Sam Altman is thinking big. Really big. The OpenAI CEO has just unveiled plans for AI infrastructure that would consume as much electricity as New York City and San Diego combined. His vision? Create enough computing power to potentially cure cancer and revolutionize education worldwide.
But experts are raising serious questions. Is this ambitious expansion necessary for AI progress, or are we heading toward an environmental disaster?
The Staggering Scale of Altman’s AI Empire
Picture this: every air conditioner in New York City running on a sweltering summer night. Add every subway car humming underground and towers blazing with light. Now imagine San Diego during a record-breaking heat wave, when demand shot past 5,000 megawatts and the grid nearly buckled.
That’s the scale of electricity Altman and his partners say their next wave of AI data centers will devour. We’re talking about a single corporate project consuming more power every day than two American cities pushed to their breaking point.
The numbers are mind-boggling. OpenAI announced plans with Nvidia to build AI data centers consuming up to 10 gigawatts of power. Additional projects totaling 17 gigawatts are already in motion. To put this in perspective, that’s roughly equivalent to powering New York City during summer peak demand and San Diego during its most intense heat wave of 2024.
“It’s pretty amazing,” says Andrew Chien, a professor of computer science at the University of Chicago. “A year and a half ago they were talking about five gigawatts. Now they’ve upped the ante to 10, 15, even 17. There’s an ongoing escalation.”
The Promise of “Abundant Intelligence”
Altman frames this massive expansion as essential for humanity’s future. In his recent blog post titled “Abundant Intelligence,” he paints a picture of AI solving our biggest challenges.
“If AI stays on the trajectory that we think it will, then amazing things will be possible,” Altman writes. “Maybe with 10 gigawatts of compute, AI can figure out how to cure cancer. Or with 10 gigawatts of compute, AI can figure out how to provide customized tutoring to every student on earth.”
His logic is straightforward: if we’re limited by computing power, we’ll have to choose between curing cancer and educating every child. Nobody wants to make that choice, so let’s build enough infrastructure to do both.
The OpenAI CEO envisions creating “a factory that can produce a gigawatt of new AI infrastructure every week.” It’s an audacious goal that would require breakthroughs across chips, energy, robotics, and construction.
A “Seminal Moment” for Computing
For computer science experts, this announcement represents a watershed moment. Chien, who has been in the field for 40 years, calls it something he’s been waiting to see.
“For most of that time computing was the tiniest piece of our economy’s power use,” he tells Fortune. “Now, it’s becoming a large share of what the whole economy consumes.”
The shift is both thrilling and terrifying. Computing could represent 10% or 12% of the world’s power consumption by 2030. We’re approaching what Chien calls “seminal moments for how we think about AI and its impact on society.”
Fengqi You, an energy-systems engineering professor at Cornell University, puts the scale in global terms. “Ten gigawatts is more than the peak power demand in Switzerland or Portugal,” he explains. “Seventeen gigawatts is like powering both countries together.”
The Energy Challenge: Nuclear Dreams vs. Reality
Altman has made no secret of his preferred energy source: nuclear power. He’s backed both fission and fusion startups, betting that only reactors can provide the steady, concentrated output needed to feed AI’s insatiable appetite.
“Compute infrastructure will be the basis for the economy of the future,” Altman declares, positioning nuclear as the backbone of that future.
But experts are skeptical about the timeline. Chien is blunt about nuclear’s near-term limitations: “As far as I know, the amount of nuclear power that could be brought on the grid before 2030 is less than a gigawatt. So when you hear 17 gigawatts, the numbers just don’t match up.”
With projects demanding 10 to 17 gigawatts, nuclear is “a ways off, and a slow ramp, even when you get there,” Chien notes. Instead, he expects wind, solar, natural gas, and new storage technologies to dominate in the short term.
You strikes a middle ground, suggesting nuclear may be unavoidable long-term if AI keeps expanding. However, he cautions that “in the short term, there’s just not that much spare capacity” whether fossil, renewable, or nuclear.
“A typical nuclear plant takes years to permit and build,” You explains. “In the short term, they’ll have to rely on renewables, natural gas, and maybe retrofitting older plants. Nuclear won’t arrive fast enough.”
Environmental Concerns Mount
The environmental implications are staggering. Experts worry about the hidden costs of consuming this much electricity for AI.
“We have to face the reality that companies promised they’d be clean and net zero, and in the face of AI growth, they probably can’t be,” Chien warns.
The concerns extend beyond carbon emissions. Cooling these massive data centers alone can consume vast amounts of fresh water in regions already facing scarcity. The rapid hardware turnover—with new Nvidia processors rolling out annually—creates waste streams laced with toxic chemicals.
You points to additional ecosystem risks: “If data centers consume all the local water or disrupt biodiversity, that creates unintended consequences.”
The Texas grid, where Altman broke ground on one project this week, typically runs around 80 gigawatts. “So you’re talking about an amount of power that’s comparable to 20% of the whole Texas grid,” Chien calculates. “That’s for all the other industries—refineries, factories, households. It’s a crazy large amount of power.”
The Business Case: Massive Investments and Partnerships
The financial scale matches the energy ambitions. Each OpenAI site is valued at roughly $50 billion, adding up to $850 billion in planned spending. Nvidia alone has pledged up to $100 billion to back the expansion, providing millions of its new Vera Rubin GPUs.
These aren’t just theoretical plans. OpenAI has already closed a massive $300 billion cloud deal with Oracle and signed strategic partnerships with multiple infrastructure providers.
Altman justifies the expansion by pointing to explosive growth in AI usage. ChatGPT usage has jumped 10-fold in the past 18 months, he notes. “This is what it takes to deliver AI,” he said during a recent Texas groundbreaking ceremony.
Strategic Implications for America
Altman emphas izes building this infrastructure in the United States, framing it as both technically and strategically imperative to keep America competitive in the global AI race.
He’s expressed concern that progress on chip manufacturing and energy production has lagged behind other nations. The massive infrastructure build-out represents his answer to maintaining American AI leadership.
The company plans to reveal more details in coming months, including specific partners and financing mechanisms. Altman has hinted at innovative funding approaches that link increased computing capacity directly with revenue growth.
Expert Warnings About the Path Ahead
While Altman’s vision is compelling, experts urge caution about the broader implications.
“They told us these data centers were going to be clean and green,” Chien observes. “But in the face of AI growth, I don’t think they can be. Now is the time to hold their feet to the fire.”
The timeline concerns are equally pressing. You questions whether the ambitious expansion can happen as quickly as planned: “How can we expand this capacity in the short term? That’s not clear.”
Beyond technical challenges, there’s a need for broader societal conversation about AI’s environmental costs. The hidden strains on water supplies, biodiversity, and local communities near massive data centers require careful consideration.
The Road Ahead
Altman’s vision of “abundant intelligence” represents either humanity’s next great leap forward or a potentially catastrophic miscalculation. The infrastructure he’s proposing would fundamentally reshape global energy consumption and computing capacity.
Whether this massive expansion delivers on its promises of curing cancer and revolutionizing education remains to be seen. What’s certain is that we’re entering uncharted territory where a single company’s computing needs rival those of entire nations.
The coming months will reveal crucial details about partnerships, financing, and implementation timelines. But one thing is already clear: the age of abundant intelligence, if it arrives, will come with an unprecedented appetite for power.
As Chien puts it, we’re approaching “seminal moments” that will define AI’s impact on society. The question isn’t whether we can build Altman’s AI empire—it’s whether we should.
