PG&E entered 2026 expecting a year’s worth of new electricity demand. Barely two months later, nearly all of it was already spoken for. Interconnection requests were piling up faster than planners had expected, overwhelming a regulatory system built for an era when electricity demand barely moved.
That world is gone.
Load growth that historically ran below 1% annually hit 4% at some grid operators last year, according to a report by the Lawrence Berkeley National Laboratory. Bain and Company projects that AI data centers alone could consume up to 9% of total U.S. electricity by 2030, adding more than 150 terawatt-hours of demand that the current grid was never really built to handle. A third of that new demand is concentrated in Virginia, Texas, and California, according to Pew Research Center, putting extraordinary pressure on regional systems already straining to keep up.
AI may dominate the headlines, but it is only part of the story. EVs, new factories, and industries shifting off diesel and gas are all pulling from the same aging grid at the same time. At Southwest Power Pool, which oversees electricity across 17 states, officials compared last year’s surge in demand to two large nuclear plants suddenly appearing on a grid with roughly 56 gigawatts of capacity.
By late 2024, more than 2,600 gigawatts of proposed generation and storage projects were waiting to connect to the grid, according to Lawrence Berkeley National Laboratory, more than twice the country’s entire installed capacity. David Sawaya, PG&E’s director of rate-reducing load growth, says virtually every utility he knows has seen its interconnection queue swell by 50% to 150% in just two years. “The process does not move at the speed of business,” he tells Fast Company. “And right now, the business is moving very fast.”
A decade behind and racing to catch up
The utilities trying to manage this transformation are not exactly starting from a position of strength. Carlos Elena-Lenz, who leads digital enablement at Hitachi Energy, recalls a colleague who joined the company after decades in oil and gas offering a blunt assessment: Utilities globally are about a decade behind that industry in adopting AI.
The culture inside many utilities has historically been built around what Elena-Lenz calls a “break-fix” model, waiting for equipment to fail rather than predicting and preventing failure. Many utilities, he says, still cannot tell you with GPS-level precision where their own assets sit on the grid.
Then there is the data problem. Yuriy Yuzifovich, CTO of AI at GlobalLogic, a Hitachi subsidiary that builds digital systems for energy companies, says utilities often want AI systems their infrastructure simply cannot support. Equipment across the grid is already generating useful data, but much of it never reaches the enterprise systems designed to use it. And even when the data does make it through, utilities often lack the people or workflows needed to act on it.
“Intelligence is just the tip of the iceberg,” he says. The much larger challenge lies beneath it: rebuilding data infrastructure, changing internal processes, and retraining workforces to actually use these systems effectively.
Each new AI workload arriving on the grid creates pressure across three dimensions simultaneously: more power, more cooling, and more filtration. For an industry already a decade behind, that’s a significant amount of catching up to do.
Some progress is visible, however. Utilities that spent years asking what they should avoid are now asking what they can do. GlobalLogic is deploying AI systems inside utility operations that continuously predict where grid stress will appear hours before it materializes. Hitachi Digital has begun using synthetic data to replicate entire power-grid networks for testing, allowing models to be stress-tested against simulated conditions before touching live infrastructure.
THE REGULATORY WALL
As is often the case with technology, the tools to modernize the grid are moving faster than the rules written to govern them.
In conversation, Sawaya is careful to describe the California regulatory process as cumbersome rather than broken: a deliberate, stakeholder-driven structure built for a different era. Bringing a new proposal to the California Public Utilities Commission, gathering testimony, building a record, and securing a decision can take two years.
For a data center developer operating on a business timeline, that can kill a project before it properly begins. Richard Schomberg, special envoy for smart electrification at the International Electrotechnical Commission (IEC), puts an even harder number on the broader bottleneck: Interconnection timelines across the U.S. can stretch to seven years, constrained by transmission capacity, substation readiness, and a queue system designed for far lower volumes.
Jesse Jenkins, who leads the ZERO Lab at Princeton University, argues that the industry may be thinking about the problem in the wrong terms. “It doesn’t make sense to build a whole new transmission line that sits there 365 days a year when you only need it for a few hours a year,” he told Bloomberg News late last year. His research suggests that data centers willing to reduce their load during peak demand hours could connect to the grid years earlier—and at significantly lower cost—than those demanding guaranteed full power around the clock.
PG&E has responded with reforms worth examining. A proposal called Rule 30, approved by the California Public Utilities Commission in July 2025, requires large customers connecting to the transmission system to pay their full interconnection costs upfront, with reimbursement tied to the revenue their electricity consumption generates over time. If a data center commits, pays, and later scales back its power usage, minimum-demand fees ensure the shortfall does not fall on existing customers.
At Southwest Power Pool, a consolidated planning process pending federal approval promises to cut interconnection study timelines from more than a year to six months. A separate fast-track program, recently approved by federal regulators, can bring certain large-load and generation projects online in as little as 90 days.
These are real steps forward and, as Sawaya acknowledges, they come from a utility that has lived through enough operational and reputational crises to be deeply cautious about moving too fast on untested solutions. One utility in one state is still a long way from a national policy response.
BUILDING AROUND THE GRID
While utilities and regulators work through the constraints of the existing system, some companies have decided to build around them instead. For example, Charlotte Meerstadt, founder and CEO of Fram Energy, is building the financial infrastructure for an energy economy that is already reorganizing itself.
The shift from centralized to decentralized energy generation, where businesses generate their own power and sell it directly to buyers through long-term agreements, is growing at a compound annual rate of 30%, according to Meerstadt. The drivers are straightforward: rising energy costs, unreliable grid supply, and the appeal of locking in a fixed electricity rate for 20 to 25 years rather than absorbing whatever the market delivers.
The billing infrastructure for those transactions barely exists. Independent power producers, including solar farms, storage operators, and property owners selling power through direct agreements, typically manage billing through spreadsheets, manually shuttling data between operations and accounting teams.
One of Fram Energy’s customers had been underbilling by $150,000 over six months without realizing it. Another was spending $50,000 a month simply to get invoices out correctly and on time. Fram’s platform automates the process, handling more than 200 variables per bill across thousands of monthly transactions. It also shows buyers exactly what they would have paid at standard grid rates versus what they actually paid—a calculation most independent producers cannot perform on their own.
Meerstadt calls it the “Stripe for the decentralized energy future.” The decentralized energy market, she projects, could reach $2 trillion by 2034, making the infrastructure problem she is solving considerably larger than it might initially appear.
WHO PAYS FOR ALL OF THIS?
Schomberg is direct about where the cost burden currently sits. Tech companies are capturing enormous economic value from AI infrastructure while the capital costs required to enable that infrastructure are being socialized across millions of ratepayers who receive none of the upside.
He advocates for what he calls a “cost causation” principle: Those whose demands drive the investment should bear its cost. PG&E’s Rule 30 moves in that direction, but applying the same logic nationally would require the kind of coordinated policy response the U.S. energy regulatory system has not historically been built to deliver.
Rob Gramlich, president of the independent power sector consultancy Grid Strategies, thinks the political consequences of getting this wrong are already arriving. “I don’t think we’ve seen the end of the political repercussions,” he told CNBC in January. “And with a lot more elections in 2026 than 2025, we’ll see a lot of implications.” Retail electricity prices have already been rising faster than inflation since 2022 and are forecast to climb another 5% this year, according to a short-term energy outlook by the U.S. Energy Information Administration. For families and small business owners already stretched thin, those numbers are not mere abstractions.
Hitachi, GlobalLogic, PG&E, Southwest Power Pool, and Fram Energy are each solving a real piece of a very large problem. But the grid is ultimately a shared resource, and the question of who bears the cost of transforming it is as much a political one as a technical one. That debate is just getting started.
