- Canadian companies are rapidly adopting AI, but many are struggling to achieve consistent returns and keep governance aligned
- Technology leaders report low preparedness as AI deployment scales, with oversight, security, and accountability gaps widening
- Workforce readiness is a major challenge, with significant upskilling and reskilling needed to fully realize AI benefits
- IBM stock (NYSE:IBM) opened trading at US$262.11
Canadian firms race to scale AI, but governance and workforce gaps raise execution risks
Canadian organizations are accelerating the adoption of artificial intelligence to drive productivity and growth.
Still, new research from IBM (NYSE:IBM) suggests many may not yet have the governance, workforce readiness, or accountability frameworks needed to deliver consistent returns for investors.
Findings from two global studies conducted by the IBM Institute for Business Value, in partnership with Oxford Economics, highlight a widening “control gap” among Canadian enterprises. While executives are moving quickly to embed AI across business operations, internal systems for oversight and execution are struggling to keep pace.
This article is a journalistic opinion piece that has been written based on independent research. It is intended to inform investors and should not be taken as a recommendation or financial advice.
Strong AI ambition, mixed financial results
According to the CEO survey, Canadian leaders are broadly confident in their AI strategies. About 90 per cent of Canadian CEOs report embedding AI across multiple workflows, and 80 per cent believe they are deploying the technology at a pace sufficient to meet business objectives.
However, the financial outcomes have been less consistent. Only 43 per cent of AI initiatives have delivered their expected return on investment over the past two years, exploting a disconnect between ambition and execution.
For investors, the data suggests that while AI spending and adoption will likely continue to rise, near-term returns may remain uneven as companies grapple with integration challenges, governance gaps, and workforce adaptation.
“Canadian organizations are still figuring out how to scale AI responsibly,” Manav Gupta, Vice President and CTO of IBM Canada, said in a news release. “What we’re seeing is a growing gap between the speed of adoption and the governance, operating models and workforce readiness needed to support it. Closing that gap will be critical to realizing AI’s full value and staying competitive.”
AI deployment surging, but preparedness lags
The report points to significant growth in AI deployment over the next several years. Canadian C-suite technology leaders expect an average of 1,189 AI agents to be deployed by 2027, representing a 36 per cent increase from current levels. This reflects a shift from experimental pilots toward embedding AI systems deeply into everyday operations.
Despite this rapid expansion, only 9 per cent of Canadian technology leaders say they feel fully prepared for the coming wave of AI deployment.
The research highlights a growing strain on IT and governance systems:
- 68 per cent of technology leaders report being accountable for AI systems they do not fully control
- 73 per cent say AI adoption is outpacing their IT governance capabilities
- 50 per cent cite security and compliance as the primary barriers to scaling AI effectively
These findings suggest that as AI ecosystems become more decentralized—often involving third-party models, cloud providers, and autonomous agents—accountability structures have not evolved at the same pace.
For investors, this introduces potential operational and regulatory risks, particularly in industries with stringent compliance requirements such as financial services, healthcare, and aerospace.
Workforce transformation emerges as key constraint
Beyond technical infrastructure, IBM’s CEO study emphasizes that workforce readiness may be the most significant determinant of AI success.
A strong majority—80 per cent of Canadian CEOs—say that the effectiveness of AI initiatives depends more on employee adoption than on the technology itself.
The anticipated scale of workforce disruption is substantial:
- By 2028, 53 per cent of employees will require upskilling to remain effective in their current roles
- 29 per cent will need to be reskilled entirely for new roles created by AI integration
This signals that human capital investment—training programs, organizational redesign, and change management—will play a critical role in determining which companies successfully translate AI investment into productivity gains.
For institutional investors, companies that proactively address workforce transition may be better positioned to capture long-term value, while those that underinvest in talent adaptation could face productivity drag and execution risk.
Governance and architecture become strategic differentiators
Some organizations are beginning to address these challenges by redesigning their technology and governance frameworks.
Boris Alexandre, Chief Information Officer for North America at Airbus Canada, highlighted the importance of modular system design: “We design modular architectures so components can evolve as technology advances, without breaking the overall system.”
This approach allows companies to adapt to rapid technological change while maintaining long-term operational stability—an increasingly valuable capability as AI tools and platforms evolve quickly.
The IBM research suggests that organizations with stronger governance maturity, clearer accountability structures, and flexible technology architectures are more likely to scale AI effectively and realize consistent returns.
Implications for investors
The findings expose a critical phase in enterprise AI adoption: the transition from experimentation to scaled implementation. While Canadian firms are clearly investing aggressively in AI, execution risks remain elevated.
Key takeaways for investors include:
- Growth momentum is strong: AI adoption is accelerating and will likely remain a core driver of enterprise investment.
- Returns remain uneven: Many initiatives are not yet delivering expected ROI, indicating a period of trial-and-error.
- Governance is a bottleneck: Weak oversight frameworks could lead to operational, compliance, and reputational risks.
- Workforce readiness is pivotal: Talent transformation may ultimately determine long-term winners.
- Preparedness varies widely: A small cohort of organizations appears ready to scale AI effectively, creating potential performance divergence across sectors and companies.
As AI continues to reshape industries, the gap between ambition and execution may become a defining factor in corporate performance. For now, IBM’s research suggests that while Canadian organizations are eager participants in the next era of business AI, many still face foundational challenges before they can fully deliver on its promise.
About IBM
International Business Machines Corp. is a global hybrid cloud, AI and consulting company with clients in more than 175 countries.
IBM stock (NYSE:IBM) opened more than 2.5 per cent higher at US$262.11 and has risen around 9 per cent in the past three months but has lost 10 per cent since this time last year.
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