Canada’s 30-day AI consultation is halfway done. Here’s why CIOs, Chief AI Officers, and tech leaders should speak up before October 31.
Canada’s national AI sprint, a 30-day consultation to shape the country’s next Artificial Intelligence and Data Act (AIDA) and National AI Strategy — is now entering its final two weeks. Led by Minister of Artificial Intelligence Evan Solomon, the sprint invites experts, builders, and business leaders to share how Canada should govern AI while staying globally competitive.
The public can submit input until October 31, 2025, through the federal Consulting Canadians portal. But this is not just another government survey. The questions reveal what Canada is trying to solve: how to balance sovereignty with scale, innovation with trust, and growth with ethics.
1. Research Edge: Can Canada Still Lead the World?
The first set of questions probes how Canada can retain its research advantage — and whether to double down on fundamental breakthroughs or applied innovation.
These aren’t academic musings; they go to the heart of competitiveness. The government is essentially asking: Where should Canada lead, and where should it partner or defer?
For tech leaders, this points to a policy shift toward strategic specialization — identifying sectors like health, life sciences, or defence where public funding and AI adoption can align.
2. Talent & Adoption: Who Builds, Who Benefits
Several questions focus on attracting and retaining AI talent across research, industry, and the public sector. The subtext: Canada’s brain drain is real.
Other questions ask where AI adoption could have the greatest impact — from health care to agriculture — and what barriers are holding it back. That’s a clear signal that Ottawa wants to connect AI policy with workforce readiness and sector-specific use cases.
For CIOs, this is an opening to influence how skills, certification, and incentives get structured across the AI workforce pipeline.
3. Commercialization & Competitiveness: Scaling Without Selling Out
Another group of questions deals with how Canada can grow globally competitive AI firms while protecting intellectual property and economic sovereignty.
The government is explicitly asking how to connect academic research to commercialization — and what needs to change in Canada’s investment climate to help startups scale.
For industry leaders, this signals that AI policy will soon touch M&A, data governance, and IP retention — areas where enterprise alignment will matter as much as innovation itself.
4. Trust & Governance: The Core of the AI Act
A major theme in the sprint is how to build public trust in AI technologies. Questions about standards, assurance, and ethical compliance show the government is preparing for risk-based regulation — similar to the EU’s AI Act, but likely more collaborative.
For enterprises, this means upcoming expectations around algorithmic transparency, bias mitigation, and explainability. The message is clear: trust will be measurable.
5. Security & Infrastructure: The Sovereignty Question
The final cluster of questions deals with AI sovereignty — from computing infrastructure and data security to national resilience.
How much sovereign compute capacity should Canada build? How do we secure AI models and critical data assets from foreign risks? These questions suggest Ottawa is linking AI regulation to national security strategy, not just innovation policy.
Tech executives working with hyperscalers or managing sensitive data should expect policy attention to shift toward cloud independence, cybersecurity, and resilience in 2026 and beyond.
What happens next
These are not just questions but the same challenges CIOs, Chief Data Officers, and Chief AI Officers manage daily — model governance, explainability, regulatory compliance, and scaling AI without breaching privacy or bias thresholds.
For many organizations, Canada’s upcoming AI Act will become the blueprint for internal AI governance. This sprint offers a rare opportunity for enterprise leaders to ensure that the blueprint reflects operational reality — not just academic theory.
After the sprint closes on October 31, the Task Force will compile findings and deliver a set of policy recommendations in November. These will directly influence how AIDA is finalized, what compliance obligations companies face, and how innovation incentives are structured for Canadian AI firms.
For tech executives, this is more than consultation, it’s strategy. Input shared now will shape how AI is deployed, audited, and trusted across industries for years to come.
The window to influence is narrow but powerful.
Because once the rules are written, the question won’t be what should Canada do about AI, but how ready are its leaders to operate within it?
