Key Points:

1. Canada’s AI brain drain threatens national competitiveness by eroding the local talent base essential for innovation and execution

   
   

2. Without retaining AI expertise, Canada risks becoming dependent on foreign ecosystems, which undermines sovereignty and commercialization potential

   
   

3. Business leaders must treat AI talent development as a core strategy—Canadians need to build, invest, and upskill locally to remain competitive

Canada is starting to punch above its weight in AI. With world-class research hubs in Toronto (Vector Institute), Montreal (Mila), and Edmonton (Amii), and visionaries such as Geoffrey Hinton and Yoshua Bengio driving Canada’s AI momentum, Canada is increasingly recognizable around the globe as a hotspot for innovation.

Alas, as the global AI boom accelerates, Canada is at risk of losing that advantage through exodus of talent. The phenomenon, often dubbed the “AI brain drain”, refers to top researchers, engineers, and startup founders relocating (or aligning remotely) with U.S. or global tech hubs as opposed to building at home.

For a business leader in Canada who is currently considering AI, this trend is one to keep an eye on because the stakes are high: how easily one can recruit, retain, and deploy AI talent will increasingly define which firms win or lose over the next half decade and beyond.

Why Business Leaders Should Pay Attention

Seeing talent leave or take jobs globally has multiple implications in terms of AI-driven innovation and the extent to which they can make an impact for Canadian businesses. Let’s take a closer look at three of them:

First, the absence of talent is an AI execution bottleneck. In many industries, the difference between AI as a novelty versus a value-creator lies in execution, not algorithms. That execution depends on access to specialized engineers, ML researchers, operations talent, data scientists, hybrid roles, and so on.

If a tech company plans on adopting or building AI, it will have to compete not only with other Canadian firms, but also with global tech giants offering premium compensation, equity, and prestige. That competitive pressure already manifests in Canada’s tech sector, where many former Canadian AI founders and researchers have relocated or anchored operations in Silicon Valley or U.S. hubs despite having roots here.

Losing that talent, or failing to attract it, translates to longer timelines, lower quality, higher costs, or outright stalling of AI initiatives.

Second, dependency on external ecosystems weakens innovation sovereignty. Relying on remote work or foreign talent is a short-term fix. If a company’s AI strategy depends on overseas labs, it risks instability from geopolitical shifts, visa regimes, cross-border regulation, or simple churn in remote teams.

Canada’s recent announcement of a $2 billion+ Canadian AI Sovereign Compute Strategy is a response to such vulnerabilities: the federal government wants Canada to own its compute infrastructure rather than remain tethered to foreign cloud or GPU suppliers.

Unfortunately, computing power alone is simply not enough. To leverage it fully, Canada needs people who know how to harness it. Without a base of AI talent anchored in Canada, compute investments risk underutilization and may be forced to finding support beyond the border.

Moreover, it is important to keep in mind that investments in AI compute are considerably larger in other jurisdictions such as the United States; even if Canadian AI founders want to stay in Canada to use the new AI infrastructure, the Canadian compute will pale in comparison to the sorts of opportunities that the Americans are offering. Therefore, it will also be challenging to convince founders to take advantage of Canada’s AI compute.

Third, the “imagination gap” will widen. Rather ironically, Canada lags many peers in actual AI adoption. Despite being a global leader in AI ideation and innovation, 12 percent of Canadian firms have broadly integrated AI into operations or products, putting the country near the bottom of OECD adoption rates.

Some of this gap stems from cultural and literacy issues. But the primary issue is structural; if Canadian firms can’t access or retain top talent, pilots stay pilots, and experimentation never scales. The brain drain heightens that barrier. In effect, the Canadian market becomes a slow adopter, while global firms dominate the frontier.

Catalysts of the Brain Drain

It’s important to understand where the pressure comes from if Canada is to begin recognizing countermeasures. They are ubiquitous and complicated, but let’s quickly identify the most critical:

Compensation and equity. U.S. tech firms routinely offer higher absolute compensation and more liquid equity upside

Prestige. Many researchers seek the cachet of working at OpenAI, DeepMind, or leading U.S. AI labs

Scale and data access. Larger U.S. and international firms have access to vast user bases and data that Canada-based projects often can’t match

Funding scale. Global venture capital and public markets remain deeper and more aggressive than those in Canada

Remote work. Many Canadian researchers don’t physically relocate now, but instead work remotely for international firms while remaining in Canada

What Canadian Business Leaders Should Do About the AI Brain Drain, Right Now

If you are serious about embedding AI in your organization, there are crucial steps you can take right now to join other business leaders seeking to alter the course of the brain drain.

For starters, Canadian business owners need to invest in AI anchors. More specifically, it is important to create internal AI competence centers or labs rather than AI projects. It is also important to provide mandates, budgets, visibility, and career ladders. Ask yourself, What would talent want or need? It is necessary to attract Canadian talent to the centers and labs that have been created in such that the opportunity is interesting.

It’s also important to offer compelling equity and long-term incentives. It’s expensive, but if the talent economy in Canada is to bolster itself, employers need to be thinking more strategically about matching or emulating international-esque equity models, grants, and research budgets. Engineers want to feel that they can build something significant—companies are recommended to do what they can to build the sandboxes that these engineers want to play in.

Furthermore, companies are encouraged to partner with local colleges and universities for that they can  align their interests with those of Canada’s top AI innovators. Develop interesting ways to fund cross appointments, joint labs, or even industrial research chairs.

Companies may also wish to ask themselves, How skilled is our existing talent? If companies are not sure, they would benefit from upskilling. To begin, companies can drive internal reskilling and establish AI‐centric learning paths. That is, engaging workers in AI 101 learning sessions can help non-technical staff understand AI itself.

Lastly, but perhaps most importantly, it is important to frame AI strategy as core business strategy—not a side project. AI disruption is old news. The ship has already set sail. Every industry is transforming. If companies are adopting AI now or are panning  to do so in the near future, it is best to think strategically. For instance, ask, How might AI drive our business strategy as opposed to merely summarizing emails? By making AI more self-evidently valuable in terms of business growth, companies are more likely to attract talent.

Delaying Investment in AI Talent is a Strategic Risk

Canada’s AI brain drain may still feel distant to many executives, but the lead time for losing competitive edge is long. If Canadian firms don’t move to secure talent now, they’ll find themselves significantly behind their competitors.

For any business in Canada that is eyeing AI, the choice is not whether to care about the brain drain. It’s whether to treat it as a strategic pillar.