AI is quickly surpassing the energy use and climate impact of other applications for GPUs. Gaming used roughly 34 terawatt-hours (TWh) per year in the US and led to carbon dioxide emissions equivalent to about 5 million cars on the road (about 24 million tons of CO2), according to a comprehensive study published in 2019. Since then, newer consoles have become more energy-intensive, although their climate impact depends a lot on user behavior and how dirty the electricity grid is wherever they’re playing.
For a rough comparison, the energy use of GPU-accelerated AI servers in data centers grew from 2TWh in 2017 to more than 40TWh in 2023 in the US, according to a 2024 study by the Lawrence Berkeley National Laboratory. Now, with all the hype, AI servers’ annual power consumption could grow to between 165 and 326TWh by 2028, the study predicted. The lower estimate would be roughly equivalent to the energy more than 8.7 million homes in the US might use in a year.
In 2025, AI likely exceeded the power consumption of Bitcoin mining, accounting for nearly half of all the electricity data centers used around the world, according to a study by Alex de Vries-Gao, a PhD candidate at Vrije Universiteit Amsterdam Institute for Environmental Studies. The resulting carbon emissions likely reached between 32.6 million and 79.7 million tons annually, he estimates. For comparison, New York City’s climate pollution reaches around 50 million tons of CO2 annually.
One unseen consequence is even more e-waste, including larger and more complex components used in AI data centers. De Vries-Gao’s latest study, published in February, estimates that AI servers could create between 0.131 million and 0.225 million tons of e-waste each year by 2030. He says that’s comparable to all the e-waste produced by a country the size of Denmark, Norway, or Austria. It’s also a much more conservative estimate compared to a 2024 study by other researchers, which predicted that e-waste from AI could reach between 1.2 million and 5 million tons by the end of the decade.
De Vries-Gao estimates a smaller amount of waste after factoring in supply chain constrictions, and because he sees the lifespan of a server growing beyond the three years that other researchers have used as a benchmark. But the amount of e-waste he projects will build up as a result of AI is still a lot, he tells me. “The total impact is significant,” he says. “Whether you’re talking about crypto miners or whether you’re talking about the big tech companies, they don’t take responsibility.”
