Joshi is the author of a new report, released Monday with support from several environmental organizations, that attempts to quantify some of the most high-profile claims made about how AI will save the planet. The report looks at more than claims made by tech companies, energy associations, and others about how "AI will serve as a net climate benefit.” Joshi’s analysis finds that just a quarter of those claims were backed up by academic research, while more than a third did not publicly cite any evidence at all.

“People make assertions about the kind of societal impacts of AI and the effects on the energy system—those assertions often lack rigor,” says Jon Koomey, an energy and technology researcher who was not involved in Joshi’s report. “It's important not to take self-interested claims at face value. Some of those claims may be true, but you have to be very careful. I think there's a lot of people who make these statements without much support.”

Another important topic the report explores is what kind of AI, exactly, tech companies are talking about when they talk about AI saving the planet. Many types of AI are less energy-intensive than the generative, consumer-focused models that have dominated headlines in recent years, which require massive amounts of compute—and power—to train and operate. Machine learning has been a staple of many scientific disciplines for decades. But it’s large-scale generative AI—especially tools like ChatGPT, Claude, and Google Gemini—that are the public focus of much of tech companies’ infrastructure buildout. Joshi’s analysis found that nearly all of the claims he examined conflated more traditional, less energy-intensive forms of AI with the consumer-focused generative AI that is driving much of the buildout of data centers.