The Upside in the Data
A joint McKinsey-Bank of Canada scenario estimates that broad AI adoption could lift GDP by 6–8 % by 2030, roughly $200 billion in added output. Yet only one-third of Canadian mid-market firms have an AI strategy.
| Sector | Potential GDP Boost (2030) | Adoption Rate 2025 | Source |
|---|---|---|---|
| Financial Services | +2.0 % | 70 % | BoC & McKinsey |
| Manufacturing | +1.5 % | 45 % | NRC / Deloitte |
| Health & Public | +1.2 % | 30 % | OECD Digital Economy Outlook |
| Total Economy | +6 – 8 % | — | McKinsey Scenario |
Implementation Challenges
- Limited AI literacy beyond tech teams.
- Fragmented data infrastructure.
- Privacy and governance complexity across provinces.
What Leaders Can Do
- Adopt “AI + Human” workflows. Embed automation into process design, not bolt-on apps.
- Invest in data foundations. Clean, standardized data yields most of AI’s productivity value.
- Build AI ethics governance. Establish board-level oversight for transparency and bias prevention.
- Upskill workforce systematically. Integrate AI fluency into training budgets.
Arcus Insight: Treat AI as general-purpose infrastructure — not a side project. Early adopters are already capturing 15–25 % efficiency gains in finance, logistics, and customer operations.