Wolf&Grayson EditorialA surge in hyperscale data centers marks a structural inflection point for the energy sector, introducing explosive load growth into systems designed around predictability. For consumer-owned utilities, that shift means moving from decades of steady, predictable demand tied to population and economic growth to preparing for single projects that can require multiple gigawatts at once.
But for distribution utilities reliant on the market or a wholesale power provider, there are different risks to the data center boom. “This could be absolutely seismic if wholesale providers would rather serve this large new lucrative load than the traditional distribution utilities,” says Elizabeth K. Whitney, Managing Principal of Meguire Whitney, LLC.
She helps municipal utilities, cooperatives, and other not-for-profit energy providers navigate federal energy policy in Washington, where artificial intelligence has become a key focus in energy debates amid a broader reordering of market priorities. Whitney’s work focuses on how federal and regional frameworks are adapting to unprecedented load growth and what that means for community-based providers. At the heart of her concern is the precedent created when communities and ratepayers are sidelined in favor of higher-paying, high-profile projects.
“This is going to dramatically change policy and markets and the way we think about energy,” Whitney says. That realization came into sharp focus when a large wholesale power provider advised several distribution cooperatives to seek alternative supply contracts because it preferred to sell its existing generation to a hyperscale facility. “Legacy community relationships could be displaced by the economics of hyperscale demand,” Whitney says. If wholesale suppliers consistently favor hyperscalers, distribution utilities may be squeezed on supply, pushed into unfamiliar markets, or forced to compete for generation, labor, and materials.
Political Pressure And The New Asymmetry
The imbalance between global technology firms and community-based utilities is not just financial. It is political, and the urgency can tilt regulatory and legislative attention toward hyperscalers, sometimes at the expense of smaller players. “There is a huge national push to accomplish AGI and dominate in the global AI race that really does not want to wait around for the utility sector to figure out how to accommodate massive new loads,” Whitney says.
At the same time, hyperscalers are shifting strategy. Rather than relying solely on local utilities for generation, many are exploring building their own power resources on site. “They are increasingly looking at bringing their own generation to those hyperscale campuses,” she says. In some cases, that approach can appear to bypass the utility altogether.
The grid still matters, however. Transmission access, interconnection rights, and participation in regional markets remain critical for efficiency and financial optimization. Utilities possess deep knowledge of regional energy markets and infrastructure constraints. That institutional expertise is a form of leverage, even when capital flows favor the technology sector.
Three Moves That Define The First Year
If a consumer-owned utility receives a call about a major AI data center, Whitney believes the first twelve months are decisive, and she shares three moves that can help utilities manage risk. The initial question is how real the project is and how dependent it will be on grid interconnection. Utilities must understand what they uniquely bring to the table. Transmission capacity, in particular, can be a pivotal asset. “If you have transmission capacity, that is something the hyperscaler cannot necessarily build itself within the fence line of their own facility,” she says.
Second, utilities must scrutinize market design and cost allocation. In restructured markets such as PJM, policymakers are actively debating whether existing frameworks can handle explosive load growth rather than incremental increases. The central issue is cost causation. Who pays for new generation, transmission upgrades, and reliability backstops? Ensuring that the costs of expansion remain with the large new customer is essential to protecting existing ratepayers.
Third, utilities must shape the community narrative early. Data centers raise questions that go beyond electricity bills. Water usage, land use, and noise have all surfaced as concerns in regions experiencing dense development. Utilities are at the center of broader conversations about siting and zoning. Preparing clear, transparent explanations of benefits and safeguards can prevent backlash later.
Resource Adequacy In An Uncertain Future
The deeper challenge lies in long-term planning. AI may accelerate demand today, but technological shifts could just as easily alter the trajectory tomorrow. Whitney points to the experience with crypto mining, where large loads appeared and then receded, leaving utilities exposed to stranded costs. “We plan to be here for the next hundred years,” she says. “Is this data center going to be demanding this large load for that long, or even a 30-year resource planning horizon?”
That question goes to the heart of resource adequacy policy. If load growth is neither incremental nor guaranteed to persist, traditional planning models may falter. Durable policy must account for volatility while safeguarding community-owned utilities and the consumers they serve.
Complicating matters further, change is outpacing regulation. “We are constantly aiming at fixing a problem that has already morphed into something else,” Whitney says. By the time a federal docket opens and a technical conference is held, market realities may have shifted again. The solution is not to freeze progress but to design flexible frameworks capable of adapting across multiple scenarios.
For consumer-owned utilities, the AI data center boom is both opportunity and stress test. It exposes weaknesses in market design, amplifies political asymmetries, and forces difficult conversations about cost and risk. “We have to be nimble and think about what this looks like a year out, five years out, 10 years out, and how to structure durable policy that can ride through those iterations.”
Follow Elizabeth K. Whitney on LinkedIn or visit her website for more insights.
