Signal 01 · · CCN Intelligence
Canada’s new AI council needs to turn adoption into business capability
Canada has named its AI advisers. The next test is whether their advice helps businesses apply AI effectively, improves public services and equips Canadians to participate. CCN proposes AI Business Fluency: combining technical understanding with practical business skills to turn adoption into measurable value.
What happened
Prime Minister Mark Carney launched the National Council on Artificial Intelligence on October 2. Its remit includes adoption, government transformation, research, talent and sovereign infrastructure. Supported by the Privy Council Office, it will advise on the government’s AI for All strategy. Ministers and departments remain accountable for policy decisions and implementation. The council’s direct role is to advise Ottawa, but the intended benefits extend to businesses, Canadians and government. Its influence will depend on whether recommendations become accessible programs, better procurement decisions and practical improvements. The council has a substantive advisory mandate. Its effectiveness cannot fairly be judged days after its creation. However, the launch announcement does not publish a meeting schedule, deadlines for recommendations, reporting requirements or a performance scorecard for the council. It also does not explain how Canadians will track government responses to its advice. These are gaps in the announcement, rather than proof that such arrangements do not exist.
Why it matters for Canada
The strategy targets 60% business adoption of AI by 2034. That is a target for businesses, rather than the percentage of Canadians using AI or government services deploying it. Other ambitions include up to 250,000 new jobs by 2031 and nearly $200 billion in potential GDP gains. These are national strategy objectives, rather than published performance commitments for individual council members. The government has announced financing through BDC’s LIFT program, $500 million through the Regional AI Initiative and an additional $700 million for the Compute Access Fund. It has also announced a national AI literacy initiative. These commitments establish a direction; their effectiveness will depend on accessibility, implementation and results. For a smaller business, the challenge begins with understanding which problem AI can solve and whether the benefit justifies the investment. Owners need financing, time, reliable advice and employees capable of applying the technology. They also need to understand integration costs, data requirements, cybersecurity, privacy and the limitations of outputs. CCN’s view is that investment and education should be designed together. Funding a system without developing the ability to use it can leave a business with an expensive experiment. Training without an affordable implementation path can leave employees with knowledge they cannot apply. The strategy recognizes a gap between experimenting with AI and integrating it into business operations. Its 60% target needs a transparent measurement method that allows Canadians to distinguish initial use from sustained, productive deployment. Statistics Canada measures businesses reporting AI use to produce goods or deliver services during the preceding 12 months. That figure reached 19.2% in the second quarter of 2026, compared with 12.2% in 2025. The council announcement still cites a starting point of just over 12%. Public reporting should identify the baseline year and explain how the target relates to the latest comparable evidence. In the third quarter of 2026, 25.2% of businesses reported plans to use AI over the following 12 months. Intentions, actual use and verified benefits are different measures. An adoption percentage can show how widely technology is spreading, but it cannot establish whether businesses are becoming more productive or managing the technology responsibly.
What CCN sees
Canada’s AI challenge is increasingly about the capability to apply technology well. Small and medium sized businesses need investment and practical education that develop technical understanding and business judgment together. AI Business Fluency gives that ambition a clearer purpose. It asks whether people can make informed choices, apply AI responsibly and demonstrate value in the work they do. The council can help by pressing for accessible programs, consistent definitions and measurable outcomes. Its credibility will grow when Canadians can trace expert advice through a government decision to a practical improvement. Canada should measure AI adoption by both its reach and the value it creates. The council should show how its advice helps deliver that value.
What leaders should consider
CCN proposes AI Business Fluency: the ability to understand AI’s capabilities, limitations and risks, connect them to a business problem, and measure whether the application creates value. This brings two capabilities together. Technical understanding helps people assess data requirements, reliability, security and appropriate human oversight. Practical business understanding helps them choose useful applications, redesign workflows, evaluate costs and measure outcomes. The depth required will vary by role, but leaders and employees need enough shared understanding to make sound decisions together. Education should build these capabilities through real business situations. A manufacturer might assess whether AI reduces production waste. A professional services firm might test whether it shortens document preparation while maintaining accuracy. A smaller employer might evaluate whether it improves customer response times without exposing confidential information. Each exercise should begin with a baseline, a defined objective and a responsible owner. Participants should learn how to test an application, challenge its outputs, account for implementation costs and decide whether to continue, change or stop. Course completion is useful evidence of participation. Stronger evidence shows what participants became capable of doing, whether they applied their learning and whether the business sustained a measurable improvement.
What to watch next
CCN proposes a public scorecard with annual adoption milestones and results by business size, sector and region. Support programs should report funding received, implementation progress and sustained use, alongside evidence of productivity, service quality and responsible governance. Education programs should also report practical capability: can participants identify suitable applications, assess risks, implement solutions and measure results? This would make AI Business Fluency a useful standard for program design and evaluation. The need for practical relevance is substantial. Statistics Canada reports that 40% of businesses considered AI irrelevant to their operations in the second quarter of 2026. Reported use was also lower among rural businesses, at 9.9%, than urban businesses, at 21%. A national average can conceal where support needs to improve. The council should publish its priorities, reporting timetable, appropriate conflict disclosures and recommendations, subject to legitimate confidentiality needs. Government should explain which recommendations it accepts, who will implement them, when results will be reviewed and what corrective action follows when progress falls short. These are CCN’s proposed accountability standards. Accountability should follow responsibility. The council should demonstrate the quality, timeliness and influence of its recommendations. Ministers and departments should demonstrate delivery and outcomes. National adoption gains should not automatically be credited to the council without evidence of its contribution.