The federal government has charted a new course for artificial intelligence in Canada, releasing its 'AI for All' strategy and signalling a significant shift in national policy. The new plan abandons the previous government's attempt to create a single, all-encompassing law, instead opting for a distributed governance model that prioritizes accelerated adoption, sovereign infrastructure, and the use of existing legal frameworks.
This new direction moves away from the proposed Artificial Intelligence and Data Act (AIDA), which stalled in Parliament and was ultimately set aside. Rather than designing a new centralized statute, Ottawa will now focus on targeted legal reforms and public investment, while relying on current privacy, human rights, and consumer protection laws to manage the risks associated with AI.
For Canadian businesses, the message is clear: AI governance is not on hold. The existing legal obligations are in effect today, and the 'AI for All' strategy provides a roadmap for how these regulations will evolve. The plan outlines economic and industrial priorities that will shape how regulators, funders, and government bodies engage with artificial intelligence for the next several years.
Adoption as a national priority
A central pillar of the new strategy is the aggressive promotion of AI adoption across the Canadian economy. The government has set ambitious, though not legally binding, targets, including generating $200 billion in additional economic growth, creating 250,000 new jobs in the AI sector over five years, and increasing AI adoption among businesses from about 12 per cent to 60 per cent by 2034.
These figures signal that making Canada an AI leader is a core policy objective. Funding decisions, procurement criteria, and the government's overall regulatory stance are expected to align with this goal. The strategy also casts the government as an active adopter of AI, not just a regulator. Public-sector use of AI will be used to establish standards for trustworthy and compliant systems, meaning companies seeking government contracts will likely face stringent governance requirements before any formal legislation is passed.
Focus on priority sectors and sovereign infrastructure
The strategy identifies several priority sectors for accelerated AI deployment: health and life sciences, energy and natural resources, transportation, agriculture, and manufacturing. Businesses in these areas can expect AI rollouts to occur through structured federal initiatives, targeted funding, and public-private partnerships. As part of this push, the government is fast-tracking critical infrastructure projects to support industrial growth.
However, federal support will come with conditions. Organizations participating in government-backed programs will have to adhere to specific rules around data governance, interoperability, and accountability. The health sector's VITAL initiative, which uses a federated data model with built-in governance requirements, offers an early glimpse of this model.
Another critical component of 'AI for All' is its focus on sovereign infrastructure. Building on the Canadian Sovereign AI Compute Strategy, the government is investing heavily in domestic supercomputing capacity and data centres. This signals an expectation for Canadian organizations to prioritize where their AI models are built, trained, and hosted. For businesses, this transforms decisions about cloud providers and data residency from purely technical matters into strategic and potentially regulatory ones, particularly for those in regulated sectors or involved in public procurement.
A diverging global landscape
Canada's strategy arrives as major global powers are pursuing fundamentally different approaches to AI governance. The European Union's AI Act, a comprehensive, risk-based framework, has an extraterritorial reach that can apply to Canadian companies if their AI systems affect individuals in the EU. For many businesses, complying with the EU's stringent rules is already a present-day legal obligation.
In sharp contrast, the United States is embracing a deregulatory, 'innovation-first' posture. An executive order signed on June 2, 2026, established a framework for the secure deployment of advanced AI, but relies on a voluntary process for developers to give the government early access to models before a public release. This approach, which followed significant industry lobbying, creates a more permissive environment south of the border. This global fragmentation places Canadian businesses in a complex position. They face a highly regulated environment when dealing with the EU, a much looser one with the U.S., and a distributed, evolving framework at home. This asymmetry presents both competitive pressures and compliance challenges for companies operating internationally. The University of Calgary research tackles diverse global challenges, and Canada's approach, more interventionist than the U.S. but less prescriptive than the EU, could become a competitive advantage if implemented coherently. However, it also risks creating a compliance gap, being neither regulated enough for clarity nor deregulated enough for speed.
How businesses should prepare
The absence of a single AI statute does not signal a pause in legal risk. On the contrary, the government has signalled that enforcement through existing channels will increase. Businesses deploying AI are already subject to enforceable rules under privacy law, human rights codes, and consumer protection acts.
The Office of the Privacy Commissioner of Canada has identified AI as a priority enforcement area, and the 'AI for All' strategy's commitment to modernizing privacy law suggests these obligations will only become stricter. Likewise, AI systems used for hiring, lending, or insurance that produce discriminatory outcomes are already vulnerable to challenges under human rights legislation, while AI-driven pricing is attracting scrutiny from consumer protection agencies.
The most immediate legal force of the new strategy will likely be felt through government procurement and funding conditions. As the federal government becomes an active AI adopter, its contracts and partnership agreements will increasingly include specific requirements for transparency, data governance, and auditability. A proposed 'Canada Trusted AI Certification' program could soon become a de facto requirement for businesses looking to work with the government or in priority sectors.
Businesses are advised to begin auditing their current AI systems against existing privacy, human rights, and consumer protection frameworks now. The strategy's emphasis on modernizing privacy law suggests that future legislation will feature stronger individual rights, expanded transparency expectations, and significantly increased penalties, aligning more closely with international standards. Organizations that invest now in data governance, transparency, and explainability will be better positioned for the regulatory environment of tomorrow.
