Much has been made of the emergence of generative AI and its strain on the electrical grid due to the energy demand. So just wait until you see how much energy agentic AI consumes. A new research paper from the Korea Advanced Institute of Science and Technology set out to quantify the “hidden costs” of AI agents, and found they can consume up to 136.5 times more energy per query than generative AI models. There’s a logic to the fact that AI agents require more processing power and energy than your standard generative AI query. Typically, LLM requests are a call-and-response: a person enters a query, and the model responds. But agentic AI typically requires multiple steps to execute a command. To do that, the researchers said, the agent must continuously ping its model to generate a new response as it reasons through all of the steps of its given task. As a result, there’s a multiplier effect that takes place. According to the researchers, an AI agent running on a large language model of the scale of most commercially available AI models would consume an average of 348.41 watt-hours per query—about the equivalent of keeping an LED light bulb on for a full day. That figure, they say, is about 136.5 times higher than the energy consumed by a generative AI query.