Canada Launches “AI for All”: A New National AI Strategy

On June 4, 2026, the federal government released its long-awaited national AI strategy, AI for All (the “Strategy”), setting out a plan to accelerate adoption, strengthen domestic capability, and position Canada as a leader in the global AI economy.

Following national consultations involving over 11,000 participants from industry, academia, and civil society, the Strategy represents a shift in focus from research leadership to broader commercialization and deployment of AI technologies. The announcement was led by Evan Solomon, Canada’s Minister of Artificial Intelligence and Digital Innovation.

The Strategy is built around three core themes: trust, opportunity, and sovereignty, reinforcing the government’s aim to ensure responsible AI adoption, deliver economic value, and align with Canadian interests.

The Strategy is organized around six “pillars”:

  • Protecting Canadians and safeguarding democracy;
  • Empowering Canadians;
  • Powering shared prosperity through adoption;
  • Building a sovereign AI foundation;
  • Scaling Canadian champions; and
  • Building trusted partnerships and global alliances.

These pillars position AI as a central component of Canada’s economic, industrial and regulatory policy framework.

Key Strategic Priorities

The Strategy brings together industrial policy, workforce development, infrastructure investment, and regulatory modernization. It targets both the supply side of AI (talent, infrastructure, and research capacity) and the demand side (adoption, commercialization, and procurement), aiming to foster a robust and competitive AI ecosystem in Canada.

Key initiatives include:

  • Driving adoption at scale: The strategy targets increasing business use of AI from current levels to approximately 60% by 2034, alongside broader economic targets of up to 250,000 new jobs and significant GDP growth.
  • Workforce development and AI literacy: National training and workplace initiatives are intended to expand access to AI skills and support labour market transitions.
  • Sovereign infrastructure investment: The Strategy emphasizes building domestic AI compute capacity, including a national supercomputing capability, to reduce reliance on foreign-controlled infrastructure.
  • Commercialization and scale-up: Targeted funding, procurement strategies, and access to capital are designed to support the growth and retention of Canadian AI companies.
  • Regulatory modernization: The federal government has signalled proposed reforms to privacy and online safety frameworks, alongside measures addressing emerging risks such as deepfakes and synthetic media.

The Strategy also reflects a “build-partner-buy” approach, prioritizing domestic capability while relying on external partnerships and market solutions where appropriate. Notably, it positions the public sector as both regulator and early adopter, with government procurement intended to drive the uptake of Canadian AI solutions in certain sectors, including health and life sciences, energy and natural resources, transportation, agriculture, and manufacturing and robotics.

Addressing Canada’s AI Adoption Gap

A central premise of the Strategy is that Canada continues to face an AI “adoption gap”. In practical terms, despite strong research institutions and globally recognized talent, Canadian businesses have been slower to integrate AI into day‑to‑day operations.

The Strategy responds by focusing on the following areas:

  • Increasing adoption among Canadian businesses, particularly small and medium-sized enterprises;
  • Reducing barriers to deployment, including access to capital, infrastructure, and technical expertise; and
  • Strengthening workforce readiness through training and AI literacy initiatives.

The goal is to convert Canada’s technical strengths into tangible economic outcomes, including increased productivity, commercialization, and sustained business growth.

Governance Approach and Key Gaps

On the legal and regulatory side, the Strategy adopts a distributed governance model. In other words, rather than introducing a comprehensive AI-specific statute, it relies on targeted reforms and existing legal frameworks, including privacy, consumer protection, human rights, and sector-specific regulation.

While the Strategy signals future legislative development, it offers little detail on timing or enforcement. As a result, certain key elements of Canada’s AI governance framework remain to be developed.

Perhaps most notably, the Strategy is largely silent on copyright law. This leaves unresolved issues that are increasingly significant for intellectual property stakeholders, including the use of copyright-protected works in training AI systems, and the ownership and protection of AI-generated outputs.

This silence creates legal uncertainty and risk for developers, rights holders, and organizations deploying AI technologies. Proactive legal advice and monitoring will be critical as the regulatory environment evolves, as this is likely to be one of the most closely watched areas for businesses deploying generative AI.

Canada in the Global Landscape

Canada’s Strategy exists in the context of two dominant global approaches to AI governance.

The European Union has adopted a comprehensive legislative framework that emphasizes risk regulation, accountability, and the protection of fundamental rights. In contrast, the United States has taken a more decentralized and market-driven approach, relying on commercial leadership and sector-specific regulation.

Canada is effectively taking a hybrid approach that combines elements of both models. It emphasizes trust, safety, and governance while also prioritizing growth, commercialization, and technological competitiveness. While this approach offers flexibility, it also leaves open questions regarding how Canada will apply its regulatory framework in practice, particularly as international standards continue to evolve.

Looking Forward

The AI for All Strategy marks a significant evolution in Canada’s approach to AI, emphasizing large-scale deployment, economic impact, and strategic autonomy.

Much will turn on how quickly these commitments translate into concrete action. This will depend in particular on regulatory reforms in privacy, safety, and AI governance, investment in infrastructure (including sovereign compute capacity), business adoption among small and medium-sized enterprises, and alignment with international frameworks to support compatibility and long-term competition.

Ultimately, the Strategy emphasizes the growing role of AI as a core element of national economic and industrial policy. Whether Canada can fully realize these benefits will depend on the pace and clarity of implementation, particularly where the Strategy currently remains high-level or silent.

 

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