AI Can Accelerate The Clean Energy Transition (If We Train It To)

Artificial intelligence will either add to the burden on an already-strained electrical grid or it can help pave the way to a secure energy future, says ACEEE.

By Nora Wang Esram
Courtesy of ACEEE

It is encouraging to see American homes, vehicles, and new industrial facilities moving away from fossil fuels in favor of clean electricity. A less welcome trend is the rapid growth in electricity demand that the power grid is unprepared for. The proliferation of data centers to meet the growing demand for artificial intelligence (AI) is exacerbating this problem.

Our daily digital lives depend on energy-intensive computing power. When we work in the cloud, shop online, stream TV, use social media, or call a ride, we use electricity. AI models are among the most energy-hungry digital processes we’ve seen in decades. AI offers enormous potential to advance knowledge and convenience and accelerate the digitalization of modern cities, buildings, transportation, farms, and factories. It can also help keep our electricity supply affordable and reliable even as demand surges.

AI clean energy
(Image: Adobe Stock / Generated with AI by Visual Venture)


Companies like Google and Microsoft/Open AI are leveraging their procurement power to accelerate advanced clean electricity technologies. Similar efforts have primarily focused on supply-side solutions, such as wind and solar in the immediate future, and eventually advanced nuclear, enhanced geothermal, hydrogen, and long-term storage. These are worthy initiatives, but building more generation and transmission capacity alone cannot resolve the new energy crisis we are facing, at least not within the limited time left for us to combat climate change. All these innovative technologies won’t be widely adopted for decades. In the meantime, our grid will continue to strain under the power demands of AI, electric vehicles, and other electric equipment and devices in a more connected world.

The Solution: Optimize Demand And Never Waste An Electron

Data centers use massive amounts of energy to train and sustain the large language models that enable AI. Energy use by these data centers is already skyrocketing, compounding the strain on an electrical grid ill-equipped to handle our ever-growing electricity demands.

Nevertheless, AI may be our best hope of solving these problems. How? By optimizing both the timing of energy use and the type of energy used. When renewable sources like solar are at their peak, we should do our most energy-intensive work and optimize energy storage. Otherwise, that extra clean energy is curtailed to maintain the power supply and demand balance. For example, in 2023, 2.6 million megawatt hours of utility-scale wind and solar output were curtailed in California — clean energy that could have powered nearly 380,000 California households for that same year…

AI clean energy, Nora Wang EsramNora Wang Esram, Senior Director for Research, oversees ACEEE’s research programs including Buildings, Industry, Transportation, Behavior, and Health and Environment. She leads and manages ACEEE’s research activities. She joined ACEEE in 2020.


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