From the Trenches: Five Pillars for Canada’s Next AI Strategy
Actionable Insights from an AI Founders Roundtable: A Direct Response to the Federal AI Strategy Task Force Consultation
The Canadian AI ecosystem is standing at a critical juncture. We, the founders actively building the future of artificial intelligence in this country, are constantly grappling with the global acceleration of technology and the persistent challenge of translating groundbreaking research into scalable, domestic businesses.
The announcement by the Honourable Evan Solomon, Minister of Artificial Intelligence and Digital Innovation, regarding the launch of the AI Strategy Task Force and the subsequent national sprint, is a welcome and necessary intervention. Canada needs a renewed strategy to position itself at the forefront of this technological revolution and secure its digital sovereignty. Our goal in contributing to this discussion is simple: to provide pragmatic, actionable insights based on the realities faced by founders in the trenches, addressing crucial issues like talent and capital flight to the US.
We recognize that Canada has already made significant strides, notably through the Pan-Canadian AI Strategy (PCAIS) and initial investments like the $2 billion Canadian Sovereign AI Compute Strategy. Organizations like Scale AI are successfully accelerating the integration of AI across business sectors by funding industry-led projects, training, and acceleration programs. However, the current pace of global innovation—driven by virtually infinite money and infrastructure in competing nations—demands radical change.
We gathered to respond to the core questions posed by the federal AI task force survey. Our collective response outlines five essential pillars required to accelerate Canada’s AI adoption and enable global scaling.
1. Research: Beyond the Vertical Niche
The idea of picking a single niche research area for Canada to dominate right now is, frankly, a dangerous hot take. Innovation often arises from non-obvious general applications, not predetermined silos. Instead of narrowly defining verticals, Canada should focus research investment on foundation-level AI, supporting organizations that can produce open-source models and general advancements, similar to what universities in the US and China are doing.
However, if investment must target specific domains where Canada has natural advantages or acute national needs, our suggestions include:
AI Healthcare: Leveraging Canada’s existing talent and knowledge base to solve problems related to decentralized, distributed populations—such as developing offline LLMs that function in remote environments like remote reserves. This focus addresses the acute systemic inefficiencies plaguing Canadian healthcare, where wait times for essential services can stretch for years.
Hardware and Climate Data: Investing in how to integrate current physical infrastructure (sensors, moisture readers, heat sensors) with AI platforms. This ties into developing accessible, sanitized, and verified government data sets (climate models, housing data) to ensure search engines and applications provide reliable information, avoiding the current situation where researchers hit constant dead ends.
2. Infrastructure: Building Canadian Digital Sovereignty
The single biggest existential threat facing Canadian AI startups is infrastructure reliance on foreign jurisdictions, predominantly the US. We need to eliminate the current “platform risk” perception of Canada.
The most glaring gap is the lack of a true, sovereign, enterprise-ready cloud solution. We need a “Canadian AWS” equivalent. This is not about vanity—it is about economic survival, data sovereignty, and security, especially when dealing with sensitive information (PII or corporate trade secrets). Currently, US legislation like the Patriot Act allows the US government to access data stored on US systems globally, posing a major risk to any company handling Canadian data or working with government entities.
Canada possesses significant infrastructure advantages we must capitalize on now:
Cheap Compute and Power: Canada has inexpensive electricity (hydro/nuclear) and a climate suitable for cheap cooling in northern data centres. If Canada became known as the cheapest and easiest place to run AI models, it would be a substantial competitive advantage.
Open Source Foundation Models: We must fund research institutions like Mila to publish the first truly competitive Canadian open-source foundation model. This model, hosted and owned domestically, would provide a secure alternative to the OpenAI API for corporate fine-tuning and specialized application development.
3. Sector Readiness: Targeting Bureaucracy and National Needs
Which Canadian sector is most ready for AI adoption? It might not be the most obvious one, but rather the area where administrative inefficiency creates the greatest drag on our economy: Government Bureaucracy.
Administrative Streamlining: AI can revolutionize administrative processes, from municipal permitting (where getting approval can take over a year in places like Ottawa) to the notoriously slow and convoluted tax remittance process run by the CRA. Streamlining this bureaucracy means reallocating resources (instead of needing 10,000 extra people just to manage inefficient processes).
Barriers: The fundamental blocking factor here is that bureaucracy is the most risk-averse sector and often lacks understanding of AI’s potential.
National Priority Sectors: Other high-impact, ready sectors include Defense/Military (especially for Arctic surveillance and handling data from Canada’s vast landmass) and Resource Management/Mining, where productivity increases could meaningfully increase GDP due to Canada’s mineral wealth. Solving productivity problems in massive national problem spaces, like the housing crisis via construction logistics and permitting, is also essential.
4. Policy: A Wartime Footing for Innovation
The government must adopt a more radical approach to policy, treating this technological race like a “wartime effort”. The slow, restrictive nature of current regulation and investment is choking innovation at the cradle.
To scale globally from Canada, two policy shifts are paramount:
Special Economic Zones (SEZs): We need bold, geographically-focused innovation zones—perhaps in regions like Atlantic Canada, leveraging deep water ports and infrastructure. These SEZs should operate under a “No Parents, No Rules” approach, featuring zero capital gains tax for long-term investments. This is the necessary mechanism to directly unlock VC capital, which currently views Canada as a platform risk and forces companies to incorporate in Delaware.
Mandatory Government AI Spending: The government should mandate that a fixed percentage of every department’s budget be dedicated to investing in Canadian AI solutions to improve internal efficiency. This provides a vital domestic market for startups and generates immediate economic benefits. Furthermore, we suggest this strategic AI expenditure should count toward Canada’s NATO defense spending percentage commitment, recognizing that competence in AI is a modern defense necessity.
5. Procurement and Commercialization: Turning Prototypes into Products
The pathway from prototype to commercial product in Canada is needlessly difficult. The current government procurement process, exemplified by programs like Innovation Solutions Canada, is plagued by cancelled budgets and red tape, stifling critical iteration speed.
Procurement Reform: Streamline government purchasing and introduce Canadian preference policies for AI solutions. Entrepreneurs are primarily seeking fast feedback loops and iteration, not massive contracts—even sandboxing solutions within government departments would be invaluable.
Commercialization Tax Credits: We must extend or augment mechanisms like the SR&ED tax credit to support market validation and de-risking the prototype-to-product transition. Currently, capital flows too easily toward foundational research but stalls when commercial scale is required.
Incentivizing Domestic Capital: We need mechanisms to heavily incentivize angel and venture capital investment in Canadian startups, thereby countering the continuous pressure to incorporate offshore.
Canada has the talent and the foundational research. Now, we need the national ambition and the policy frameworks to execute at scale and speed. This is our opportunity to build the strongest economy in the G7—but only if we act like it.
Key Contributors to this article based on an extensive roundtable discussion with over 15 AI founders based in Ottawa: Rami Alhamad, Hai Nghiem, Brandon Hynes, Chris Bartholomew, and Aaron Gould.
We hope this inspires the Canadian government and other cities to host roundtables and gather more insights from the grassroots and the founders in the trenches currently working in AI.
king research into scalable, domestic businesses.
The announcement by the Honourable Evan Solomon, Minister of Artificial Intelligence and Digital Innovation, regarding the launch of the AI Strategy Task Force and the subsequent national sprint, is a welcome and necessary intervention. Canada needs a renewed strategy to position itself at the forefront of this technological revolution and secure its digital sovereignty. Our goal in contributing to this discussion is simple: to provide pragmatic, actionable insights based on the realities faced by founders in the trenches, addressing crucial issues like talent and capital flight to the US.
We recognize that Canada has already made significant strides, notably through the Pan-Canadian AI Strategy (PCAIS) and initial investments like the $2 billion Canadian Sovereign AI Compute Strategy. Organizations like Scale AI are successfully accelerating the integration of AI across business sectors by funding industry-led projects, training, and acceleration programs. However, the current pace of global innovation—driven by virtually infinite money and infrastructure in competing nations—demands radical change.
We gathered to respond to the core questions posed by the federal AI task force survey. Our collective response outlines five essential pillars required to accelerate Canada’s AI adoption and enable global scaling.
1. Research: Beyond the Vertical Niche
The idea of picking a single niche research area for Canada to dominate right now is, frankly, a dangerous hot take. Innovation often arises from non-obvious general applications, not predetermined silos. Instead of narrowly defining verticals, Canada should focus research investment on foundation-level AI, supporting organizations that can produce open-source models and general advancements, similar to what universities in the US and China are doing.
However, if investment must target specific domains where Canada has natural advantages or acute national needs, our suggestions include:
AI Healthcare: Leveraging Canada’s existing talent and knowledge base to solve problems related to decentralized, distributed populations—such as developing offline LLMs that function in remote environments like remote reserves. This focus addresses the acute systemic inefficiencies plaguing Canadian healthcare, where wait times for essential services can stretch for years.
Hardware and Climate Data: Investing in how to integrate current physical infrastructure (sensors, moisture readers, heat sensors) with AI platforms. This ties into developing accessible, sanitized, and verified government data sets (climate models, housing data) to ensure search engines and applications provide reliable information, avoiding the current situation where researchers hit constant dead ends.
2. Infrastructure: Building Canadian Digital Sovereignty
The single biggest existential threat facing Canadian AI startups is infrastructure reliance on foreign jurisdictions, predominantly the US. We need to eliminate the current “platform risk” perception of Canada.
The most glaring gap is the lack of a true, sovereign, enterprise-ready cloud solution. We need a “Canadian AWS” equivalent. This is not about vanity—it is about economic survival, data sovereignty, and security, especially when dealing with sensitive information (PII or corporate trade secrets). Currently, US legislation like the Patriot Act allows the US government to access data stored on US systems globally, posing a major risk to any company handling Canadian data or working with government entities.
Canada possesses significant infrastructure advantages we must capitalize on now:
Cheap Compute and Power: Canada has inexpensive electricity (hydro/nuclear) and a climate suitable for cheap cooling in northern data centres. If Canada became known as the cheapest and easiest place to run AI models, it would be a substantial competitive advantage.
Open Source Foundation Models: We must fund research institutions like Mila to publish the first truly competitive Canadian open-source foundation model. This model, hosted and owned domestically, would provide a secure alternative to the OpenAI API for corporate fine-tuning and specialized application development.
3. Sector Readiness: Targeting Bureaucracy and National Needs
Which Canadian sector is most ready for AI adoption? It might not be the most obvious one, but rather the area where administrative inefficiency creates the greatest drag on our economy: Government Bureaucracy.
Administrative Streamlining: AI can revolutionize administrative processes, from municipal permitting (where getting approval can take over a year in places like Ottawa) to the notoriously slow and convoluted tax remittance process run by the CRA. Streamlining this bureaucracy means reallocating resources (instead of needing 10,000 extra people just to manage inefficient processes).
Barriers: The fundamental blocking factor here is that bureaucracy is the most risk-averse sector and often lacks understanding of AI’s potential.
National Priority Sectors: Other high-impact, ready sectors include Defense/Military (especially for Arctic surveillance and handling data from Canada’s vast landmass) and Resource Management/Mining, where productivity increases could meaningfully increase GDP due to Canada’s mineral wealth. Solving productivity problems in massive national problem spaces, like the housing crisis via construction logistics and permitting, is also essential.
4. Policy: A Wartime Footing for Innovation
The government must adopt a more radical approach to policy, treating this technological race like a “wartime effort”. The slow, restrictive nature of current regulation and investment is choking innovation at the cradle.
To scale globally from Canada, two policy shifts are paramount:
Special Economic Zones (SEZs): We need bold, geographically-focused innovation zones—perhaps in regions like Atlantic Canada, leveraging deep water ports and infrastructure. These SEZs should operate under a “No Parents, No Rules” approach, featuring zero capital gains tax for long-term investments. This is the necessary mechanism to directly unlock VC capital, which currently views Canada as a platform risk and forces companies to incorporate in Delaware.
Mandatory Government AI Spending: The government should mandate that a fixed percentage of every department’s budget be dedicated to investing in Canadian AI solutions to improve internal efficiency. This provides a vital domestic market for startups and generates immediate economic benefits. Furthermore, we suggest this strategic AI expenditure should count toward Canada’s NATO defense spending percentage commitment, recognizing that competence in AI is a modern defense necessity.
5. Procurement and Commercialization: Turning Prototypes into Products
The pathway from prototype to commercial product in Canada is needlessly difficult. The current government procurement process, exemplified by programs like Innovation Solutions Canada, is plagued by cancelled budgets and red tape, stifling critical iteration speed.
Procurement Reform: Streamline government purchasing and introduce Canadian preference policies for AI solutions. Entrepreneurs are primarily seeking fast feedback loops and iteration, not massive contracts—even sandboxing solutions within government departments would be invaluable.
Commercialization Tax Credits: We must extend or augment mechanisms like the SR&ED tax credit to support market validation and de-risking the prototype-to-product transition. Currently, capital flows too easily toward foundational research but stalls when commercial scale is required.
Incentivizing Domestic Capital: We need mechanisms to heavily incentivize angel and venture capital investment in Canadian startups, thereby countering the continuous pressure to incorporate offshore.
Canada has the talent and the foundational research. Now, we need the national ambition and the policy frameworks to execute at scale and speed. This is our opportunity to build the strongest economy in the G7—but only if we act like it.
Key Contributors to this article based on an extensive roundtable discussion with over 15 AI founders based in Ottawa: Rami Alhamad, Hai Nghiem, Brandon Hynes, Chris Bartholomew, and Aaron Gould.
We hope this inspires the Canadian government and other cities to host roundtables and gather more insights from the grassroots and the founders in the trenches currently working in AI.
This article comes at the perfect time! You totaly nailed the challanges, that brain drain is such a worldwide problem, not just Canada’s.