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Wednesday, February 5, 2025

New Infrastructure Costs for AI — Utility Bills


Demand for artificial intelligence, from generative AI to the development of artificial general intelligence, puts greater burdens on power plants and water resources, which might also put the pinch on surrounding communities.

The need to feed power to the digital beast to support trends, such as the rise of cryptocurrency, is not new but the persistent demand to build and grow AI calls new attention to the limits of such resources and inevitable rises in price.

“The growth in power utilized by data centers is unprecedented,” says David Driggers, CTO for cloud services provider Cirrascale. “With the AI boom that’s occurred in the last 18 to 24 months, it is literally unprecedented on the amount of power that’s going to data centers and the projected amount of power going into data centers. Dot-com didn’t do this. Linux clustering did not this.”

The hunger for AI led to a new race for energy and water that can be very precious in some regions. The goal might be to find a wary balance, but for now stakeholders are just looking for ways to keep up. “Data centers used to take up 1% of the world’s power, and that’s now tripled, and it’s still going up,” Driggers says. “That’s just insane growth.”

In recent years, chipmakers such as Nvidia and AMD saw their sales to data centers ramp up in response to demand and expectations for AI, he says, as more users and companies dove into the technology. “A big part of it is just the power density of these platforms is significantly higher than anything that’s been seen before,” Driggers says.

Related:Digital Mindset: The Secret to Bottom-Up GenAI Productivity

Feeding the Machines

There was a time when an entire data center might need one megawatt of power, he says. Then that became the power scale to support just a suite — now it can take five megawatts to do the job. “We’re not a hyperscaler but even within our requirements, we’re seeing over six months, our minimum capacity requirements are doubling,” Driggers says. “That’s hard to keep up with.”

The runaway demand might not be simple to respond to given the complexities of regulations, supply, and the costs this all brings.

Evan Caron, co-founder and chief investment officer, Montauk Climate, says a very complicated interdependency exists between public and private infrastructure. “Who bears the cost of infrastructure buildout? What markets are you in? There’s a lot of nuance associated with where, what, when, how, et cetera.”

There is no catchall answer to this demand, he says, given local and regional differences in resources and regulations. “It’s very hard to assume the same story works for every part, every region in the US, every region globally,” Caron says, “who ultimately bears the cost, whether it’s inflationary, whether it’s ultimately deflationary.”

Related:AI’s Hidden Cost: Will Data Preparation Break Your Budget?

Even before the heightened demand for AI, data centers already came with significant utility price tags. “Generally speaking, a data center uses a lot of land, a lot of water — fresh water — a lot of power,” Caron says. “And you need to be able to build infrastructure to support the needs of that customer.”

Depending on where in the US the data center is located, he says there can be requirements for data centers to build substations, transmission infrastructure, pipeline infrastructure, and roads, which all add to the final bill. “Some of it will be borne by the consumers in the market,” Caron says. “The residential customers, the commercial customers that aren’t the data center are going to get charged a share of the cost to interconnect that data center.”

Still, it is not as simple as hiking up prices any time demand increases. Utility companies typically must present before their respective utility commissions the plans to provide those services, their need to build transmission lines, and more to determine whether it is worth making such upgrades, Caron says.

Related:The Real Cost of AI: An InformationWeek Special Report

“That’s why you’re seeing a lot of pushback,” he says, “because the assets that are going behind the meter get unfair subsidies from a utility, from a transmission company, from a generation company.” This can increase costs passed on to other consumers.

It does not have to be that way though. If hyperscalers were required to front the entire bill for such new infrastructure, Caron says, it could be argued that it would be a benefit to the rest of the customers and community. However, that is not the current state of affairs. “They’re not interested in bearing the cost across the board” he says, “so they’re pushing a lot of those costs back to consumers.”

The first several years of such buildouts could be very inflationary, Caron says. The promise of AI — to deliver smarter systems that are more efficient with lower costs of living — would ultimately be deflationary. In the near term, however, there is a supply and demand imbalance, he says. “You have more demand than supply; prices have to rise to meet that.”

That could lead to increased costs across technology-driven regions with elevated competition for resources. “It’s going to be very inflationary for a long time,” Caron says.

He foresees the Trump administration moving to rip out regulation based on a narrative that these processes can be easier, but state governments and the federal governments have distinct powers that can make this more complex than solving the problem with the stroke of one pen “Utilities are regulated monopolies in the state,” Caron says. “There’s almost 3,000 separate utilities in North America.”

Multiple stakeholders, incumbent energy companies, independent power producers, and the fairness doctrine around antitrust are all elements that come into play in this energy race. “You’re not going to get everyone to be aligned around the same set of expectations,” Caron says.

Consumers want prices to go down, he says, while energy generators can want prices to go up, transmission companies get a regulated rate of return, and public utility commissions are responsible for the protection of consumer interests. “You don’t have a situation where this is a cooperative game,” Caron says. It is a multi-stakeholder systems approach and it’s not going to be that easy to solve all the problems in a short period of time.”

A complex lattice of operators, state law, co-ops, government agencies, commissions, and federal involvement that all come into play as well. “It is not obvious how this can be solved quickly.”

The near-term demand for power could have a historic impact. “It’s probably the second time in modern history where we’ve had to completely rethink how power markets evolve and how power markets grow and scale,” he says.

Not a Drop to Drink

That still does not even include water in the equation yet. “Water is a scarce resource,” Coran says. “Data centers use five million gallons a day of water. That water’s got to come from somewhere.” It can come from brackish water or greywater systems, he says, as well as from fresh water. That demand can compete with residential water systems and hospital water systems.

Could demand and the cost of these resources push systems to their breaking point, where supply simply cannot keep up? He says the recent executive orders issued around creating a national energy emergency likely would not emerge if demand remained moderate.

Improved efficiencies and upgraded systems contributed to deflationary energy loads in some energy markets, Caron says. “We weren’t in an energy crisis,” he says. “We were actually retiring power plants. We had too much. We were in an abundance scenario.” That honeymoon with energy seems over with have changed with the swelling demand for power to support technology such as data centers and AI.

“The reason why we’re in an energy crisis now, and that’s why the Trump administration has issued an executive order for an emergency an energy crisis, is we do not have the resources today,” Caron says, The national priority, including national security, placed on owning AI and data center infrastructure means more power and other resources will be necessary. “Without mobilizing every bit of the economy, like it’s almost wartime mobilization, we will run out of those resources to be able to support the load growth that people are predicting for AGI, AI, inference, and LLM. We just don’t have it.”



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