Maryland voters see higher electric bills, other downsides from data centers in new UMBC poll

A new University of Maryland Baltimore County poll shows widespread concern among Maryland likely voters about data centers, with 80% saying they believe the facilities will have a mostly negative impact on household electricity costs

Just 6% of those surveyed said new data centers would have a mostly positive impact on electric costs. Seventy-five percent expect a negative impact on the quality of life for people living near data center sites.

Opposition extends to whether new data centers should be built at all.

Among 370 likely voters asked about new data centers being built in Maryland, 78% opposed them and 13% supported them. A separate group of 406 voters was asked about a new data center being built near their community, with 77% opposed and 16% in support.

Voters also expressed concerns about the environmental impact. Sixty-eight percent said new data centers would have a mostly negative impact on water quality, while 60% said the same about air quality.

The potential economic benefits didn't fare much better. Forty-nine percent said data centers would have a mostly negative impact on Maryland's economy, compared with 19% who expect a positive impact. Forty-eight percent expect a negative impact on state and local tax revenue, while 20% expect a positive one.

When it comes to jobs and employment opportunities, 37% expect a negative impact, 28% expect no real impact and 26% expect a positive impact.

Data centers weren't the only issue that likely voters expressed concerns about. The poll also found negative views of Maryland's economy and the direction of the state, while Gov. Wes Moore's job approval remained slightly higher than his disapproval.

Nearly half of likely voters, 49%, said Maryland is on the wrong track, compared with 37% who believe the state is headed in the right direction.

Views on the state's direction varied sharply by party. Half of Democrats said Maryland is headed in the right direction, while 30% said it's on the wrong track. Among Republicans, 90% said the state is on the wrong track, and 7% said it's headed in the right direction. Fifty-five percent of unaffiliated voters said Maryland is on the wrong track.

The poll found 49% of likely voters approve of the job Wes Moore is doing as governor, while 42% disapprove and 8% said they don't know.

Among Democrats, 70% approve of Wes Moore's job performance. Among Republicans, 7% approve and 88% disapprove. Unaffiliated voters were more likely to disapprove, 49% to 37%.

The poll also found broad dissatisfaction with Maryland's economy.

Eighty-one percent of likely voters rated economic conditions in the state over the past year as poor or fair. Just 17% described conditions as good or excellent.

Looking ahead, 43% expect economic conditions to be worse a year from now, 37% think they'll be about the same and 12% expect them to improve.

When asked what they consider when evaluating the state's economy, 94% pointed to the prices of everyday goods and services. Personal finances followed at 90%, housing costs at 86%, state taxes and fees at 84%, interest rates at 74%, unemployment and job reports at 67% and the stock market at 41%. Respondents could select more than one answer.

Artificial intelligence also received largely negative marks.

Sixty-seven percent of likely voters said they believe AI will have a negative impact on society, compared with 23% who expect a positive impact.

Negative views crossed party lines, with 71% of Democrats, 57% of Republicans and 70% of unaffiliated voters saying they expect AI to have a negative impact on society.

The UMBC Poll surveyed 776 Maryland likely voters from Sept. 22 through Sept. 27 using live telephone interviews and text-to-web surveys. The poll has a margin of error of plus or minus 3.5 percentage points.

UMBC classified registered voters as likely voters if they said they were either "absolutely certain" or "very likely" to vote in the November 2026 general election. The results were weighted by gender, age, race, geography, and educational attainment

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