Editor’s note: This is the second article in an ongoing series by Dr. Andrew Maxwell, the Bergeron Chair in Technology Entrepreneurship in the Lassonde School of Engineering at York University. Every other week – and occasionally every week – we’ll present a new article by Maxwell, in a series whose wide-ranging and incisive themes encompass: Canada and innovation policy; productivity and industry; innovation frameworks; AI and higher education; research and intellectual property; technology adoption; entrepreneurship and commercialization; universities and higher education; entrepreneurship education; and AI and the future of work. The first article was published on May 20, 2026.

Canada loves to talk about innovation.

We celebrate AI breakthroughs. We fund research. We launch programs. We announce strategies. And then we wonder why productivity barely moves.

Recent remarks by federal AI Minister Evan Solomon highlighted Canada’s strengths in AI and innovation. He is right: Canada has world-class researchers, leading AI institutes, strong universities and growing investment.

But reassurance is not a strategy.

The problem is not that Canada lacks innovation. The problem is that Canada struggles with adoption – and adoption is what drives productivity and economic impact.

This is not new. For more than 30 years, Canadian reports have identified the same gap: strong discovery, weaker commercialization and slow diffusion.

The terminology has changed – commercialization gap, productivity puzzle, innovation paradox – but the diagnosis is consistent. Canada invents. Canada funds. But Canada adopts slowly.

The performance metrics tell the story.

Canada’s productivity growth has lagged peer countries for decades. But aggregate productivity numbers mask an important distinction. Parts of the business sector, particularly advanced manufacturing, are beginning to see productivity gains associated with automation, robotics and digital technologies. These improvements are encouraging because they demonstrate that technology adoption works.

Yet overall productivity remains weak. One reason is that large non-business sectors – health care, education, and public administration – have seen far less transformation.

These sectors represent a significant share of the economy, but they often operate with limited competitive pressure, risk-averse governance structures, and procurement systems that discourage experimentation. As a result, productivity gains in business sectors are diluted by stagnation elsewhere.

Even within manufacturing, adoption is uneven. Advanced manufacturing sectors that integrate digital technologies are improving performance, while process industries often show slower gains. The result is not a broad productivity surge, but pockets of success surrounded by slow diffusion.

Innovation is not invention – it is adoption

This pattern reinforces a simple point: innovation is not invention –  is adoption.

Most of the economic value of innovation comes not from breakthroughs but from widespread deployment. Adoption requires organizations to change workflows, develop new skills, and accept short-term disruption. These are behavioural and institutional challenges, not technological ones.

Funding research is easier than driving adoption. Doing more of the same therefore produces incremental results.

Organizations resist change. Risk aversion is rational. Incentives reward maintaining the status quo. Performance metrics emphasize activity rather than outcomes. These structural factors slow adoption – and slow productivity.

For years, Canada’s structural weaknesses were masked by favourable conditions: strong resource demand, stable trade relationships and proximity to the United States. That buffer is eroding. Countries are now competing not just on AI discovery, but on AI deployment. Competitive advantage increasingly depends on how quickly organizations adopt and integrate new technologies.

Standing still is no longer neutral. It is falling behind.

One reason adoption remains slow is rarely discussed. Canada has limited capability in innovation management. We train engineers to design technology and scientists to discover knowledge, but we rarely train leaders to manage the adoption of innovation.

Adoption requires evaluating uncertainty, redesigning workflows, aligning incentives, and scaling pilots. Without this capability, organizations default to incremental change.

If the diagnosis is slow adoption, the treatments look very different from traditional innovation policy. The focus shifts from funding inputs to accelerating deployment. Success must be measured not by research outputs, but by productivity gains and organizational transformation. Policies must encourage experimentation and reduce the perceived risk of adoption. Procurement must enable, rather than constrain, innovation. And the largest opportunities may lie not in inventing new technologies, but in transforming how health care, education, and public services operate.

There are encouraging signs. Manufacturing adoption is improving. AI capability is strong. The foundation exists. The challenge now is diffusion.

For 30 years, Canada has recognized the gap between discovery and impact. The difference today is urgency. The global environment is forcing the issue. Countries that adopt faster will pull ahead. Those that do not will gradually fall behind.

Innovation requires adoption.
Adoption requires change.
Change requires capability.

Canada does not need more innovation announcements. It needs a strategy for adoption.

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