Our conception of AI is that it's a digital technology. It exists in the cloud and it doesn't have a physical manifestation. But the reality is that it has the largest physical footprint of any technology in history. To train and serve up AI models requires tangible, physical data centers. They are required for storing and processing data, text, images, code, and other information sources.
To train and run the more advanced AI models requires more and larger data centers than ever before. It's estimated that by the year 2030, companies will have invested nearly $7 trillion in data center infrastructure in a race to dominate the AI market. The amount of money that is being poured into building data centers is far beyond anything that was ever spent on the Apollo program to get the first man to the moon.
The four largest spenders on data centers — Google, Microsoft, Amazon, Meta — now spend more money building data centers each year than almost all the others combined. They call their data centers “campuses” — large tracts of land that rival the largest Ivy League universities, with several massive buildings densely packed with racks on racks of computers. Those computers emanate a huge amount of heat because of millions of power-hungry processing chips running the chatbots, agents, and other tools that millions of people interact with every day.
To keep them from overheating, the buildings have massive cooling systems — large fans, air conditioners, or systems that evaporate water to cool down the servers. The equipment all together creates a cacophony of humming, whirring, and crackling that can — especially in underdeveloped communities — be heard for miles, twenty-four hours a day, creating a relentless source of noise pollution.
According to the International Energy Agency, each ChatGPT query is estimated to need on average about ten times more electricity than a typical search on Google. One study found that producing one thousand pieces of text from generative models used as much energy on average as what it would take to charge the standard smartphone nearly four times. Generating one thousand images used on average as much energy as “as 242 full smartphone charges; in other words, every AI-generated image could consume enough energy to charge a smartphone by roughly 25 percent.
Developers and utility companies are now preparing for AI megacampuses that could soon require 1,000 to 2,000 megawatts of power. A single one could use as much energy per year as around one and a half to three and a half San Franciscos. By 2030, at the current pace of growth, AI computing globally could use more energy than all of India, the world’s third-largest electricity consumer.
The largest data centers are currently being constructed in the US. Take Stargate, one of the largest AI data centers in the world which is under construction in rural Texas. It will eventually include 4 million square feet of buildings across 1,100 acres. It already has 62 diesel generators and 10 gas-powered turbines on site, with plans for 41 more and it's just to power this data center. The largest one is being built by Meta in Louisiana which is roughly one fifth the size of Manhattan. If you add up just the three largest facilities in the world, the amount of energy that they demand almost matches the average power demand of New York City.
They are being built largely to meet demand for generative AI tools like chatbots. OpenAI reported that global use of chatbots more than doubled in the last year, going from 400 to 900 million users. Growth is the number one concern for all of these data centers. They are trying to beat everybody else in being the first to really harness the profitability around AI. And for them, that really means essentially getting as much power as fast as they can.
Big tech companies are projected to spend more than $800 billion on the infrastructure behind artificial intelligence in 2026. And in 2027, that number will exceed a trillion dollars. That's on par with the entire U.S. defense budget. Stargate's proposed on-site power plant could deliver more than 1.7 gigawatts of power. That's enough energy to power more than one million homes for a year. And the plant will emit more than 7.8 million tons of greenhouse gases each year. That's the annual emissions of about two million cars.
