Canada stands at a critical juncture in the global race to adopt artificial intelligence, but a new report by John Stackhouse, senior vice president at RBC, reveals that the country risks falling behind due to a pervasive “imagination gap.” Despite world-class research talent and early ambitions to lead in AI, Canadian businesses are struggling to embrace the technology’s transformative potential.
The report he cites, titled “Bridging the Imagination Gap,” identifies cultural, operational, and psychological barriers—rather than technological shortcomings—as the primary obstacles holding Canadian firms back.
Here are five key takeaways from John Stackhouse’s report.
1. Interest in AI adoption is a good sign, but we need to translate it into action
Recent data from Statistics Canada paints a mixed picture of AI adoption across the country. In the second quarter of 2024, just 6.1 percent of Canadian enterprises reported using AI in their operations. By the same period in 2025, that figure had doubled to 12.2 percent, signalling growing interest in the technology. Nearly 18 percent of firms expressed intentions to adopt AI software in the coming year, with an additional 6 percent planning to deploy AI-enabled hardware. While these numbers suggest momentum, the report cautions that interest alone does not guarantee execution.
The adoption rates vary dramatically by sector, revealing stark disparities in how different industries perceive AI’s value. Professional, scientific, and technical services (37.7 percent) and information and cultural industries (37.8 percent) lead the charge in planned AI adoption, reflecting their tech-savvy nature.
However, sectors that form the backbone of Canada’s economy—manufacturing, retail, and construction—lag significantly, with fewer than one in five businesses planning to integrate AI. This divide suggests that traditional industries may be struggling to envision practical applications for AI in their operations.
Compounding the problem is a widespread lack of AI literacy among Canadian workers. A 2025 KPMG Canada survey found that only 24 percent of employees have received any form of AI education or training. This knowledge gap fuels skepticism and slows workplace acceptance of AI tools. Paradoxically, this apprehension persists despite overwhelming evidence of AI’s benefits.
A Business Development Bank of Canada study revealed that 97 percent of small and medium-sized enterprises (SMEs) that adopted AI reported tangible improvements in their operations. The disconnect between AI’s proven value and its slow adoption underscores what RBC calls the “imagination gap”—a failure to recognize how AI could transform businesses across all sectors.
2. Risk today, reward tomorrow
One of the most significant barriers to AI adoption in Canada is what RBC terms the “first-mover dilemma.” Implementing AI requires substantial upfront investments—financial, reputational, and operational—while the benefits often materialize gradually and may seem abstract to decision-makers. This creates hesitation at the leadership level, with Canadian technology officers frequently facing six to 12-month approval delays due to cost-benefit uncertainty.
The report contrasts this cautious approach with the more aggressive adoption strategies of Canadian divisions of global firms, which are often less likely to approve AI pilots than their U.S.-based counterparts. This reluctance comes at a cost.
Bell Canada serves as a case study in overcoming this challenge. In 2023, the company initiated board-level tutorials on AI’s potential and quantified the opportunity cost of inaction. This strategic framing led to rapid funding approvals for AI-driven speech analytics, which now processes over 50,000 customer calls daily, transforming both client experience and internal workflows. The lesson is clear: when businesses present AI as a strategic imperative rather than a technological experiment, they can overcome inertia and unlock both capital and momentum.
3. How AI literacy is the missing middle
The RBC report identifies low AI literacy as a critical barrier to widespread adoption. With only one in four Canadians having received any AI-related training, there’s limited understanding of its capabilities and risks. This knowledge gap fuels skepticism at all organizational levels, from frontline workers to executives, slowing buy-in and implementation.
Successful companies have addressed this challenge by embedding AI literacy into their workforce development strategies. Hopper, a Montreal-based travel platform, provides a compelling example. Instead of replacing customer support staff with AI systems, the company retrained its employees for AI-enhanced roles.
The results were striking: 75 percent faster inquiry handling, resolution times reduced from 20 minutes to under five, and approximately 90 percent cost savings. This approach not only improved efficiency but also demonstrated how human-AI collaboration could create value. The report also highlights grassroots innovation as a powerful antidote to skepticism.
Lumberhub, an online marketplace for lumber purchases, faced a critical pricing lag in its operations. An employee without deep coding expertise leveraged generative AI to build a quoting engine that automated pricing and inventory data integration—a process previously performed manually over the phone. By empowering such “super-agents”—employees who experiment with and implement AI solutions—companies can turn skepticism into ingenuity and drive organic AI adoption from within.
4. Canadian organizations need a starting point
For many Canadian organizations, particularly larger ones, the challenge isn’t a lack of potential AI applications but an overabundance of possibilities. RBC’s research shows that companies often become paralyzed when faced with numerous potential use cases, struggling to prioritize which applications to pursue first. This analysis paralysis stalls the implementation of high-value opportunities that could deliver significant returns.
The report identifies three common barriers that prevent successful scaling of AI initiatives: budget cliffs between pilot funding and operational integration; “champion churn,” where internal advocates leave and take momentum with them; and ROI misalignment, where technical successes fail to translate into financial metrics that resonate with decision-makers.
To overcome these challenges, RBC suggests that businesses need to develop robust internal evaluation processes to prioritize AI projects effectively. More importantly, they must learn to articulate AI’s benefits in language that resonates with decision makers—focusing on productivity gains, profitability improvements, and long-term value creation rather than technical specifications. This translation from tech-speak to business outcomes is crucial for securing ongoing support and funding for AI initiatives.
5. What are the foundations for AI success in Canada?
The report identifies two fundamental prerequisites for successful AI adoption that many Canadian businesses lack: quality data and adequate computing infrastructure.
On the data front, many Canadian firms struggle with low-quality, fragmented, or siloed information. Small and medium-sized enterprises, many of which operate on legacy systems, face particularly steep integration challenges. The healthcare sector illustrates this problem vividly. St. Michael’s Hospital in Toronto is part of GEMINI, Canada’s largest hospital data platform, which integrates over 60 percent of Ontario’s hospital data.
Despite this achievement, the platform still faces significant governance and interoperability challenges. Infrequent data refresh cycles and format mismatches delay real-time applications and compromise potential savings, particularly in areas like clinical trials, where automation could reduce costs by up to 80 percent.
The infrastructure challenge is equally pressing. Canada trails every other G7 nation in AI compute capacity, with approximately one-tenth the per capita resources of the United States.
This shortage creates bottlenecks that slow iteration and innovation. Training cycles that should take hours can stretch into days due to waiting times in public computer queues. While private cloud services—primarily U.S.-based—offer alternatives, they raise sovereignty and security concerns for sensitive applications.
There are signs of progress. Ottawa’s new $2 billion Canadian Sovereign AI Compute Strategy, including the CoreWeave-Cohere partnership, aims to provide domestic high-performance computing resources. Regional initiatives in Alberta also show promise. However, the report emphasizes that without rapid deployment and clear incentives, Canada risks losing its competitive edge not from lack of talent, but from inadequate infrastructure.
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Generative AI assisted in the production of this story.
