Google has released its 2024 Environmental Report, an 80-plus page document detailing all of the giant company’s efforts to apply technology to environmental problems and limit its own contributions. But it completely dodges the question of how much energy AI uses — perhaps because the answer is “a lot more than we’d like to say.”
You can read the full report here (PDF)and honestly, there's a lot of interesting stuff in there. It's easy to forget how many plates a company the size of Google keeps spinning, and there's some really remarkable work in there.
For example, work is being done on a water replenishment programwhich it hopes will offset the water use in its facilities and operations, ultimately having a net positive effect. It does this by identifying and funding watershed restoration, irrigation management, and other work in that area, with dozens of such projects around the world funded at least in part by Google. It has replaced 18% of its water use (by whatever definition of that word is used here) in this way, and is improving every year.
The company also makes a big deal about highlighting the potential benefits of AI in the climate, such as optimizing irrigation systems, creating more fuel-efficient routes for cars and boats, and predicting flooding. We’ve highlighted a few of these in our AI coverage , and they could be quite useful in many areas. Google doesn’t have to do this, and many big companies don’t either. So credit where credit’s due.
But then we get to the part called “Responsibly Managing AI’s Resource Consumption.” Here Google, so confident in every statistic and estimate up until now, suddenly spreads its hands and shrugs. How much energy does AI consume? Can anyone Real be sure?
Still, it must be bad, because the first thing the company does is downplay the entire data center energy market, saying it’s only 1.3% of global energy consumption, and the amount of energy Google uses is at most 10% of that — so only 0.1% of the world’s energy powers its servers, according to the report. Small feat!
Interestingly, the company decided in 2021 that it wanted to reach net zero emissions by 2030, though the company admits there is a lot of “uncertainty,” as it likes to put it, about how that will actually happen. Especially since emissions have increased every year since 2020.
By 2023, our total greenhouse gas emissions will [greenhouse gas] emissions amounted to 14.3 million tons of CO2e, representing a 13% year-over-year increase and a 48% increase compared to our base year 2019. This result was primarily due to increases in data center energy consumption and supply chain emissions. As we further integrate AI into our products, reducing emissions may be challenging due to the increasing energy demand from the greater intensity of AI computing and the emissions associated with the expected increase in our investments in technical infrastructure.
(Emphasis mine in this quote and in the quote below.)
Yet, the growth of AI is lost in the aforementioned uncertainties. Google has the following excuse for why it is not specific about the contribution of AI workloads to its overall data center energy bill:
Predicting the future environmental impact of AI is complex and evolving, and our historical trends likely do not fully capture the future direction of AI. As we deeply integrate AI into our product portfolio, the distinction between AI and other workloads will not be meaningful. So we focus on datacenter-wide metrics because they encompass the total resource consumption (and thus environmental impact) of AI.
“Complex and evolving”; “the trends probably don’t capture it completely”; “the distinction…won’t be meaningful”: this is the kind of language used when someone knows something but would really, really rather not tell you.
Does anyone really believe that Google doesn’t know, down to the penny, how much AI training and inference has contributed to its energy costs? Isn’t it part of the company’s core competency to break those numbers down so precisely in terms of cloud computing and data center management? It has all these other explanations about how efficient its custom AI server units are, how it does all that work to reduce the energy required to train an AI model by 100x, and so on.
I have no doubt that there are many great green efforts going on at Google, and you can read all about them in the report. But it’s important to emphasize what the company seems to refuse to address: the enormous and growing energy costs of AI systems. The company may not be the single biggest driver of global warming, but despite its potential, Google doesn’t appear to be net positive yet.
Google has every reason to downplay and obfuscate these numbers, which even in their reduced, highly efficient state can hardly be good. We’ll definitely be asking Google to get more specific before we find out if they get even worse in the 2025 report.
