AI Could Reshape Everything We Know About Climate Change

With one announcement, Chinese AI startup DeepSeek shook up all of Wall Street and Silicon Valley’s conventional wisdom about the future of AI. It should also shake up the climate and energy world. 

For the last year, analysts have warned that the data centers needed for AI would drive up power demand and, by extension, emissions as utilities build out natural gas infrastructure to help meet demand.

The DeepSeek announcement suggests that those assumptions may be wildly off. If the company’s claims are to be believed, AI may ultimately use less power and generate fewer emissions than anticipated.

Still, don’t jump for joy just yet. To my mind, the biggest lesson for the climate world from DeepSeek isn’t that AI emissions may be less than anticipated. Instead, DeepSeek shows how little we truly know about what AI means for the future of global emissions. AI will shape the world’s decarbonization trajectory across sectors and geographies, disrupting the very basics of how we understand the future of climate change; the question now is whether we can harness that disruption for the better.

“We're just scratching the surface,” says Jason Bordoff, who runs the Center on Global Energy Policy at Columbia University about the implications of AI for emissions. “We're just at inning one of what AI is going to do, but I do have a lot of optimism.”

---

Many in the climate world woke up to AI early last year. Over the course of a few months, power sector experts issued warnings that the U.S. isn’t prepared for the influx of electricity demand from AI as big technology companies raced to deploy data centers to scale their ambitions. A number of studies have found that data centers could account for nearly 10% of electricity demand in the U.S. by 2030, up from 4% in 2023.

Many big tech companies have worked to scale clean electricity alongside their data centers—financing the build out of renewable energy and paying to open up dormant nuclear plants, among other things. But utilities have also turned to natural gas to help meet demand. Research released earlier this month by Rystad Energy, an energy research firm, shows that electric utilities in the U.S. have 17.5 GW of new natural gas capacity planned, equivalent to more than eight Hoover Dams, driven in large part by new data centers. 

All of this means an uptick in emissions and deep concern among climate advocates who worry that the buildout of electricity generation for AI is about to lock the U.S. into a high-carbon future.

As concerning as this might be, the projections for short-term electricity demand growth might mask much more challenging risks that AI poses for efforts to tackle climate change. As AI drives new breakthroughs, it will change consumption patterns and economic behavior with the potential to increase emissions. Think of a retailer that uses AI to better tailor recommendations to a consumer, driving purchases (and emissions). Or consider an AI-powered autonomous vehicle that an owner leaves to roam the streets rather than paying for parking.  

At the most basic level, AI is bound to generate rapid productivity gains and rapid economic growth. That’s a good thing. But it’s also worth remembering that since the Industrial Revolution, rapid economic growth has driven a rise in emissions. More recently, some developed economies have seen a decoupling of growth from emissions, but that has required active effort from policymakers. To avoid an AI-driven surge in emissions may require an active effort this time, too. 

But AI isn’t all risk. Indeed, it’s very easy to imagine the upsides of AI far outweighing the downsides. Most obviously, as DeepSeek shows, there may be ways to reduce the emissions of AI with chip innovation and language model advances. As the technology improves, efficiencies will inevitably emerge.

The data center buildout could also catalyze a much wider deployment of low-carbon energy. Many of the technology companies that are investing in AI have committed to eliminating their carbon footprints. Not only do they put clean electricity on the grid when they build a solar farm or restart a nuclear power plant, but they help pave the way for others.

“Governments are starting to realize that if they're going to attract data centers, AI factories, and wider technology companies into their countries, they have to start removing the barriers to renewable energy,” says Mike Hayes, head of climate and decarbonization at KPMG.

And then there are all the ways that AI might actually cut emissions. Researchers and experts group the potential benefits into two categories: incremental improvements and game changers. 

The incremental improvements could be manifold. Think of AI’s ability to better identify sites to locate renewable energy projects, thereby greatly increasing the productivity of renewable energy generation. AI can help track down methane leaks in gas infrastructure. And farmers can use AI to improve crop models, optimizing crop yield and minimizing pollutants. The list goes on and on. With a little consideration, you could probably identify a way to reduce emissions in every sector.  

It remains difficult to quantify how these incremental improvements all add up, but it’s not hard to imagine that emissions reductions thanks to these developments could easily outweigh even the most dramatic estimates of additional pollution. 

And then there are the game changers that could, in one blow, completely transform our ability to decarbonize. At the top of that list is nuclear fusion, a process that could generate abundant clean energy by combining atomic nuclei at extremely high temperatures. Already, start-ups are using AI to help optimize their fusion reactor designs and experiments. A fusion breakthrough, supported by AI technologies, could provide a clean alternative to fossil fuels. It could also power large-scale carbon dioxide removal. This would give the world an opportunity to suck carbon out of the atmosphere affordably and pull the planet back from extreme temperature rise that may otherwise already be baked in. 

“If you think like a venture capital investor, you're betting 1 or 2% of incremental emissions, but what could the payoff potentially be?” asks Cully Cavness, co-founder of Crusoe, an AI infrastructure company. “It could be things like fusion, which could address all the emissions.”

For those of us, myself included, who haven’t spent the last decade thinking deeply about AI, watching it emerge at the center of the global economic development story can feel like watching a juggernaut. It came quickly, and it’s hard to predict exactly where it will go next. 

Even still, it seems all but certain that AI will play a significant role shaping our climate future, far beyond the short-term impact on the power sector. Exactly what that looks like is anyone’s guess.