Energy-hungry AI models could strain water and power grids. Can the sector handle the demand?

It’s bedtime, and your kid wants a story. You, however, recoil at the thought of reading a book you’ve been through 100 times. So you turn to a chatbot powered by artificial intelligence and type a prompt into your phone: “Write a children’s story about a friendly giraffe.”

and OpenAI, while Meta Platforms Inc. increased its capital-spending estimates this year to US$40-billion to support AI. Canada has more modest ambitions. The federal government announced a $2.4-billion package in March, most of which will go to help companies and researchers access AI computing services and build infrastructure.

Along with two colleagues, Ms. Luccioni published a study last November that found that generating text with an LLM required 0.047 kilowatt hours of electricity for every 1,000 inferences, which is about the same as fully charging a smartphone nearly four times. Image generation, on average, used 60 times more energy. One model used nearly as much juice to fully charge a smartphone every single time it produced a picture.

By 2027, AI computing could be responsible for up to 6.6-billion cubic metres of water withdrawal – equivalent to six Denmarks, according to a study conducted by Prof. Ren and his colleagues. Withdrawal generally assumes at least some portion of the water is returned to the original source, whereas consumption measures the portion that is lost to a local environment such as through evaporation.

Phil Harris, the chief executive of Ottawa-based Cerio, sees it this way: “We’re still living in a pre-Copernican age of understanding of data centres.” The places are put together all wrong for the era of AI, in his view. GPUs draw power even when not in use, and are crammed together into a rack as tightly as possible, which generates intense concentrations of heat.

Mr. Gadepally, who is also the chief technology officer at Toronto-based cloud services provider Radium, said the company is implementing approaches such as capping power, which saves customers money and reduces energy and cooling needs. Radium is a lot smaller than the cloud computing giants, but has a growing list of customers. “We are absolutely getting customers that are making business decisions off of the sustainability story,” he said.

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