In recent economic analysis. Harvard economist Jason Furman crunched the numbers from U.S. Bureau of Economic Analysis data and found that investments in information-processing equipment and software largely tied to AI data centers made up just 4% of total U.S. GDP in the first half of 2025.
Yet, those same investments drove roughly 92% of the period’s GDP growth. Excluding them, annualized GDP growth would have limped along at a mere 0.1%—a virtual standstill that economists often flag as recession territory, especially amid slowing job growth and weakness in consumer spending, manufacturing, and services.
The surge stems from massive capital expenditures by Big Tech on AI infrastructure scale of spending. Companies like Microsoft, Google (Alphabet), Meta, and Amazon poured nearly $370 billion into capex in 2025 alone, much of it on servers, GPUs, and data center builds.
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Goldman Sachs estimates global AI-related spend hit $200 billion this year, with U.S. data center construction reaching a record $40 billion annualized rate in mid-2025. This isn’t just hardware—it’s software, R&D, and power/grid upgrades too.
Renaissance Macro Research noted in August that AI data center contributions to GDP growth outpaced U.S. consumer spending typically ~70% of GDP for the first time ever. Other sectors dragged: Manufacturing and real estate saw outright declines.
Retail and services added little, with job creation cooling sharply, unemployment claims hit a 4-year high in recent months. Consumer credit is flashing yellow delinquencies rising, and without the tech boom, the Federal Reserve might have cut rates further to stave off contraction—potentially averting recession but risking higher inflation elsewhere.
S&P Global pegs data centers and high-tech as responsible for ~80% of private domestic demand growth in H1 2025; without it, the economy flatlines. It’s a classic “jobless recovery” vibe: GDP looks robust Q3 now tracking 4.2% annualized per Atlanta Fed, but the gains are K-shaped—concentrated in tech hubs and elite firms, not broadly shared.
Data centers employ few ongoing workers mostly construction-phase jobs, limit wage-driven consumption spillovers, and strain resources—electricity demand could double by 2028, driving up bills 6-7% yearly and emissions already 2% of U.S. total.
Morningstar warns AI capex now exceeds the dot-com peak relative to GDP, needing $2 trillion in annual revenue by 2030 to justify current: ~$20 billion. Bubble fears are real—53% of investors see one brewing.
Furman himself notes that absent the AI boom, we’d likely see lower rates and energy costs, spurring ~half the lost growth elsewhere. The data center boom is a lifeline keeping recession at bay, but it’s propping up a patient with underlying issues.
The energy crunch is reshaping the AI and tech economy in profound ways, turning what was once a frictionless growth story into a high-stakes balancing act. Data center power demand is projected to more than double globally to 945 TWh by 2030—equivalent to Japan’s entire electricity consumption today—with AI driving the lion’s share.
In the US, this could translate to an 8% average rise in household electricity bills by 2030, spiking to 25% in hotspots like Virginia. Wholesale prices near data centers have already jumped up to 267% since 2020, fueling $9.3 billion in capacity cost hikes in markets like PJM.
For Big Tech, $800 billion in 2025 data center commitments from Alphabet, Amazon, Meta, Microsoft, and OpenAI risk ballooning into capex overruns if grid delays persist, potentially delaying ROI and throttling the $370 billion hyperscaler spend.
On the flip side, this scarcity is birthing a $580 billion global data center market by 2025, with AI claiming 27% share by 2027, redirecting trillions toward infrastructure. Utilities are filing for $30 billion in rate hikes, but the real winner? A projected 36 GW US power shortfall by 2028, sparking M&A and investments in everything from natural gas to batteries.
Without mitigations, this could shave 1-2% off US GDP growth annually through blackouts and higher costs, per RAND estimates. Markets are pivoting hard: chip stocks like Nvidia may face “power-limited” ceilings, with Jensen Huang warning of electricity as the new bottleneck—data centers could hit 40% of net new US demand by 2030.
Utility and energy plays are surging—Constellation Energy (CEG) up 50% YTD on nuclear restarts, while renewables like NextEra (NEE) and battery firms (e.g., Fluence, FLNC) eye 23% CAGR in storage needs.
But speculation is rife: Sam Altman called out an “AI bubble” in August, and utilities like Constellation are tempering hype, warning of overstated loads. Geopolitically, China’s edge in manufacturing and energy could erode US AI leadership if transformers and generation lag—Elon Musk flagged this as a “worrying” long-term risk.
AI infra stocks could dip 20-30% on permitting snarls, but energy innovators SMRs, advanced solar might 5x as demand quadruples to 1,600 TWh by 2035. If AI delivers transformative productivity as optimists bet, it could broaden out. If not, we’re borrowing from tomorrow’s growth today.