and sway over that spending: enough to change whether some projects get financed, said Mona Dajani, co-chair of Cooley’s infrastructure, energy and real estate practice.

Hundreds of data center developments that are still awaiting permits, utility service or tax incentives could be particularly exposed, Dajani noted. But even active construction projects could be threatened. Texas law grandfathers in some projects’ permits, protecting them from future changes to local permitting requirements – but that doesn’t resolve state permitting changes or electrical service guarantees that Governor-elect Gina Hinojosa could vacate.

Democratic Texas gubernatorial candidate Gina Hinojosa arrives to speak to supporters at an election night event in Austin, Texas, on November 3, 2026. Ashley Landis/AP

The wait for approvals could add significant costs for AI companies, Dajani said: Interest, equipment commitments and utility expenses will all continue to accrue, even while a project is on ice. At some point, existing projects could stop being financially viable.

If that happens, AI companies – who have already strained to build out data centers fast enough to meet their anticipated demand – may not be able to meet their explosive spending targets.

“This is a rare case where state and local leaders have influence of geopolitical-level import,” said Harry Krejsa, director of studies at the Carnegie Mellon Institute for Strategy & Technology.

Unsustainable growth

Data centers aren’t exclusively a Democratic issue: Americans have displayed bipartisan consensus for putting guardrails around data center buildouts.

Texas Republican Governor Greg Abbott had already imposed a data center moratorium that Hinojosa campaigned on extending until lawmakers establish stronger AI regulations.

People protest data center expansion at a rally at the Capitol before a Texas Senate Committee on Finance hearing in Austin, on July 27, 2026. Jay Janner/The Austin American-Statesman/Getty Images

But Trump had railed against any attempts to stymie AI’s growth and spending, citing economic and national security – particularly in the high-stakes race against China. Many Republican politicians who may have otherwise supported AI regulations, including frameworks for data center construction, remained silent.

Still, there’s evidence that the AI buildout could be on an unsustainable path.

The United States had 5,427 data centers at the end of last year, according to Stanford University’s AI Index Report, and AI companies have announced plans for 3,969 new US data centers, according to Aterio, a data center research company. But only about 800 are under construction, and AI experts have raised doubts about the viability of many of the announced projects.

If Tuesday’s election results trigger an investment slowdown, that could trim some of the industry’s fat.

Example A: CoreWeave, a neocloud business that rents out computing capacity, recently projected such extensive losses that its bond yields surged to 15% – the danger zone. That was particularly troubling, because its expected return on investment was only around 9%.

In other words, CoreWeave loses money on every single dollar it spends on expanding its data center capacity.

Deep-pocketed hyperscalers – Amazon, Google, Meta and Microsoft – don’t have that problem. But their stocks have been slammed in recent weeks as investors grow impatient with what they view as an unsustainable amount of spending that may not return profits for years.

A path forward

“AI is catching a break here,” said Joe Brusuelas, chief economist at RSM US.

Brusuelas expects growth to slow from last quarter’s 3.4% pace to something closer to 2.4% if there is an AI slowdown. That’s still solid long-term growth. And America’s economy is massive and diverse. Investment that otherwise would have gone to data centers can go elsewhere.

“It’s slowing, but it doesn’t mean we’re going to have a recession,” Brusuelas said.

Two dump trucks sit at the the remote site of a proposed, 1-gigawatt data center complex in Hudspeth County, Texas, on October 26. Omar Ornelas/El Paso Times/USA Today Network/Reuters

It also presents an opportunity for AI companies to get smart about their future AI data center rollouts – and get put on a more sustainable course.

The helter-skelter approach to data center construction has resulted in significant amounts of money getting flushed down the toilet in unworkable projects – collateral damage from massive competition to be first and biggest. Data centers already face $200 billion in project delays, according to Mike Mathews, global digital infrastructure practice leader at risk adviser Marsh.

A more rational, politically sensitive approach could create longer-term benefits for the communities that host the data centers and for the AI companies themselves.

There’s precedent for that. In the previous decade, the Googles of the world built out data centers for the cloud computing revolution, promoting the fact that they’d be built sustainably with renewable energy – even before it was cost-effective to do that. A similar, community-based approach could provide AI companies with the compute they need and give them the political and social license to operate their data centers for the long haul.

“Like the saying goes: If you want to go fast, you go it alone; if you want to go far you go together,” said Krejsa. “If you squander political license to operate at home, that’ll be a bigger impediment to remaining competitive with China.”