For years, the “cloud” sounded weightless.
Data floated somewhere above us. The digital economy seemed to exist everywhere and nowhere at once.
But the cloud was never in the sky. It was always on land, plugged into the grid, cooled by water and air, and built in communities.
That reality has become impossible to ignore. The International Energy Agency projects that global electricity use from data centers could more than double by 2030. In the United States, the Electric Power Research Institute estimates that data centers could grow from roughly 4 to 5 percent of national electricity use today to 9 to 17 percent by the end of the decade.
That does not mean AI is bad. It does mean AI is physical.
And once a technology becomes physical, it has to contend with the world as it is: land, power, water, permitting, and trust.
I have spent much of my career in nuclear energy, and one thing I have learned is that the hardest problems are often outside the reactor. At Idaho National Laboratory, I helped launch the National Reactor Innovation Center, whose job was to help companies move from promising reactor designs on paper to real demonstrations in the world.
That meant engineering, but it also meant environmental review, local officials, state agencies, and communities that wanted to understand what might be built near them.
One moment stayed with me. We received a Freedom of Information Act request from a county commission asking about projects that could be built in their region. We sent the information, but more importantly, we reached out and offered to meet. The conversation that followed was constructive and necessary.
The lesson was simple: transparency cannot be an afterthought. AI infrastructure developers should learn that lesson now.
A data center may serve a global digital economy, but it lands in a specific town. The benefits may be national, but the burdens - construction traffic, land use, water concerns, power demand, transmission upgrades - are often local.
Nuclear energy has lived through this tension. It began with extraordinary promise: a tiny atom producing enormous amounts of energy, with hopes of abundance and national strength. Much of that promise was real. Nuclear power provides about one-fifth of America’s electricity and nearly half of its carbon-free electricity.
But the physics working was not enough.
Over time, construction became difficult. Costs rose. Regulation became essential, but also complex. Communities sometimes felt that decisions were being made around them, not with them. Even when nuclear projects delivered clean, reliable power, they also showed how easily trust can fray when people feel excluded, or asked to bear risks without clear benefits.
The lesson from nuclear is not that we should be less ambitious. It is that ambition only works when people can trust how it is being carried out.
The simple story about AI and energy is already taking shape: AI needs enormous amounts of power; nuclear can provide it; problem solved.
There is truth in that story. Nuclear energy may have an important role to play in powering the AI economy. Large technology companies are looking for firm, clean power, and nuclear energy is having its most promising moment in decades.
Vogtle Units 3 and 4 in Georgia show both the promise and the difficulty of nuclear’s comeback: they are now producing carbon-free electricity, but only after years of delay and major cost escalation. The lesson is not to give up, but to be clear-eyed about what it takes to build.
AI companies should not treat energy procurement as a back-office function or community engagement as a public-relations exercise. They should treat both as core to their business strategy.
That means engaging early, explaining what a project means for the community as well as the country, and being clear about power demand, water use, transmission needs, tax revenues, jobs, and who pays. It also means designing visible local benefits and working with utilities and regulators so the costs of serving large new loads do not quietly fall on households and small businesses.
This is not an argument for slowing down. It is an argument for building in a way that can last.
The United States needs AI infrastructure. It needs clean, reliable energy. It needs advanced manufacturing, electrification, climate resilience, and national security. But none of those ambitions will be achieved by software alone.
The future is not actually in the cloud. It is in communities. It is in steel and concrete. It is in people and institutions.
The real test for AI is not only whether it can transform the digital world, but whether it can be built responsibly in the physical one.