In the US, AI has become one of the least liked things in public life.
That is not a rhetorical flourish. In the NBC News poll from early March, just 26 percent of voters had a positive view of AI and 46 percent a negative one, a margin of almost two to one. Here is where this could be heading, and most of the industry is not ready for it. On current trends, AI ends up regulated like a controlled substance. Licensed at the source, metered by how much it consumes, capped where the physical limits bite. Not because of what it might think. Because of what it drinks and what it burns, and because voters can now feel both on their utility bill.
For two years the public argument about AI was theatrical. Superintelligence, extinction, the machine that wakes up. That fight was always going to stay abstract, because nobody gets a bill for it. The fight that decides AI’s future is duller and already half over. It is about kilowatts and gallons.
Start with the meter. The 2024 Lawrence Berkeley National Laboratory report for the US Department of Energy puts data centers at about 4.4 percent of US electricity in 2023, heading to between 6.7 and 12 percent by 2028. In June, a UN University report projected that AI data centers will use roughly 9.3 trillion litres of water a year by 2030, the annual domestic water needs of 1.3 billion people. A single large site can draw up to 5 million gallons a day, the same as a town of 50,000. These are not projections about a model’s intelligence. They are projections about a town’s water table.
Then the politics. A cost you can see turns into a vote you can count. 78 percent of Americans worry that new data centers will push up their energy bills. An Economist and YouGov poll in May found over 70 percent think AI is moving too fast, and the split was almost even across parties, 68 percent of Republicans and 77 percent of Democrats. That last number is the one that matters. An issue this bipartisan does not fade after an election. It hardens into law.
And the law is already being written. In 2026, lawmakers in more than 30 states filed over 300 bills on data centers, from moratoriums to rules forcing operators to pay for their own power. More than 100 communities have enacted local moratoriums. In March, Senator Sanders and Representative Ocasio-Cortez introduced a federal bill to pause any data center drawing 20 megawatts or more until national safeguards exist. Notice the trigger. Not what the model can do. How much power it pulls. When you regulate a thing by metering its consumption and licensing its supply, you have stopped treating it as software. You are treating it the way states treat alcohol, or pharmaceuticals, or anything else society decided is useful but cannot be left to run open.
The control point makes the analogy literal. The EU AI Act already sets obligations for models trained above ten to the twenty-fifth floating-point operations. US reporting rules attach to similar training thresholds. Compute is the chosen lever for a reason. It is detectable, it is excludable, it is countable. So is a controlled substance. You can see it, you can restrict who gets it, you can measure the dose. The plumbing for a licensed, metered AI economy is not a future proposal. It is being installed now, one state bill and one compute threshold at a time.
Now the honest objection, because there is a good one. The industry says it will pay its own way. In March, the big developers signed a pledge to cover the full cost of the new power they need, and California, Ohio, and Utah have started writing that into law. If they fund their own generation, where is the problem.
The problem is that this concedes the point. The moment a cost is separately metered, allocated, and legislated, it stops being a free input and becomes a regulated one. A voluntary pledge is the soft version of a license, the industry writing its own rules before someone less friendly writes them instead. The other objection, that efficiency will outrun demand, runs into a century of evidence. Cheaper energy has never reduced total use. It expands it. Every gain in compute efficiency gets spent on more compute. The hinge does not stop squeaking. We just oil more hinges.
Two facts most coverage skips, because they decide who is right. First, the energy hog is not the dramatic training run everyone pictures. The UN report estimates 80 to 90 percent of AI energy goes to everyday use, the billions of small queries. What gets regulated is not a handful of giant labs. It is the ordinary act of using AI at scale. Second, the money has already committed. Big tech has staked roughly a trillion dollars on buildout against a public that is turning. That collision is not a debate anymore. It is a date on the calendar.
So the era of unlimited, unaccounted AI is closing, and from the most boring direction imaginable. Not a treaty on machine consciousness. A line item on a power bill in Ohio.
If you are building or buying AI, do one thing this quarter. Stop asking only whether it works, and start asking whether you can account for it. What it costs to run, what it draws, what its agents did and why. Treat that as a procurement requirement now, while it is still your choice and not yet a condition of your license.
Because of what AI might become. Not a free utility you plug in and forget, but something closer to a controlled substance. Useful, in demand, and increasingly sold under supervision. Licensed at the source, metered by the dose, available mainly to those who can show what they did with it. We have done this before with everything society decided was too powerful to leave unwatched, from alcohol to medicine to money itself. AI could be next in that line. If it is, the companies that come through will not be the ones holding the most powerful model. They will be the ones holding the paperwork.
