Artificial intelligence (AI) is playing a growing role in optimizing energy systems, reducing emissions and advancing sustainability. At the same time, the technology’s rapid expansion is driving a significant increase in energy consumption, requiring faster, more co-ordinated planning across infrastructure, policy and industry.

At Ontario Tech University’s recent AI Forum, the Powering the future – Responsible AI for the Energy Transition panel brought together leaders from across the energy sector to examine a critical question: Can Canada’s energy systems keep pace with the rapid growth of AI?

Moderated by Chris Benedetti, Managing Partner and Chief Executive Officer at Sussex Strategy Group, the discussion explored how energy systems must evolve to support AI-driven demand while maintaining reliability, affordability and sustainability.

How are AI and energy systems evolving together, and what can we expect in the future?

AI is increasing efficiency and overall energy demand, requiring closer alignment between AI needs and energy infrastructure planning.

“We have traditionally trained people in one discipline: engineers on energy systems and data scientists on digital tools,” said Marlene Ramphal, Nuclear Engineer in Residence at Ontario Tech. “What we need is more cross‑disciplinary integration, so people can work across those systems.”

Kshitij Ahuja, Director of Digital Transformation at Nuclear Promise X, emphasized that since AI is here to stay, the key challenge is not the viability or adoption of the technology, but the planning required across energy systems, infrastructure and processes to support it.

“The most important thing we can do here is integrated planning between the rising demand from an energy perspective and how we grow our infrastructure to match that,” he said.

Ahuja also highlighted the importance of maintaining human oversight as systems evolve. “It’s the humans-in-the-lead concept: how do we keep continuing to grow ourselves too?”

What is driving energy demand, and what role will nuclear energy play?

The rapid expansion of data centres, with their significant and continuous electricity-supply requirements, is placing pressure on energy systems.

“It’s pretty consumptive-heavy in terms of the electricity supply,” said Lisa McBride, Country Leader for GE Vernova Hitachi’s Small Modular Reactor Canada business. “We have a lot of outreach from data companies trying to understand how they’re going to meet their energy needs.”

She said nuclear energy will play a key role in meeting that demand, as will other energy sources such as gas. “We all need to figure out very quickly how we’re going to deploy energy that’s scalable in the way that’s required.”

How prepared is Canada’s energy system to meet future demand?

Canada’s energy industry has strong foundations, but meeting future demand will require better co-ordination across technologies, infrastructure and sectors.

“Electricity is a system; it’s not a fuel,” said Susanna Zagar, President and Chief Executive Officer of the Canadian Gas Association.

She emphasized that energy planning must move beyond siloed approaches, and that each energy source plays a role and must be integrated into a co-ordinated energy system based on when and how it is most effective. “Use the right fuel for the right job at the right time,” she said.

She added that Canada is well-positioned because of its abundance of natural resources, but “the systems haven’t talked to each other very well for a very long time.” Progress will depend on how quickly systems can be aligned and scaled, she said.

As artificial intelligence adoption accelerates, can energy infrastructure scale quickly enough to meet demand?

While the pace of AI adoption presents challenges, it also creates opportunities to improve efficiency and accelerate processes.

Ramphal highlighted AI’s ability to improve reliability in existing energy assets, and how data‑driven approaches can help operators anticipate issues and optimize performance before failures occur.

The rapid growth in AI‑driven energy demand is “certainly a challenging opportunity,” added McBride. “The demand is growing faster than anybody actually predicted.”

Ahuja pointed to early examples of AI accelerating processes, including regulatory timelines. For example, Austin, Texas-based nuclear startup Aalo Atomics used AI to reduce the time required to secure permits by 92 per cent. He noted that while such examples are not universally applicable, they demonstrate how AI can support faster and more efficient processes when used appropriately.

What risks does AI introduce, and how can they be mitigated?

Panelists emphasized that while AI offers clear benefits, it must be implemented with strong governance and oversight.

“AI can be a stressor and it can be good for us,” said Ahuja. “It’s both, but it needs to be controlled, with some guardrails and governance around it.”

He noted that current applications are deliberately narrow, with clear checks and balances. “We’re not at the point where we can just give an AI agent full liberty,” he said. “We need verification, approvals and the right checks and balances.”

McBride highlighted reliability as a key concern, particularly in safety-critical sectors. “The reliability of the information is important when we think about the safety case for nuclear, as well as public engagement and knowledge, and how we work through different regulatory processes,” she said.

Zagar added that these risks can be managed through accountability, transparency and well-designed regulatory frameworks.