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The major U.S. automakers are catching up on Tesla’s power game.

It was my first truck-powered cocktail party.
General Motors had gathered journalists at a Beverly Hills mansion last week for a vehicle-to-home show and tell. GM’s engineers outfitted the garage with all the components needed for an electric vehicle’s battery to back up the house’s power supply. Then they tripped the circuit breaker to cut off the home from grid power and let the plugged-in Chevy Silverado electric pickup run the home’s lights and other electrical systems for the remainder of the gathering.
V2H tech, as it’s known, will be available in the top-of-the-line Silverado EV First-Edition RST that will begin deliveries in the middle of this year, making the Chevy competitive with its natural rival, the electric Ford F-150 Lightning. The Ford, released just two years ago, was one of the first American EVs to use bidirectional charging to let the vehicle battery to power the home. Soon, though, V2H may be commonplace: GM promises to put it not just in all its new electric trucks, but also in all the new EVs it’s building on the new Ultium platform by 2026, which may force other automakers to follow suit.
These moves aren’t just about a new feature to highlight in truck commercials. In the EV age, car companies have to become energy companies, too.
GM has spun off a whole new group, GM Energy, just to handle all the ways its electric Chevrolets and Cadillacs will interface with the integrated home. In its simplest guise, V2H, the system requires several boxes mounted to the wall in the garage. There’s a “dark start” battery to make sure the backup system has enough juice to get going again in case of power outage; and there’s an inverter to turn the DC electricity from a truck battery into AC for the house. The GM’s PowerShift charger refills the EV battery, but also allows energy to flow both ways.
That’s just the beginning. GM Energy is also introducing stackable PowerBank batteries a person could keep in their basement or garage. The company will add the ability to integrate solar panels into the system later in 2024, according to Chief Revenue Officer Aseem Kapur.
With these new pieces in place, energy can move around a person’s home in any direction. On a very sunny day, excess solar energy could be routed to the house’s battery stack — just as, at the scale of the utility grid, excess power from solar farms is stashed away in batteries during the afternoon to provide energy at night. The home’s battery stack could be used to back up the power supply in case of outage (just in case your Silverado isn’t plugged in at the time).
And the next stage is coming soon. Kapur said that by 2026, GM’s Ultium EVs will be equipped with vehicle-to-grid — V2G — capability. Today, some residents with home energy storage are using their stashed kilowatt-hours to participate in a virtual power plant; they engage in energy arbitrage by storing electricity when it’s cheap and selling it back to the grid when it’s expensive, making money in the process. V2G represents one step further. EVs that can talk to the grid could help to prevent blackouts and let their drivers engage in energy arbitrage using the battery in their pickup truck while it’s parked in the driveway. (For what it’s worth, Kapur told me the charging and discharging cycles from doing this are much easier on the EV’s battery life than the herky-jerky, stop-and-start nature of driving.)
It turns out that electrification is a multi-pronged revolution in the car business. First came the cars. As Heatmap has reported, Tesla’s enormous lead in selling EVs has eroded as the big companies’ electric offerings have improved and Musk became distracted with Twitter, Cybertrucks, and robotaxis.
The energy business marks another way the old-fashioned car companies are finally catching up to Elon Musk. Tesla for years has sold its own solar panels and Powerwall home batteries. It set up a virtual power plant in Texas to allow its solar and battery customers to make money on the energy markets. Suddenly, Detroit is moving into that space.
GM Energy’s home-of-the-future system will be sold as an added feature for people who buy an EV like the Silverado and want to back up their home electricity, but anybody — Chevy driver or no — could buy into the interconnected residential energy system. Ford’s Home Integration System performs the same function. At CES in January, Kia demonstrated an entire connected home to evangelize the potential of V2H and V2G. It won’t be long before all the major automakers have a similar solution on offer.
Of course, the home is just one part of the new energy ecosystem. In the days of gasoline, the oil companies controlled refueling and filled the country with Chevron and Texaco stations on every corner. But in the electric age, the carmakers are trying to exert more control on that market. Tesla appeared to grab the early lead in fast-charging stations, then it convinced the other automakers — GM and Ford included — to adopt its plug standard in their EVs so their customers could take advantage of Tesla’s charging network.
But with recent mass layoffs to Tesla’s Supercharger team, that advantage is in doubt. Musk may have opened the door for the other carmakers to swoop in. GM was among seven automakers that, earlier this year, pledged to build out 30,000 new fast-charging stations of their own by the decade’s end. As car companies continue to build out their energy businesses, they’ll keep creeping up on Tesla’s territory there. Then Musk really better hope that the robotaxi pans out.
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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.