AI is no longer a side experiment. It is already part of products, workflows, and day-to-day operations. So the question is not whether companies should use AI, but how to use it responsibly at scale. From our perspective, it starts with efficiency: getting the same or better results with less compute, less energy, and a lower environmental footprint.
The way models are chosen affects energy use and emissions, and as expectations around transparency grow, it's important to have a more solid way to explain those choices. The good news is that reducing AI’s footprint does not mean slowing innovation. It means running better systems: smaller models, faster inference, and clearer measurement.
How Big Is the AI Sustainability Impact?
Before we go further, let’s start with a few facts about AI and sustainability.
3-40Wh: Amount of energy consumed for one small to long ChatGPT query (Source, 2025)
