On the eve of the federal budget, Gowling WLG brought together senior leaders from government, industry, and academia for a candid discussion on how Canada can balance innovation, regulation, and competitiveness in this age of artificial intelligence.

The conversation examined Canada's AI strengths and shortfalls—from research leadership and responsible governance to the realities of global competition—and what it will take to turn the opportunities at hand into sustained progress.

Canada's AI long game

"For Canada, AI has been and will continue to be a long game," said Mark Schaan, Associate Deputy Minister at ISED, noting that the country's been investing in AI for more than four decades. Canada's approach, he explained, is built on this foundation of fundamental research, supported by a strategic focus on commercialization and digital infrastructure.

But Schaan cautioned that with other jurisdictions moving quickly, Canada can't rely on its early leadership alone. To stay competitive, he said, the country must keep refining its national strategy and accelerating the shift from research to real-world adoption. That evolution is mirrored in how AI governance is changing globally, from the early focus on ethics, to the new era of technical and safety-driven regulation as commercialization moves to the forefront.

Comparing the European Union's AI Act, the UK's proposed risk-based model, and the U.S.'s more hands-off approach, Schaan noted that Canada's strength lies in its ability to bridge these different perspectives.

What AI sovereignty means in Canada

As Canadian businesses adopt new AI tools—or learn how to use new AI features included in existing, often foreign-based, tools—the big question lies in what "AI sovereignty" truly means.

Schaan described Canada's efforts to build greater "sovereign compute" capacity through targeted investments in funding, hardware, and data infrastructure that support both innovation and security. "We want companies to own their AI outcomes," he said, explaining that true sovereignty is about having enough strategic autonomy to manage risk without cutting off collaboration.

Canada, he noted, doesn't yet have the full "sovereign stack"—for example, it lacks domestic chip manufacturing—but is investing pragmatically in the areas where it can lead. Building that independence, he added, means focusing on the parts of the ecosystem where Canada brings real strength such as research and digital infrastructure.

Céline Bey, Gowling WLG's Co-Managing Partner (France), added that Europe faces similar challenges, with policymakers investing heavily in startups, research institutions, and AI education and skills training to reduce future dependence on foreign platforms. It's an approach she said could help guide Canada's next phase of AI development.

Boards that ask better questions will lead the AI era

While national policy will shape the pace of adoption, the real test of Canada's AI leadership will play out within individual organizations. Turning ambition into strategy now depends on how boards and executives govern, resource, and question their own use of the technology.

Parna Sabet-Stephenson, leader of Gowling WLG's FSxT Group, emphasized that the conversation must move from risk to readiness. "You need a governance framework that includes AI," she said, pointing to emerging best practices such as AI risk assessments, cross-functional tech committees, and the rise of Chief AI Officers in regulated industries. "But the role of a board member is more than oversight; it's also foresight."

Cameron Schuler, Chief Commercialization Officer & VP of Industry Innovation at the Vector Institute, agreed that literacy at the leadership level will determine which organizations thrive. "You need people who can ask the right questions about AI," he said, underscoring that effective oversight depends as much on curiosity as it does on technical fluency.

Anticipating change and building a foundation for sustainable growth

That mindset—curious, sensible, and accountable—will set the tone for how AI ends up reshaping customer and client experiences in the years ahead.

Gregory Clark, Director of AI and Advanced Analytics at BMO, observed that this transformation is already underway. From entertainment to banking to health care, consumer habits are shifting as people expect more intuitive and personalized digital experiences. He illustrated the point with an anecdote about digital comics: only after sales dropped did most publishers change their layouts from left-to-right to top-to-bottom to better fit phone screens. The move showed how quickly audiences disengage from products that fail to evolve with technology.

Despite this pressure to innovate, the panelists emphasized that success in the AI era requires as much level-headedness as imagination. Clark explained that BMO's approach to AI governance, for instance, focuses on matching the right tools to the right problems. Not every issue, he noted, needs an AI solution. Often, traditional machine learning or statistical models are the better fit.

Schaan stressed that the same practical sensibility must apply at the policy level, as well. "You can't sic AI on bad data or bad processes," he said, underscoring the importance of strengthening data quality, governance, and infrastructure to support sustainable growth.

The path forward

Across the discussion, one guiding principle resonated: Canada's ability to balance ambition with pragmatism—at organizational, industry, and policy levels—is essential in determining whether AI becomes a lasting engine of progress across the country. With deep research roots, trusted institutions, and a balanced regulatory mindset, Canada has the tools to lead, provided it doesn't let caution eclipse ambition.

Schuler put it simply: "The real risk is missing the opportunity."