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Over the past four years, Dallas, the beating heart of the U.S. energy economy, has become the beating heart of the U.S. data-center economy. That’s thanks to its cheap land, friendly regulatory posture, liquid labor market, excellent transportation infrastructure, and ample grid connectivity. Roughly 125 facilities are up and running in the metro region, and an additional 19 are under construction and 53 are planned. The building boom is boosting wages for blue-collar workers and helping hold the local unemployment rate at 4.1 percent, close to its historic low.
Yet Dallas and its suburbs are also in the midst of a building bust. Retail construction is strong. But despite high rents and a growing population, few new homes are being built: The number of houses builders broke ground on dropped 12 percent year-over-year, and the number of multifamily units in the works plummeted 43 percent over the past three years. Office construction is also depressed.
Is the tech boom offsetting these other downturns or causing them? That’s the big question facing Dallas and the rest of the United States.
Investors are more pumped about AI than they have been about any technology since the railroad. If they weren’t directing a torrent of money to the handful of firms finessing algorithms and constructing data centers, the country’s employment level and economic output might be lower. Then again, if they weren’t directing a torrent of money to the handful of firms finessing algorithms and constructing data centers, they might be directing it to everyone and everything else. So is AI fueling the American economy or siphoning gas from it? Is it “crowding out” investment in non-tech enterprises, as economists put it, or boosting investment in an otherwise lackluster expansion?
Certainly, AI is pushing up GDP—or, to be precise, the AI build-out is pushing up GDP. In 2020, American businesses spent $3.6 trillion, adjusting for inflation, on investments in durable assets, such as software, warehouses, and trucks. Last year, they spent $4.4 trillion. Oracle, Microsoft, Amazon, Meta, and Alphabet are shelling out $800 billion on capital expenditures just this year, a sum that has grown eightfold over the decade. It’s a Silicon Valley hard-hat stimulus, bigger than the one Washington passed to counter the Great Recession. And it is transforming national accounts. In this year’s second quarter, household consumption rose at a 3.8 percent annualized pace. Private investment in everything but real estate climbed at a pace of 12.7 percent. Spending on equipment went up at a 21 percent rate. Purchases of computers alone added 0.7 percentage points to GDP, and “information processing equipment” a mammoth 0.9 percentage points.
This private-sector stimulus has as much to do with New York, London, and Shanghai as it does with Cupertino and San Francisco. The early AI boom was mostly financed by wildly wealthy venture capitalists and wildly profitable tech companies, many of the investors staking cash. But soon, AI firms needed more computing power to perfect their models. They needed to build data centers and chip factories. They needed hundreds of billions of dollars more liquidity than the Bay Area could provide. The world’s investors took a look at the sparkling returns they were promising and signed on. The cost of loans climbed as demand for loans climbed. Crowd out crowded in.
The effect is easiest to see in the construction sector. AI-linked firms are currently building 543 data centers, and 2,513 more are in the pipeline. Spending on the build-out has increased 65 percent over the past year, according to an analysis by the Harvard economist Jason Furman. At the same time, the amount devoted to building housing and retail outlets has dropped 10 percent. Spending on the construction of education facilities is down 13 percent; offices, 14 percent; hotels, motels, and resorts, 15 percent; and manufacturing plants, 24 percent.
Tech enterprises are not merely making it more expensive for non-tech enterprises to finance construction projects. They’re bidding up the cost of labor, land, and materials. They’re spurring landlords and institutional investors to buy Treasuries or stocks instead of bothering with apartment buildings and retirement homes. They’re forcing families to pay more for home loans too. As a general point, high yields are “sucking all the money out of the mortgage market,” Daryl Fairweather, the chief economist at Redfin, told me.
Governments trying to build infrastructure are getting hit by the same increase in borrowing costs. So are families looking to buy a new car or renovate a property. So are young people looking to launch a small business or sign up for a training program. In a roundabout way, Claude and ChatGPT might be increasing credit-card delinquencies as well.
Granted, the effect might not be that big outside of the construction and real-estate sectors, which are highly sensitive to interest rates and overhead expenses. (The trade war, immigration crackdown, and war with Iran are pummeling them too.) Justin Wolfers, an economist at the University of Michigan, noted that “2007 through 2022 was an unusual period” in which borrowing costs were close to zero. Today, rates have returned to where they were in the 1990s, and they remain lower than they were in the 1980s. They are “what I would call normal,” he said. Moreover, higher interest rates force investors to think before they stake, squeezing out the frothiest, goofiest, and scammiest projects first. Cryptocurrency mining facilities are “clearly being crowded out,” Ryan Cummings, an economist at the Stanford Institute for Economic Policy Research, told me. He called that “a good thing.”
Then again, houses and apartment buildings are a good thing, as are factories and hotels. Small, AI-driven changes in interest rates might lead to hundreds of thousands of American families remaining renters for the next decade. They might lead to scores of commercial outlets not getting built. They might lead to hundreds of non-tech start-ups remaining nothing more than an idea.
Will all of these data centers be a good thing, aside from their utility to AI firms? Perhaps not. Normally, cities and towns become more prosperous and credit-worthy when they lure companies to build facilities there. “It’s a two-plus-two-equals-five argument,” Jess Cornaggia, a finance professor at Pennsylvania State University, told me. Power plants, schools, stadiums, and factories hire workers, generate revenue for local businesses, increase tax receipts, and spur additional firms to co-locate. But data centers might end up being a two-plus-two-equals-four, or even two-plus-two-equals-three, proposition. Investors are demanding larger yields on bonds for water and school projects in communities with a lot of data centers, meaning they expect those communities to experience more resource strains and collect less property-tax revenue in the future. Once data centers are up and running, they use a considerable amount of power and water while generating close to no jobs, after all.
These trade-offs have been mostly absent from the hyped-up debate over AI’s effect on welfare and wealth, but they’re important. Giving up homes, parks, health clinics, and grocery stores might be worth it if white-collar firms become radically more productive and creative. Giving up non-tech start-ups might be worth it if we get a cure for cancer. But the more resources the country devotes to AI at the expense of other innovations, the more its future depends on that bet paying off.
