President Trump declared Monday that American communities must prioritize data centers—or risk becoming “backwards and poor.” “If they want to be successful and rich, with far lower taxes and jobs all over the place, let Data Reign,” he stated. “The good news is that there are plenty of other places that want them. If we kill the Golden Goose, you will only have yourselves to blame,” Trump added, noting China’s apparent surprise at the growing anti-data center movement.

Recent polling shows Americans’ opposition to local data centers has intensified. A survey conducted last month found 70 percent of respondents oppose constructing such facilities in their communities to support artificial intelligence, including 60 percent of Republicans and 76 percent of Democrats.

Environmental and financial concerns drive much of the backlash. According to an analyst at the Environmental and Energy Study Institute, a medium-sized data center consumes up to 110 million gallons of water annually for cooling—a volume equivalent to roughly 1,000 households’ yearly usage.

Despite Trump’s push for corporate responsibility, opposition has grown sharply as data center development accelerates. A Gallup poll from March revealed 70 percent of Americans oppose community projects, while separate polling showed 41 percent would reject facilities within three miles of their homes—up from 28 percent in January.

New York enacted the nation’s first statewide data center moratorium in July, and lawmakers in over a dozen additional states have proposed similar restrictions. Project delays are also mounting: more than 500 localities have stalled development, and Data Center Watch reported over 75 projects worth $130 billion were halted in early 2026 alone—nearly matching the total blocked during all of 2025.

Concerns about electricity costs remain central to public skepticism. A recent poll found 62 percent of Americans believe new data centers would raise their utility bills, compared to 13 percent who expect no impact and just 3 percent who anticipate lower costs.