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Plus, which is the best hyperscaler on climate — and which is the worst?

The biggest story in energy right now is data centers.
After decades of slow load growth, forecasters are almost competing with each other to predict the most eye-popping figure for how much new electricity demand data centers will add to the grid. And with the existing electricity system with its backbone of natural gas, more data centers could mean higher emissions.
Hyperscalers with sustainability goals are already reporting higher emissions, and technology companies are telling investors that they plan to invest hundreds of billions, if not trillions of dollars, into new data centers, increasingly at gigawatt scale.
And yet when we asked our Heatmap survey participants “Do you think AI and data centers’ energy needs are significantly slowing down decarbonization?” only about 34% said they would, compared to 66% who said they wouldn’t.
There were some intriguing differences between different types of respondents. Among our “innovator” respondents — venture capitalists, founders, and executives working at climate tech startups — the overwhelming majority said that AI and data centers are not slowing down decarbonization. “I think it’s the inverse — I think we want to launch the next generation of technologies when there’s demand growth and opportunity to sell into a slightly higher priced, non-commoditized market,” Joe Goodman co-founder and managing partner at VoLo Earth Ventures, told us.
Not everyone in Silicon Valley is so optimistic, however. “I think in a different political environment, it may have been a true accelerant,” one VC told us. “But in this political environment, it’s a true albatross because it’s creating so many more emissions. It’s creating so much stress on the grid. We’re not deploying the kinds of solutions that would be effective."
Scientists were least in agreement on the question. While only 47% of scientists thought the growth of data centers would significantly slow down decarbonization, most of the pessimistic camp was in the social sciences. In total, over 62% of the physical scientists we surveyed thought data centers weren’t slowing down decarbonization, compared to a third of social scientists.
Michael Greenstone, a University of Chicago economist, told us he didn’t see data centers and artificial intelligence as any different from any other use of energy. “I also think air conditioning and lighting, computing, and 57,000 other uses of electricity are slowing down decarbonization,” he said. The real answer is the world is not trying to minimize climate change.”
Mijin Cha, an assistant professor of environment studies at the University of California Santa Cruz, was even more gloomy, telling us, “Not only do I think it’s slowing down decarbonization, I think it is permanently extending the life of fossil fuels, especially as it is now unmitigated growth.”
Some took issue with the premise of the question, expressing skepticism of the entire AI industry. “I’m actually of the opinion that most of the AI and data center plans are a massive bubble,” a scientist told us. “And so, are there plans that would be disruptive to emissions? Yes. Are they actually doing anything to emissions yet? Not obvious.”
We also asked respondents to name the “best” and “worst” hyperscalers, large technology companies pursuing the data center buildout. Many of these companies have some kind of renewables or sustainability goal, but there are meaningful differences among them. Google and Microsoft look to match their emissions with non-carbon-power generation in the same geographic area and at the same time. The approach used by Meta and Amazon, on the other hand, is to develop renewable projects that have the biggest “bang for the buck” on global emissions by siting them in areas with high emissions that the renewable generation can be said to displace.
Among our respondents, the 24/7 “time and place” approach is the clear winner.
Google was the “best” pick for 19 respondents, including six who said “Google and Microsoft.” By contrast, Amazon and Meta had just three votes combined.
As for the “worst,” there was no clear consensus, although two respondents from the social sciences picked “everyone besides Microsoft and Google” and “everyone but Google and Microsoft.” Another one told us, “The best is a tie between Microsoft and Google. Everyone else is in the bottom category.”
A third social scientist summed it up even more pungently. “Google is the best, Meta is the worst. Evil corporation” — though with more expletives than that.
The Heatmap Insiders Survey of 55 invited expert respondents was conducted by Heatmap News reporters during November and December 2025. Responses were collected via phone interviews. All participants were given the opportunity to record responses anonymously. Not all respondents answered all questions.
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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.