Growing opposition to data center development in the US following the 2026 midterm elections could slow the country’s artificial intelligence expansion and affect economic growth, as voters backed candidates and local measures seeking restrictions on new projects.
Democratic candidates critical of data center construction won key races in states including Ohio, Michigan, Texas and Georgia. More than a dozen towns in Ohio also voted to halt or restrict new developments, with similar measures passing in parts of Kansas, Florida and California.
The results have raised concerns among technology companies already struggling to secure sufficient computing capacity to meet growing AI demand.
Texas, Georgia and Ohio account for more than 40% of planned US data center capacity, according to Evercore ISI. Major projects by OpenAI, Meta and other technology companies in these states could face delays or additional regulatory scrutiny.
OpenAI executives have reportedly discussed whether the election results could force the company to revise its data center capacity expectations for next year.
The backlash stems partly from concerns over data centers’ impact on local electricity and water supplies, the environment and residential communities.
However, the expansion has also been a major driver of investment, construction employment and economic growth. AI-related investment is projected to account for 1.9% of US GDP growth this year, according to Goldman Sachs.
Industry experts warned that restrictions could delay construction and weaken economic activity. Sequoia Capital partner Pat Grady said the election results could extend timelines for data center projects, while construction economists cautioned that a slowdown could affect jobs and investment.
Despite the opposition, several projects already approved are expected to proceed, although future developments could be delayed or scrapped.
The election results highlight growing political pressure on the AI industry as communities weigh the economic benefits of data center investments against concerns over their environmental and social costs.
