KPMG Report: 93% of Canadian Businesses Use AI But Only 2% See Returns

A new KPMG survey reveals a striking disconnect in Canadian business AI adoption: while 93% of organizations now use artificial intelligence in some form, only 2% are seeing any return on their generative AI investments. The findings highlight the gap between widespread AI implementation and realized business value, raising questions about how companies are deploying the technology.

The report surveyed 753 business leaders across Canada and found that AI usage jumped dramatically from 61% last year to 93% currently. However, the minuscule return rate suggests most organizations are still in experimental phases or struggling to translate AI capabilities into measurable business outcomes.

The Adoption-Value Paradox

The 32-percentage-point surge in AI adoption over a single year demonstrates that businesses view artificial intelligence as essential technology they cannot ignore. Competitive pressure, vendor marketing, and fear of falling behind competitors have driven rapid implementation across industries. Yet the 2% return figure reveals that adoption alone doesn't guarantee success.

This pattern mirrors previous technology waves where early adoption preceded clear value creation. Cloud computing, mobile applications, and big data analytics all experienced similar trajectories where widespread implementation preceded demonstrated ROI. The question is whether AI follows this historical pattern or faces unique challenges preventing value realization.

Several factors likely explain the low return rates. Many companies have deployed AI for experimental use cases rather than core business processes, limiting potential impact. Others may lack the data quality, technical expertise, or organizational change management required to effectively implement AI solutions. Additionally, measuring AI returns remains challenging, with benefits often manifesting as productivity improvements or cost avoidances rather than direct revenue increases.

What Businesses Are Actually Doing with AI

The survey doesn't detail specific AI use cases, but industry patterns suggest most Canadian businesses are deploying AI in relatively limited ways. Customer service chatbots, automated email responses, and basic data analysis represent common entry points requiring minimal technical sophistication or organizational change.

More transformative applications—using AI for product development, strategic decision-making, or business model innovation—remain less common. These higher-impact use cases typically require significant investment in data infrastructure, specialized talent, and process redesign. The 2% return figure suggests few organizations have progressed to this level.

Generative AI tools like ChatGPT, Claude, and specialized industry solutions have lowered barriers to AI experimentation. Employees across organizations now use AI for writing, research, and analysis without formal approval or tracking. This informal adoption likely contributes to the high usage rates but may not translate into measurable business value.

Industry-Specific Challenges

Canadian businesses face particular challenges implementing AI effectively. Smaller market size compared to the United States means less venture capital available for AI startups and fewer experienced AI practitioners. Companies outside major cities like Toronto, Montreal, and Vancouver struggle to recruit specialized talent required for sophisticated AI implementations.

Regulatory considerations also play a role, particularly in highly regulated industries like finance, healthcare, and telecommunications that comprise significant portions of the Canadian economy. Privacy laws, data residency requirements, and sector-specific regulations can limit how companies deploy AI, potentially constraining return potential.

Resource-based industries important to the Canadian economy—energy, mining, forestry—may face longer timelines for AI value realization. These sectors require specialized AI applications rather than generic tools, demanding custom development that increases costs and extends payback periods.

The Path to Value Creation

The KPMG findings suggest that most organizations need to fundamentally rethink their AI strategies. Rather than broad experimentation across multiple use cases, companies may achieve better returns focusing resources on specific high-impact applications aligned with core business objectives.

Successful AI implementation typically requires investments beyond the technology itself. Data quality improvements, employee training, process redesign, and organizational change management all contribute to whether AI generates returns. Companies treating AI as purely a technology purchase rather than a business transformation initiative may struggle to demonstrate value.

Building internal AI expertise represents another critical factor. Organizations relying entirely on vendors for AI solutions often struggle to effectively evaluate, implement, and optimize these technologies. Developing internal capabilities—even modest ones—helps companies make better decisions about AI investments and maximize their value.

What This Means Going Forward

The KPMG report serves as a reality check for AI enthusiasm. While the technology holds genuine transformative potential, realizing that potential requires more than simply adopting AI tools. Companies need clear strategies, appropriate investments, and realistic timelines for value creation.

The 2% return figure may actually understate challenges, as measuring AI ROI remains difficult and companies may not be tracking returns systematically. However, it also suggests that early movers who figure out effective AI implementation could gain significant competitive advantages over the 98% still searching for value.

For the AI industry, the findings highlight the importance of moving beyond technology capabilities to focus on business outcomes. Vendors that help customers actually achieve returns—rather than simply deploying AI—will likely capture disproportionate value as the market matures.