The Power Struggle: The Complex Relationship Between Energy & AI

By Angela Calcagno, ACE NY Communications Fellow

It’s everywhere. In our search engines, in our favorite apps, on our phones, and in so many places we don’t even realize or see. Artificial Intelligence (AI) is certainly the buzzword of the era. 

We’ve all heard about the benefits and drawbacks of Artificial Intelligence—workplace automation, algorithm bias— but how will this affect our work in energy? 

It will certainly affect our day-to-day work (like it has everyone else’s), with more tools for writing emails, better spell checks, AI notetaking, document summaries and more. But how else could it affect our work, and does it mean we are obsolete? (Spoiler alert: no!) 

While AI’s role in energy remains largely uncharted, it holds immense promise for grid support. 

According to the National Renewable Energy Laboratory (NREL), next-generation AI provides “proactive, real-time” energy system solutions, making split-second decisions and predicting blackouts to strengthen grid reliability amid growing power demand. 

In New York state, researchers at the University of Buffalo have developed an AI-driven “self-healing grid” that can reroute power autonomously in milliseconds to prevent outages. Meanwhile, on the West Coast, a company called Grid Beyond is using AI to predict peak energy generation and balance the grid accordingly. 

AI is also being deployed for cybersecurity, reinforcing grid resilience in response to increasing cyber threats. The growing need for robust security measures has led to AI-driven systems that detect anomalies and respond to threats instantaneously—often without human intervention. 

This is all awesome! But these technologies, even just  creating an AI photo of a cat with a cowboy hat for example, requires immense electrical energy. Creating a single AI photo uses as much energy as charging a smartphone from 0 to 100%. Can the U.S. energy grid can keep up with its demands? We hope so; those at the top (thank you NYISO) are actively trying to plan for an AI-centric future, but that is a tough task. One often-overlooked aspect of AI is its massive energy consumption—not just for computation, but for data storage. With large-scale data centers popping up across the country, many state lawmakers are evaluating how their grids will handle the increased energy load and the financial burden on ratepayers. 

Yet AI adoption shows no signs of slowing. Data centers can bring economic investment to an area, which is why communities want them, but similar to other manufacturing facilities, they have needs, namely power. With millions of daily users worldwide, AI’s economic impact reached $200 billion in 2023 and is projected to surpass $1.8 trillion by 2030. 

With no way to halt or slow its expansion, the question remains—what’s next? 

The energy industry has a unique opportunity to rise to the challenge. As energy demand surges, so does the need for diversification and grid resilience. We know that wind, solar, and battery storage are an amazing trifecta that can be the backbone of the grid. Improving the technology to boost efficiency and think outside the box is going to be key. Fortunately, with advancements in renewable energy, transmission infrastructure, and battery storage, the sector is preparing for the future. It's a big puzzle, but if we can figure out what pieces we need, it could be beneficial to all. 

Not only is renewable energy essential to sustaining AI operations, but AI itself may prove instrumental in accelerating the clean energy transition—making it more efficient and effective than ever before.