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The surge in electricity demand from data centers is making innovation a necessity.

Electric utilities aren’t exactly known as innovators. Until recently, that caution seemed perfectly logical — arguably even preferable. If the entity responsible for keeping the lights on and critical services running decides to try out some shiny new tech that fails, heating, cooling, medical equipment, and emergency systems will all trip offline. People could die.
“It’s a very conservative culture for all the right reasons,” Pradeep Tagare, a vice president at the utility National Grid and the head of its corporate venture fund, National Grid Partners, told me. “You really can’t follow the Silicon Valley mantra of move fast, break things. You are not allowed to break things, period.”
But with artificial intelligence-driven load growth booming, customer bills climbing, and the interconnection queue stubbornly backlogged, utilities now face little choice but to do things differently. The West Coast’s Pacific Gas and Electric Company now has a dedicated grid-innovation team of about 60 people; North Carolina-based utility Duke Energy operates an emerging technologies office; and National Grid, which serves U.S. customers in the Northeast, has invested in about 50 startups to date. Some 64% of utilities have expanded their innovation budgets in the past year, according to research by National Grid Partners, while 42% reported working with startups in some capacity.
The innovators on these teams are well aware that their reputation precedes them when it comes to bringing novel tech to market — and not in a flattering way. “I think historically we’ve done a poor job partnering with too many companies and spreading ourselves thin,” Quinn Nakayama, the senior director of grid research, innovation, and development at PG&E, told me. That’s led to a pattern known as “death by pilot,” in which utilities trial many promising solutions but are too risk-averse, cost-conscious, and slow-moving to deploy them, leaving the companies with no natural customers.
It doesn’t help that regulators such as public utilities commissions understandably require new investments to meet a strict “prudency” standard, proving that they can achieve the desired result at the lowest reasonable cost consistent with good practices. Yet this can be a high bar for tech that’s yet untested at scale. And because investor-owned utilities earn a guaranteed rate of return on approved infrastructure investments, they’re incentivized to pursue capital-intensive projects over smaller efficiency improvements. Freedom from the pressure of a competitive market has also traditionally meant freedom from the pressure to innovate.
But that’s changing.
To help bridge at least some of these divides, National Grid Partners set up a business development unit specifically for startups. “Their sole job is to work with our portfolio companies, work with our business units, and make sure that these things get deployed,” Tagare told me. Over 80% of the firm’s portfolio companies, he said, now have tie-ups of some sort with National Grid — be that a pilot or a long-term deployment — while “many” have secured multi-million dollar contracts with the utility.
While Tagare said that National Grid Partners is already reaping the benefits from investments in AI to streamline internal operations and improve critical services, hardware is slower to get to market. The startups in this category run the gamut from immediately deployable technologies to those still five or more years from commercialization. LineVision, a startup operating across parts of National Grid’s service territories in upstate New York and the U.K., is a prime example of the former. Its systems monitor the capacity of transmission lines in real-time via sensors and environmental data analytics, thus allowing utilities to safely push 20% to 30% more power through the wires as conditions permit.
There’s also TS Conductor, a materials science startup that’s developed a novel conductor wire with a lightweight carbon core and aluminum coating that can double or triple a line’s capacity without building new towers and poles. It’s a few years from achieving the technical and safety validation necessary to become an approved supplier for National Grid. Then five or more years down the line, National Grid Partners hopes to be able to deploy the startup Veir’s superconductors, which promise to boost transmission capacity five- to tenfold with materials that carry electricity with virtually zero resistance. But because this requires cooling the lines to cryogenic temperatures — and the bulky insulation and cooling systems need to do so — it necessitates a major infrastructure overhaul.
PG&E, for its part, is pursuing similar efficiency goals as it trials tech from startups including Heimdell Power and Smart Wires, which aim to squeeze more power out of the utility’s existing assets. But because the utility operates in California — the U.S. leader in EV adoption, with strong incentives for all types of home electrification — it’s also focused on solutions at the grid edge, where the distribution network meets customer-side assets like smart meters and EV charging infrastructure.
For example, the utility has a partnership with smart electric panel maker Span, which allows customers to adopt electric appliances such as heat pumps and EV chargers without the need for expensive electrical upgrades. Span’s device connects directly to a home’s existing electric panel, enabling PG&E to monitor and adjust electricity use in real time to prevent the panel from overloading while letting customers determine what devices to prioritize powering. Another partnership with smart infrastructure company Itron has similar aims — allowing customers to get EV fast chargers without a panel upgrade, with the company’s smart meters automatically adjusting charging speed based on panel limits and local grid conditions.
Of course, it’s natural to question how motivated investor-owned utilities really are to deploy this type of efficiency tech — after all, the likes of PG&E and National Grid make money by undertaking large infrastructure projects, not by finding clever means of avoiding them. And while both Nakayama and Tagare can’t deny what appears to be a fundamental misalignment of incentives, they both argue that there’s so much infrastructure investment needed — more than they can handle — that the friction is a non-issue.
“We have capital coming out of our ears,” Nakayama told me. Given that, he said, PG&E’s job is to accelerate interconnection for all types of loads, which will bring in revenue to offset the cost of the upgrades and thus lower customer rates. Tagare agreed.
“At least for the next — pick a number, five, seven, 10 years — I don’t see any of this slowing down,” he said.
And yet despite all that capital flow, PG&E still carries billions of dollars in wildfire-related financial obligations after its faulty equipment was found liable for sparking a number of blazes in Northern California in 2017 and 2018. The resulting legal claims drove the utility into bankruptcy in 2019, before it restructured and reemerged the following year. But the threat of wildfires in its service territory still looms large, which Nakayama said limits the company’s ability to allocate funds toward the basic poles and wires upgrades that are so crucial for easing the congested interconnection queue and bringing new load online.
Nakayama wants California’s legislature and courts to revise rules that make utilities strictly liable for wildfires caused by their equipment, even when all safety and mitigation procedures were followed. “In order for me to feel comfortable moving some of my investments out of wildfire into other areas of our business in a more accelerated fashion, I have to know that if I make the prudent investments for wildfire risk mitigation, I’m not going to be held liable for everything in my system,” he told me.
And while wildfire prevention itself is an area rich with technical innovation and a central focus of the utility’s startup ecosystem, Nakayama emphasizes that PG&E has a host of additional priorities to consider. “We need [virtual power plants]. We need new technologies. We need new investments. We need new capital. We need new wildfire-related liability,” he told me.
Utilities — especially his — rarely get seen as the good guys in this story. “I know that PGE gets vilified a lot,” Nakayama acknowledged. But he and his colleagues are “almost desperate to try to figure out how to bring down rates,” he promised.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation.What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.