How much energy do data centers and artificial intelligence use?

I'm dismayed by the current political discourse on this topic. Seems like the two camps are 1) let mega corps build data centers with impunity or 2) use NIMBY tactics to oppose them in all cases.

I want to see a pro-growth approach that makes the mega corps assume the costs of their negative externalities. I want to see an increased build out of renewable and nuclear energy sources. I want to see environmental protections in place to limit impacts on aquifers and other water sources.

Democracies don't handle nuance well.

Something I havent heard alot of people talk about is meat. I dont think you can be against data centers, but also buy cheap meat. I understand food != compute, and thats a fact. BUT the same people who are protesting against AI data centers are the same people who fly every year, eat steak in every other dinner, and generally indulge in activities that are bad for the planet (and theres no acknowledgement).

Select quote:

* 5% of electricity in the United States is used to power data centers. For AI-focused ones specifically, it’s probably around 2%.*

I think it’s massive.

The author claims it's surprising that AI uses less electricity than the rest of data centers. Why?? Data centers do a million different things other than AI

I think its easy to forget how much energy is required to boil a liter of water, and these charts are a great reminder of the mundane things like that which escape our attention.

> For longer queries or requests that rely on AI agents or reasoning, the footprint is higher. Epoch AI estimated that a long query (7,500 words of input) could consume about 2.5 Wh, and a very long one (75,000 words) could consume 40 Wh. Those are far higher than the simple text query.

One thing that's missing from almost all of these energy estimates is the impact of "agentic" queries, which were rare a year ago and increasingly common today.

I've asked questions of GPT-5.6 Pro that take 19 minutes to return an answer, as the model runs hundreds of search and site navigation tool calls (and a bit of executed Python code too) trying to get to a credible answer.

I'm confident that 19 minutes involves a lot more than 75,000 words worth of tokens.

With coding agents we can at least get an accurate token count. I'm already at 204,000 tokens of GPT-5.6 Sol today and I haven't started work yet.

Remarkably, it took non-AI workloads 25 years to grow from zero to 3%, and it took AI only ~ 2.5 years to get to 2%.

This puts a number to my intuitive feeling that things move an order of magnitude faster this time.

We all just look at energy as a price. I think more people are concerned if our prices will go up, not how much energy it uses. The bigger question is water.

How much water do they use? Is it potable to begin with? Is it usable after? Will they drive prices up. These are one time builds with minimal jobs created after for a tech that could end my career. If I lose my job, I don’t also want to have no water and higher bills.

Our World in Data is great, but this article would've been improved if it offered a chart that offered a comparison to it's leading "1.5% of global electricity number".

For example: 7% to 10% of all global electricity is consumed by air conditioning. It's not hard to think of relatively small interventions that could save 1.5% of global energy use annually.

I presume running an electric shower includes heating up the water? Otherwise I don't understand how it could be so energy intensive. The energy is the mgh of the water lifted, plus the heat you put into it. Heat tends to be by far bigger in that calculation unless I've missed something.