US data center power demand forecast to hit 106GW by 2035, report warns
BloombergNEF research reveals a sharp 36% jump in energy forecasts as "hyperscale" projects reshape the American grid
The energy footprint of US data centers is expanding far more rapidly than previously anticipated, driven by a surge in massive-scale artificial intelligence (AI) projects that threaten to overwhelm existing power infrastructure.
According to a new report released this week by BloombergNEF (BNEF), titled AI and the Power Grid: Where the Rubber Meets the Road, demand for power from US data centers is now projected to reach 106 gigawatts (GW) by 2035.
The figures represent a significant revision of industry expectations. The 106GW forecast is a "36% jump from the previous outlook" published by BNEF just seven months ago, underscoring how quickly the generative AI boom is altering the physical requirements of the technology sector.
"Colliding with grid realities"
The report paints a concerning picture for IT leaders and utility providers, suggesting that the pace of digital infrastructure buildouts is outpacing the electrical grid's capacity.
"This boom in data center demand is colliding with grid realities," the report states.
BNEF analysts warn that specific regions are already facing precarious supply crunches. In the PJM Interconnection, a major regional transmission organization covering 13 eastern states and DC, data center capacity is forecast to reach 31GW by 2030. This figure "nearly matching the 28.7GW of new generation" expected to come online during the same period, leaving virtually no buffer for error.
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The situation is similarly tense in Texas. The report notes that in the Electric Reliability Council of Texas (ERCOT) grid, reserve margins could fall into "risky territory after 2028," signaling that while short-term growth might be manageable, long-term reliability is in question.
The rise of the mega-campus
A key driver of this energy spike is the shift toward significantly larger facilities. As tech giants race to train more complex Large Language Models (LLMs), the physical footprint of the average data center is ballooning.
Of the nearly 150 new projects added to BNEF's tracker over the last year, "nearly a quarter exceed 500 megawatts." This represents "more than double last year’s share" of such massive facilities.
"The massive growth rate in data center power demand reflects more than a surge in the number of data centers in the pipeline; it also highlights the new centers' size," the report notes.
Geographic shift beyond "Data Center Alley"
The power constraints are forcing a geographical restructuring of the US internet infrastructure. Northern Virginia, long known as the world’s "Data Center Alley," is "nearing saturation," prompting developers to look elsewhere.
New projects are increasingly migrating south and west. BNEF highlights that developers in Texas are "transitioning former crypto-mining sites into AI data centers," capitalizing on existing connections to power and population centers. Meanwhile, hyperscale campuses are appearing in "suburban and exurban zones," typically within 30 miles of major cities in states like Georgia and Ohio.
This sprawl is reliant on robust connectivity. "Fiber optics form the digital spine enabling this sprawl," the report said, allowing these massive campuses to operate outside urban cores while maintaining the low latency required for high-performance computing.
For CIOs and IT procurement leaders, the report serves as a warning: the era of abundant, easily accessible power for digital expansion may be drawing to a close, marking an "inflection moment for US grids."
Rene Millman is a freelance writer and broadcaster who covers cybersecurity, AI, IoT, and the cloud. He also works as a contributing analyst at GigaOm and has previously worked as an analyst for Gartner covering the infrastructure market. He has made numerous television appearances to give his views and expertise on technology trends and companies that affect and shape our lives. You can follow Rene Millman on Twitter.
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