At least 75 U.S. data center projects worth roughly $130 billion were blocked or delayed in the first quarter of 2026, nearly equal to the total for the prior full year, as active opposition groups climbed from 396 to 833 across 49 states in that same period. Underneath local objections over water and power lies a deeper question about who owns compute, since revenue flows to companies headquartered in Seattle, Redmond, or Menlo Park while counties absorb costs including substation strain, truck traffic, and tax incentives forfeited in advance. Technical developments are beginning to loosen the requirement for massive co-located clusters: a 2023 Google DeepMind finding showed geographically separated machines could train models while exchanging roughly 500 times less data, and a March project called Templar trained a 72-billion-parameter model across more than 70 contributors over ordinary internet connections. Nvidia also introduced Spectrum-XGS Ethernet in August 2025 specifically to stitch sites together across long distances as individual facilities hit power and capacity ceilings.
Data center demand drove 63 percent of one year's capacity price increase across the 13-state PJM grid region, recovering about $9.3 billion from ratepayers, illustrating the direct financial impact on households and businesses far from any server facility. If distributed training methods continue maturing, the industry's structural dependence on single enormous campuses could diminish, reshaping siting strategies, grid interconnection queues, and the competitive landscape for regional and mid-sized operators.
An analysis framing data center disputes as a power struggle over compute ownership touches on a high-interest strategic and geopolitical angle for the AI infrastructure sector. The Observer piece appears to offer a distinct editorial perspective not covered in already-published stories.