Canada Urged to Scale AI Investment to $10B to Bridge "Commercialization Gap"

Canada stands at a critical juncture in the global artificial intelligence race. Despite housing approximately 10% of the world's top AI researchers, the nation captures less than 2% of global venture capital investment in the sector. A new joint report released on January 19, 2026, by Mila (Quebec Artificial Intelligence Institute) and global consultancy Bain & Company argues that this disparity represents a fleeting economic opportunity. The report, titled The Rise of the Canadian Venture Scientist, calls for a dramatic fivefold increase in annual AI venture capital investment—from $2 billion to $10 billion—to align Canada’s financial ecosystem with its scientific prowess.

The central thesis of the report is clear: Canada has successfully established itself as a research powerhouse but risks becoming a "farm team" for other nations if it cannot convert its intellectual property into domestic commercial success. The data presented underscores a worrying trend of talent and value migration, prompting urgent calls for systemic changes in how the country supports deep-tech founders.

The Disparity Between Talent and Capital

The report highlights a stark asymmetry between Canada's intellectual contributions to AI and its commercial capture of that value. While Canadian institutions have been pivotal in the development of modern deep learning, the financial infrastructure required to scale these innovations remains underdeveloped compared to global competitors, particularly the United States.

According to the findings, Canada deployed approximately $2 billion in venture capital toward AI startups in 2024. While significant, this figure pales in comparison to the capital intensity seen in other leading AI nations. To match its 10% share of global AI research talent, the report estimates that Canada’s investment levels must rise to approximately $10 billion annually.

Table 1: The Canadian AI Ecosystem Gap

Metric	Current Status (2024)	Target Status
Global Share of Top AI Researchers	~10%	Maintain Leadership
Global Share of AI VC Investment	< 2%	~10%
Annual AI Venture Capital Deployed	$2 Billion	$10 Billion
Location of High-Potential Startups	Majority HQ abroad	Majority HQ in Canada

The consequences of this capital gap are measurable. The report reveals that in 2024, two-thirds of high-potential Canadian-led startups—defined as those raising more than $1 million—were headquartered outside of Canada. This "brain drain" of incorporated entities means that the long-term economic benefits, including tax revenue, job creation, and ecosystem maturity, are accruing elsewhere.

The "Farm Team" Dilemma

Stéphane Marceau, Managing Director of Mila Ventures, framed the issue as a structural failure to support the transition from lab to market. "Canada has proven it can lead in AI science. Now it needs the on-ramps that help researchers turn breakthroughs into companies that start and scale here," Marceau stated.

He warned that without immediate intervention, Canada risks solidifying its position as a supplier of raw talent rather than a builder of industry. "We are not just a farm team but a place where enduring companies get built, before the window closes," Marceau added, emphasizing that retaining value requires more than just funding—it requires an ecosystem that provides operator partners, early access to compute power, and real-world testing environments.

Defining the "Venture Scientist"

A key concept introduced in the report is the "Venture Scientist." This term describes a specific profile of founder: frontier technical or scientific experts who transition directly from research to building venture-scale companies. These individuals are distinct from traditional software entrepreneurs because their companies are built on novel, often unproven scientific breakthroughs rather than engineering innovations alone.

The report argues that the Venture Scientist is the critical node in the deep tech ecosystem. However, these founders face unique challenges. Unlike typical SaaS founders, they often lack commercial experience and require a support system that pairs them with execution-focused leadership and "go-to-market" expertise.

Key Support Requirements for Venture Scientists:

• Co-founder Matching: Pairing scientific brilliance with commercial execution and operational leadership.
• Infrastructure Access: Subsidized or prioritized access to high-performance computing (HPC) and sovereign cloud resources.
• Accelerated IP Transfer: Streamlined pathways to move intellectual property from university labs to private entities without debilitating bureaucratic friction.

Mobilizing Capital and Policy

While the target of $10 billion seems ambitious, the report notes that the Canadian ecosystem already possesses significant untapped potential. It estimates that there is currently $11.5 billion in "dry powder" (committed but unallocated capital) available within the Canadian venture capital landscape. AI currently accounts for about 30% of Canadian VC investment, suggesting that while the interest exists, the scale of deployment needs to accelerate drastically.

Luca Diomede, a Montreal-based Partner at Bain & Company, described the current moment as a "unique window of opportunity." He stressed that the solution requires an "all-around mobilization" of investors, policymakers, and academic institutions. "The bottom line is blunt: Canada doesn't need more proof of its assets. It needs conviction and execution now to turn research leadership into companies," Diomede said.

Strategic Recommendations

To bridge the gap, the report outlines a multi-stakeholder approach. It is not enough for the government to simply increase grants; private capital must be unlocked, and corporate Canada must become an active adopter and acquirer of domestic AI technology.

The report’s recommendations include:

1. System-Wide Coordination: Aligning university tech transfer offices, incubators, and VCs to reduce friction for spinning out companies.
2. Sovereign Compute Strategy: Ensuring Canadian startups do not have to rely solely on foreign infrastructure to train foundation models, which often leads to data and IP leakage.
3. Talent Retention via Ownership: Creating tax and equity structures that make it financially attractive for top researchers to build their companies domestically rather than moving to the Bay Area or London.

The urgency of the message is underscored by the rapid pace of global AI development. As other nations aggressively subsidize their domestic AI sectors and compete for the same pool of talent, Canada’s historical advantage in research is under threat. The transition from a research hub to a commercial powerhouse is not guaranteed, and as the report concludes, the defining moment for Canada's AI economy is unfolding right now.