AI is everywhere in Canadian business, except the bottom line

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It’s a scene playing out in boardrooms across Canada. 

Executives are investing in AI, chasing productivity gains, new efficiencies, and the promise of smarter decision-making, but few can explain what it’s actually doing for their bottom line. 

A recent KPMG’s survey of 753 Canadian business leaders found adoption has surged from 61 to 93% since 2024. Yet only 31% have fully integrated AI into core operations, while another third are testing it in parts of their business. The rest are still experimenting.

The findings suggest a widening gap between optimism and outcomes that could shape Canada’s economic trajectory for years to come.

For many, AI remains a series of tests rather than a system-wide shift in how work gets done. The result is a national AI boom still waiting to prove its worth at the enterprise level, and a growing sense among executives that adoption alone is no longer enough.

ROI is elusive, and the clock is ticking

Right now, just two percent of leaders report seeing measurable ROI from their AI investments, most of them (63%) at large firms earning over $1 billion in annual revenue. 

Three in ten expect returns within the year, while 61% believe it will take up to five years.

“Only a small sliver of Canadian businesses are generating growth from their AI investments today, and that’s understandable — new technologies take time to be adopted and demonstrate identifiable return on investment,” says Stephanie Terrill, Canadian managing partner of digital and transformation at KPMG Canada.

“Canada is facing near-term threats to its economic competitiveness and grappling with declining productivity and prosperity, so waiting years for AI investments to create value isn’t realistic,” she added.

Measuring what matters

The challenge is knowing what to track. 

More than half of respondents said they struggle to capture value from AI, and fewer than four in ten have a clear plan for doing so. 

Terrill argues that the issue lies in outdated ROI frameworks.

“To realize the full value of AI, organizations need clear ROI frameworks that measure not just financial impact, but strategic and capacity gains,” she says. “Paired with strong governance and accountability, that’s how businesses will turn AI ambition into measurable results”.

KPMG recommends combining traditional metrics like cost savings and productivity with softer indicators such as employee experience, customer loyalty, and smarter decision-making. 

These measures give a truer picture of AI’s impact on competitiveness and culture.

Investing in people as much as platforms

While many executives are prioritizing tools and systems, talent remains a critical piece.

Nearly half of surveyed companies (46%) are focusing AI budgets on hiring new tech talent, with 41% investing in generative AI tools and 33% in change management and adoption.

Only 35% of leaders strongly agree their employees have the right skills to fully leverage AI. 

“Business leaders are no longer thinking about whether they should invest in AI — they’re focusing on how to scale it responsibly and effectively,” Terrill says. 

“That’s why organizations need to make investments not just in technology, but in the people and processes that make AI work — including a strong focus on AI literacy to ensure teams are empowered to use these tools with confidence and clarity.”

Why this matters

Adopting AI isn’t the hard part anymore. Turning it into value is. 

The survey suggests that AI maturity in Canada is growing fast, but the ability to measure, scale, and embed it remains uneven. That matters in a country already grappling with slow productivity growth and labour strain.

“Canadian organizations need to accelerate AI implementation into core operations to start achieving near- to medium-term productivity gains if we hope to become more economically competitive as a country,” said Terrill.

The challenge now is less about experimentation and more about execution, moving from pilots and promises to performance and proof. How Canada meets that moment could determine whether its AI boom translates into real economic strength.

Final shots

• AI adoption in Canada is high, but integration depth and ROI tracking lag.
• Measuring AI’s real impact requires both hard numbers and strategic metrics tied to growth and capability.
• Companies that build literacy and align AI with core operations, not just pilots, will see faster returns.
• Canada’s competitiveness depends on how quickly its organizations can move from experimentation to execution.