Data Centres: Catalyst or Challenge for Canada’s Energy Sector?

With AI data centres emerging as one of Canada’s fastest-growing sources of electricity demand, last week’s webinar tackled a critical question: Can Canada accommodate rapid AI data centre growth while ensuring affordable electricity, maintaining public trust, and meeting broader electrification and climate goals? What are the inevitable trade-offs?

As utilities face new requests from hyper-scalers and tech giants like AWS and Microsoft, they must weigh these against long-standing electrification goals. « The energy transition, electrification—those are going to put major demands on our electricity systems, » noted OPG’s Elissa Downey, Senior Manager of Strategic Initiatives. « How does new, unprecedented growth [from additional data centre demand] compare to that? Are there trade-offs? What does that look like when you think about siting a data centre in the province—how does that compare to your traditional large manufacturing facility that might create a lot more jobs, and how might the province think about that? »

Forecasting future demand was a recurring theme. While Ontario relies on these « high-certainty » loads for its official projections, the discussion revealed that grid planning must evolve quickly—especially as developers seek fast-track connections that don’t always align with infrastructure build timelines.

Panellists also examined how AI itself could help modernize the grid. Taylor Briggs, Public Policy Principal at Amazon Web Services pointed to a shifting paradigm: « Much of the grid… was built out in the ’60s and ’70s. What can we do to modernize that, and where can we use AI technology to help modernize that? … Five years ago, we were not having these conversations, and today they’re very much at the forefront. »

The discussion wasn’t without caution. Mél Hogan, Associate Professor of Film & Media at Queen’s University, challenged the broader narrative of AI inevitability « I don’t think we should be investing in cloud companies’ conception of AI where it is scraping the contents of the Internet as mass plagiarism… It’s about defining AI. It’s about educating people around the hype and the marketing, versus some applications that are very specific and scientific and trained on in-house large language models, not scraping the Internet. »

As Canada moves to scale up an affordable, reliable electricity grid, panelists emphasized the need for clear frameworks, cross-sector collaboration, and greater public debate. The promise of AI is real—but so are the risks, and planning for both requires transparency, nuance, and long-term thinking.