News

Power, Water, Jobs, Taxes: Weighing the AI Buildout's Real Costs and Benefits

• By John K. Waters
• 07/17/2026

New York Governor Kathy Hochul did something on July 14 that would have been difficult to imagine at the start of the generative AI boom. She told the data center industry to stop.

Hochul signed an executive order imposing a one-year moratorium on certain new hyperscale data centers, making New York the first state to pause the development of these facilities statewide.

The order temporarily halts state environmental permitting for new data centers requiring more than 50 megawatts of electricity while regulators study effects on the power grid, water supplies, ratepayers, and host communities. Previously approved projects were not broadly canceled.

The announcement landed in an industry accustomed to states competing for its business with tax exemptions, expedited permitting, and promises of cheap land and power.

President Donald Trump attacked the decision, writing on Truth Social that Hochul had made a "terrible decision" that would send investment to other states, and that the taxes and jobs data centers bring "amount to LIQUID GOLD." Hochul answered that New York was not rejecting data centers outright. It was demanding better terms.

"But when you benefit from the talent and energy of New York, we expect you to protect our resources and give back to our communities," Hochul said at a press conference announcing the order. In a written statement, she said New York would "lead the way in creating the strongest standards in the nation for data center development."

The exchange crystallized a political struggle spreading nationwide. Artificial intelligence may live in the cloud, but the cloud has become impossible to ignore on the ground: acres of windowless buildings, substations, transmission lines, cooling equipment, backup generators, and construction traffic, drawing power continuously and, depending on how it's cooled, substantial water.

The question is no longer whether AI needs infrastructure. It does. The harder question is whether the people living next to that infrastructure are being asked to assume too much of its cost.

What the numbers actually show
A 100-megawatt data center running continuously consumes 876,000 megawatt-hours of electricity a year, roughly as much continuous power as tens of thousands of homes. A 1-gigawatt campus uses ten times that, comparable to the output of a large nuclear reactor at full capacity, and can approach the electricity demand of hundreds of thousands of households.

A report from the U.S. Department of Energy and Lawrence Berkeley National Laboratory estimated data centers consumed about 4.4 percent of U.S. electricity in 2023, a share that could rise to between 6.7 percent and 12 percent by 2028.

New York's own interconnection queue illustrates why officials are nervous. Hochul's executive order says nearly 12 gigawatts of proposed data center load, equivalent to roughly a dozen large nuclear reactors, was waiting to connect to the state's electric system as of May 2026, with more than 8 gigawatts entering the queue during 2025 alone.

Not every proposed project will be built, but utilities may still need to plan transmission and generation around requests that could materialize, or risk stranding infrastructure that ordinary ratepayers end up financing either way.

The case against the buildout
The strongest argument against current data center development isn't that society should stop using cloud computing or AI. It's that the industry is moving faster than public infrastructure and local planning systems can adapt.

Electricity is the central concern. Data centers can arrive as enormous new loads in regions that have seen little demand growth for decades, and the generation, transmission, and substation investment needed to serve them takes years, while technology companies want power within months. Opponents worry households will subsidize those upgrades through higher rates, and that utilities will extend the lives of coal and gas plants or delay climate targets because renewables and transmission cannot be added quickly enough.

Those concerns aren't hypothetical, though the rate impact isn't settled either. A 2026 working paper from researchers at the Electric Power Research Institute and Watershed, examining U.S. electricity prices from 2015 through 2024, found data center growth had modestly reduced average retail rates during that period, likely because large, steady loads spread fixed grid costs across more electricity sales. The researchers warned that future supply constraints could reverse that effect: data centers may lower rates where grids have spare capacity and raise them where new infrastructure is expensive, or supply is tight.

Water produces a similar split, and it is where the sharpest disclosure problem lives. Cooling method matters more than facility size. Evaporative cooling cuts electricity use but consumes water; dry cooling uses less water but more electricity, especially in hot weather; closed-loop liquid cooling recirculates coolant but still has to shed heat somewhere.

Researchers at the University of California, Riverside, in a peer-reviewed analysis led by associate professor Shaolei Ren, estimated that if 2024 water-use intensity continues, data center expansion through 2030 could require between 697 million and 1.45 billion gallons per day of new water-system capacity, at the high end comparable to or exceeding New York City's average daily water supply.

The effect wouldn't be evenly distributed. It would concentrate in host communities, often during the hottest periods when water and electricity systems are already stressed. Reporting by CalMatters found that companies frequently do not disclose facility-level water use, even in water-stressed areas, leaving residents with marketing comparisons ("less water than agriculture," "about as much as a golf course") they have no way to independently check.

Beyond power and water, the case against rests on three more concrete grievances. Noise is local and persistent: cooling fans, chillers, transformers, and backup generators can produce a mechanical hum that doesn't quiet at night the way traffic does, and residents near existing facilities have complained about low-frequency noise that conventional zoning codes weren't built to address.

Land use is a second friction point: data centers can occupy hundreds of acres near transmission corridors and population centers, competing with housing, farms, and other industrial development, while employing relatively few people once construction ends. And tax incentives, exemptions from sales, property, or equipment taxes offered to attract developers, draw the sharpest criticism: supporters call them necessary to compete for investment, critics call it states bidding against one another to subsidize some of the world's richest companies.

Hochul said she would pursue legislation repealing New York's sales-tax exemptions for the largest data centers, a move that may prove as consequential as the moratorium itself.

The case for building
The argument in favor starts with a blunt fact: the modern economy already depends on data centers. Hospitals, banks, manufacturers, government agencies, universities, and retailers all run on cloud infrastructure that lives somewhere physical. AI adds a new layer of demand on top of that base load: training large models requires enormous processor clusters, and serving those models, known as inference, consumes computing power every time a user enters a prompt, generates an image, or assigns a task to an AI agent. Agentic systems can multiply that further, since a single user request may trigger dozens of model calls, searches, and tool operations.

Supporters frame data centers as infrastructure rather than real estate, warning that countries unable to provide electricity and computing capacity risk dependence on foreign AI systems and weaker standing in strategically important industries.

The facilities also bring real economic benefits: construction employs large numbers of electricians, engineers, and pipefitters; campuses generate substantial property-tax revenue even with small permanent headcounts; and operators purchase from utilities, contractors, and local businesses.

New demand can also accelerate investment the grid needs anyway. Major technology companies have become some of the world's largest corporate purchasers of renewable energy and are investing in geothermal, batteries, advanced nuclear, and the restart of existing nuclear plants.

Some workloads can shift to another time or location when the grid is stressed, and research suggests even moderate flexibility of this kind could reduce transmission congestion and renewable-energy curtailment, though implementing it at commercial scale requires coordination among operators, utilities, and customers.

The pro-development argument isn't that data centers have no cost. It's that refusing to build them doesn't eliminate demand. It sends the investment, tax revenue, and computing capacity elsewhere. Trump's "liquid gold" framing captures that view, even if it skips past the local trade-offs.

From resistance to rules
New York is the first state to impose a statewide moratorium, but it isn't acting alone. Lawmakers in 15 states have introduced legislation that would halt or restrict data center development, according to the National Conference of State Legislatures, while cities, counties, and townships have adopted local moratoriums rewriting zoning rules on noise, setbacks, water use, and electrical infrastructure. 

Heatmap News found that at least 20 proposed projects, representing more than $41.7 billion in planned investment, were canceled following local opposition in the first quarter of 2026 alone, a record for a single quarter.

The opposition doesn't follow a neat partisan pattern. Rural conservatives object to land seizures, transmission corridors, and threats to property values. Environmental groups focus on water, emissions, and fossil-fuel generation. Labor unions support construction jobs but may oppose blanket moratoriums. Consumer advocates worry about rates, and local officials want tax revenue but also want leverage.

That mixture may make the backlash more durable than a conventional left-versus-right fight. New York's approach tries to occupy the middle. The moratorium is temporary and doesn't declare data centers inherently undesirable; it gives regulators one year to write statewide environmental standards, cost-allocation rules, and a community-benefits framework that could require developers to pay directly for grid upgrades, disclose peak water use, meet noise standards, and fund community projects. Those requirements would make projects more expensive.

Supporters would call that accountability. Developers might call it a reason to build somewhere else. Both could be right.

AI needs infrastructure. It does not get a blank check.
The data center backlash is often portrayed as a collision between technological progress and public fear. That framing is too simple. Many opponents use cloud services and AI themselves. They aren't rejecting computation. They're asking why their town should provide the land, water, electricity, tax breaks, and political consent required to make somebody else's digital economy possible.

The industry's answer is that AI and cloud computing have become essential infrastructure, and building too slowly could constrain innovation and weaken economic competitiveness.

Communities have an equally strong response: essential infrastructure still requires rules. Airports face noise limits, factories face emissions permits, utilities face rate regulation, and stadiums negotiate public financing and community benefits. Data centers are not less physical simply because their product is digital.

Hochul's moratorium may eventually be remembered as a temporary political gesture. It may also mark the moment the AI infrastructure boom lost its assumption of automatic consent. The next phase will not be decided solely by who can build the largest model, buy the most GPUs, or raise the most capital. It will also be decided at utility commissions, zoning boards, town halls, and kitchen tables.

AI needs data centers. The question is whether the companies building them can convince communities that they need AI's infrastructure, too.