Data centers are swallow up the earthgoing up electricity billsand become a lightning rod for public discontent with the power of big tech in society.
the Maine legislature recently passed a data center ban in the state (but failed to override the governor’s veto). According to the National Conference of State Legislatures, 14 states spanning the political spectrum from Oklahoma to New York are considering legislation that would ban or suspend the opening of new data centers, such as public opinion on AI is more and more negative.
Yet despite public and political reluctance, there is a torrent of capital to build new data centers. America’s biggest tech companies are on track to spend as much as $1 trillion per year by 2027 on AI, according to recent Wall Street estimates. Globally, a recent McKinsey report predicts that spending on data centers will reach $7 trillion by 2030.
At the same time, the idea of bringing data centers closer to consumers, even inside their homes, is gaining traction in real estate circles. Major players in housing, including housebuilders Pulte Groupare currently being tested with Nvidia and California startup Span to install small, split data center “nodes” on the exterior walls of newly built homes, according to recent report by CNBC’s Diana Olick.
Whether this model can be scaled up and whether homeowners, HOAs and regulators will approve it is up for debate. Experts point to some advantages of home data centers, with the home network allowing for less construction of new centers and greater energy efficiency.
“It’s technically possible and already under study,” said Balaji Tammabattula, chief operating officer at BaRupOn, a U.S. energy and technology company currently building a data center campus in Liberty County, Texas. He said that just as a personal computer can contribute processing power to a distributed network, a home can host computing hardware that powers a larger data processing system.
Advocacy groups and community members protest laws surrounding data centers outside the Texas Capitol in Austin, Monday, Feb. 23, 2026.
Austin, American Statesman/Hearst Journals | Hearst Newspapers | Getty Images
The home as data center model would follow similar attempts to use latent data. domestic electricity for cryptocurrency mining or to sell excess rooftop solar or EV credits.
“Feasibility depends on available power, internet connectivity, heat management and the type of workload. For batch processing and non-urgent tasks, the home environment works surprisingly well,” Tammabattula said, although for high-density AI training or real-time workloads, residential constraints are more difficult to overcome.
Concrete examples are now being revealed as proof of concept, such as waste heat from data centers as this issue is receiving more attention in Europe. For example, a UK-based startup called Heat installs servers in homes that process cloud computing workloads while channeling the generated heat directly into the home’s hot water tank, providing homeowners with free hot water in exchange for hosting the hardware. British Gas supported a trial of this model.
On a larger scale, operations have just started for heat pumps that deliver waste heat from Microsoft data centers in Finland to heat the homes of around 250,000 local residents.
“These examples show that the concept works at both the household and community level,” Tammabattula said.
The home data center has a large number of advantages and disadvantages. On the positive side, the residential model reduces land and infrastructure requirements that become serious bottlenecks, distributes computing closer to end users and creates a natural incentive for homeowners through energy savings, Tammabattula said. He added that home computing also has a strong sustainability aspect since waste heat is reused rather than cooled at great expense.
But your questions for ChatGPT or Claude probably won’t soon be generated from a server in someone’s walk-in closet or basement, because these in-depth AI interactions still require sprawling data centers. Residential environments currently lack the power density, redundancy, physical security, and environmental controls that enterprise workloads require. And if you can’t get a signal for your own Wi-Fi network or phone calls, you can’t power a data center.
“The quality of connectivity varies between households, creating large-scale reliability issues. There are also regulatory and insurance issues regarding housing commercial equipment in private homes,” Tammabattula said.
Currently, the economics only work for specific workload types such as batch processing, rendering, and search computing. “Anything that requires guaranteed uptime or low latency is not yet suitable for this model,” he added.
Home data center vs. hyperscalerThe home data center is far more likely to become a niche layer of future infrastructure than a replacement for hyperscale data centers, given its limitations. Home data center models also typically involve a third party owning and operating the equipment, so the owner does not need to manage anything technically.
“Houses will not replace hyperscale data centers, especially for large AI training clusters that need dense power, high-speed networking, specialized cooling and tightly controlled environments,” said Gerald Ramdeen of Luxcore, a company developing next-generation optical networks and decentralized cloud infrastructure. A more realistic opportunity, he said, would be to transform homes into professionally managed edge computing nodes, useful for AI inference, low-latency workloads, flexible/batch computing, cloud gaming, and some heat reuse applications.
This approach has implications for everyday life as it increasingly intersects with and through AI.
“It can be used to sort through your teenage daughter’s seven billion photos,” said Sean Farney, vice president of data center strategy for the Americas at JLL, a U.S.-based global professional services and commercial real estate company that manages 4.4 GW of data center space worldwide from more than 340 data center locations.
Farney noted that your smartphone has more computing capacity than the first data center ever built. So while the idea of a home data center hasn’t taken off yet, it probably will. “It’s difficult to compete with a hyperscaler because maintaining a super distributed footprint is operationally expensive. But it can be done, and the successful company is looking at a good-sized valuation,” he said.
There are still some technical limitations to domestic data centers before success is possible on a commercial scale. On the one hand, the home should have a fairly reliable supply of electrical and mechanical resources, since Farney says a data center will outpace the residential power supply very quickly. “A 20-kilowatt residential generator doesn’t even get you an AI server cabinet,” he said.
But if technology is able to solve these problems, will homes be able to overcome the scale effect of data centers? Farney thinks the answer is yes.
AI Cybersecurity and Physical Security Are IssuesAimee Simpson, director of product marketing at Huntress, a global cybersecurity company, says one reason to be skeptical about the rise of home data centers is cybersecurity vulnerabilities.
“A collection of micro-data centers at home creates the need for a more robust network security approach,” Simpson said. Although a home network operating at scale has potential decentralization benefits (more sites means more redundancies in the event of a data center failure), expanding the footprint also makes security more complex.
“The hardware and software at each site should be secure and carefully monitored to avoid vulnerabilities,” Simpson said. The physical security of the site, meanwhile, “would be almost impossible to guarantee,” she said. “There’s a reason why the mega data centers run by Amazon and Microsoft are surrounded by high fences and guarded 24/7.”
The Microsoft data center campus, currently under construction, is reflected in Mount Pleasant, Wisconsin, September 18, 2025.
Audrey Richardson | Reuters
“I can’t imagine a world in which end users with data security and compliance obligations would be comfortable with the idea of their sensitive and confidential information being processed and managed by servers that are potentially in someone’s garage,” Simpson said. However, it is aware of legitimate networks of microdata centers that use tamper-proof physical containers. If these could be located in residences, it could alleviate some security concerns.
According to Arthur Ream, a professor of computer information systems at Bentley University, the home-as-datacenter model is plausible, already exists, and is a sensible answer to inference workloads and even training.
“The interesting question isn’t whether home computing works. It’s whether security, reliability and regulation hold up at the gigawatt scale or whether the industry has quietly figured out that the cheapest place to put operational risk from AI is in someone else’s laundry room,” Ream said.
Span is pioneering this model, according to Ream, with examples like work with Nvidia and PulteGroup where Span owns and installs liquid-cooled Nvidia RTX PRO 6000 Blackwell GPUs in residential homes, then sells the compute to hyperscalers and AI cloud providers while the homeowner gets a Span smart panel, battery backup and discounted pricing for r electricity and Internet. Homeowners pay fees of about $150 per month for electricity and Internet; installation is free while SPAN sells the compute to AI customers.
“The economic argument is one that needs to be taken seriously: a 100 MW data center costs around $15 million/megawatt and takes three to five years to build. Span says it can match that capacity by deploying XFRA nodes to 8,000 new homes in about six months at $3 million/megawatt.
Other experts are less circumspect and say the concept won’t work.
“Infrastructure for AI is not infrastructure for crypto. You don’t run data centers in basements,” said Sviat Dulianinov, chief strategy officer of Bright Machines, a San Francisco-based software and robotics company. Modern AI runs on “AI factories” made up of thousands of GPUs working together, requiring complex engineering, precision manufacturing, and tightly integrated supply chains: from server and rack construction to deployment. “It also requires industrial-scale power and cooling. Computing will move closer to the edge, but these will be standardized engineering systems rather than crowdsourced home data centers,” Dulianinov said.
And as data centers draw ire from communities from coast to coast, real estate professionals are closely following developments but have their own reservations about how residential communities will respond.
“HOAs would absolutely go to town on this idea,” said Jeff Lichtenstein, president and founder of Echo Fine Properties in Palm Beach Gardens, Florida. “I can’t even imagine our Facebook community page. Fights between data companies, cities and homeowners associations would make typical fights between Republicans and Democrats look like child’s play,” Lichtenstein said.
