Industry and Technology Committee on April 13th, 2026

[Michel Richer, Senior Vice-President, Enterprise Solutions, Data Engineering and AI, Bell Canada]

Thank you, Mr. Chair and members of the committee.

Canada is at an inflection point. Artificial intelligence is moving rapidly from the research stage into the very core of our economy. It is reshaping how we build, produce, serve customers and compete globally.

The question before this committee is not whether AI will transform Canada’s strategic industries, but whether Canada will shape that transformation or allow it to be shaped elsewhere.

Bell believes Canada has a real opportunity to lead. Not only can it contribute to research, but it can also deploy AI at scale to strengthen productivity, competitiveness and economic sovereignty. Achieving that depends on trusted infrastructure, practical adoption, and clear authority over the systems Canadians rely on.

For Bell, AI sovereignty is operational. It depends on who controls the compute, where data is stored, how it moves across networks and who has the authority to operate or shut down critical systems.

Bell’s networks already form part of Canada’s digital backbone, supporting businesses, governments and public safety nationwide. Building on that foundation, we are investing in Bell AI Fabric, Canada’s largest AI compute project.

Bell AI Fabric brings together sovereign compute capacity, Canadian data centres, national fibre connectivity and telco-grade cybersecurity. Bell is deploying capacity across several provinces with multiple facilities already in operation and additional sites under development. This national footprint avoids single-point dependencies and allows AI capacity to scale with Canada’s needs.

Bell is fully funding this new sovereign AI infrastructure, demonstrating our long-term commitment to building critical AI capacity in Canada. Beyond technology, this infrastructure delivers real economic benefits. AI data centres drive construction activity and long-term skilled jobs. They create opportunities for local suppliers, workforce development and partnerships with indigenous communities, universities, and research institutions, helping anchor high-value economic activity in communities across Canada.

For Bell AI Fabric, the goal is to give governments, researchers and businesses access to AI infrastructure powerful enough for enterprise-scale adoption while ensuring that data, models and operational authority remain in Canada. This foundation is essential if AI is to improve productivity and competitiveness across Canada's strategic industries while supporting our economic sovereignty and security.

On adoption and commercialization, the global AI race is about embedding AI into real operations—factories, logistics networks, call centres, farms, health systems and public services. Bell helps enterprises and governments move from pilots to production, using AI to automate workflows, improve network performance, strengthen cybersecurity and deliver better services.

Bell is also partnering with Canadian AI leaders to ensure that value creation stays in Canada. For example, Bell has partnered with Cohere, a leading Canadian AI company, to deliver full-stack AI solutions that combine Canadian-controlled compute, networks and security with world-class Canadian models. These partnerships help translate Canada's research strength into deployable solutions that can be adopted at scale under Canadian jurisdiction.

AI delivers economic value only when it's used at scale. Organizations, including governments and critical industries, will use AI at scale only if they trust that the infrastructure, data and decision-making remain under Canadian control. From our perspective as an operator of national digital infrastructure and a leading provider of AI-powered enterprise solutions, the role of public policy is to ensure that Canada remains globally competitive and to support responsible deployment. Where AI moves into real operations, productivity improves across sectors. Economic benefits remain in Canada.

In closing, Canada’s AI opportunity is real, but it is time-bound. If Canada wants to lead in the AI economy, we must move now to build and deploy the infrastructure that allows innovation to scale safely, competitively and under Canadian control.

With our unprecedented investments in Bell AI Fabric, Bell is making a robust contribution to the future of AI in Canada.

Thank you.

[The Chair, Liberal, Ben Carr]

Thank you very much, Mr. Richer.

Mr. Madan, the floor is yours for up to five minutes.

[Chris Madan, Vice-President, Digital Product and Head of AI Factories, Telus]

Thank you.

Good afternoon, Mr. Chair, honourable members and fellow panellists. Thank you for the opportunity to appear before this committee on a matter of critical importance to Canada's economic future.

We stand at a decisive inflection point. We possess world-leading AI research and innovation, yet we confront a systemic productivity crisis that has allowed our national growth to stall for decades. We train brilliant minds, engineers and researchers, only to witness them leave because the essential domestic infrastructure required to commercialize their innovation does not exist. Seventy-five per cent of AI patents developed in Canada are owned by foreign entities, and our most valuable talent inevitably follows the computing infrastructure down south.

In today's AI era, compute power is national power, and we cannot adopt AI at scale without the absolute confidence that our proprietary data, operational intelligence and competitive advantages remain under Canadian jurisdiction. This isn't just my belief; this is a message we hear from Canadian entities looking to adopt AI themselves. They want clarity on the Canadian definition of AI sovereignty, and they want consistency in how that definition is used. Data sovereignty is a necessary component, but to be truly sovereign we need full operational control over the infrastructure itself. This includes the facilities, the hardware, the networks, the operations and the data. It means Canadian operational control across every layer and Canadian jurisdiction throughout, limiting foreign control or exposure to extraterritorial laws. We call this sovereign by design, built from the ground up, not retrofitted.

At Telus, we have moved beyond debate and have responded to this national challenge with decisive action. We built Canada's first fully sovereign AI factory, which opened its doors in Rimouski in September 2025. It features Canada's fastest and most powerful supercomputer, bringing the same cutting-edge capabilities that power AI innovation in Silicon Valley right here to Canadian soil. Partnering with the world's leading AI infrastructure provider, Nvidia, we're delivering the world's best technology without compromising sovereignty. Furthermore, our facilities operate in a LEED gold-certified building, powered by 99% renewable energy through Hydro-Québec and exhibiting industry-leading energy efficiency. This infrastructure reflects essential Canadian environmental values, proving that large-scale AI can align with a sustainable, low-carbon future.

Unlike many announcements that have merely announced intentions, we are fully operational today, actively serving Canadian organizations. Telus has been part of—and leading—Canada's AI ecosystem for over a decade now, working with research institutions like Mila, Amii and Vector, and with industry partners, to advance responsible AI adoption. Today, alongside our consortium partners, including leaders like Cohere, we're offering the full stack of AI solutions: the infrastructure, the platforms and the applications that Canadian organizations need to deploy AI at scale while maintaining complete control. This is critical for our industry and our national economic security. Canadian manufacturers can deploy AI without sending data abroad. Researchers can train models here, keeping innovation at home. Health care institutions can leverage AI for patient care without compromising privacy.

As the government works to scale AI adoption across public institutions and to nurture a domestic ecosystem, we must eliminate ambiguity. We need clarity on what “sovereign” truly means, clear definitions that distinguish between data residency and operational control, and procurement standards that prioritize Canadian-controlled infrastructure.

Telus stands ready to partner with the Government of Canada, this committee and Canadian industry to advance this critical infrastructure. We have the talent, the resources and now the infrastructure. We need continued commitment to build and a policy framework that gives businesses the confidence to continue building here, ensuring that Canada owns its AI future and doesn't merely participate in someone else's.

Thank you, Mr. Chair. I look forward to your questions.

[The Chair, Liberal, Ben Carr]

Thank you very much.

Madam Pineau, the floor is yours for five minutes.

[Joëlle Pineau, Chief AI Officer, Cohere Inc.]

Thank you, Mr. Chair.

Mr. Chair and members of the committee, thank you for inviting me to testify today.

My name is Joëlle Pineau. I'm the chief AI officer at Cohere, where I lead the company's product strategy and supervise our research at Cohere Labs. I'm also a professor at McGill University and an academic member of Mila.

I'd like to begin by highlighting the magnitude of the moment we are in.

AI is a fundamental economic shift reminiscent of the massive industrial mobilization of the forties and has rapidly evolved from an academic pursuit into a defining force in national productivity, security and sovereignty, which has taken me from McGill University to being with Cohere today.

Global competition is now nation to nation. Countries are mobilizing defence budgets and strategic investors to back their AI champions. Without actively building sovereign AI capacity, we risk absolute reliance on foreign infrastructure and losing decades of economic benefit.

Canada can anchor its ecosystem with our own values and governance system. Founded in Toronto in 2019, Cohere is Canada's only foundational model lab at global scale today, building large language models that are powering new applications more quickly and cost effectively and placing us among just three other nations—the United States, China and France—with domestic capabilities at this critical layer.

While Canada is a research powerhouse, accounting for 5% of top-tier AI researchers globally, and is leading the G7 in talent growth, we have historically struggled with commercialization.

Canada needs to keep up with its peers. Canada faces a persistent productivity gap, lagging behind some other G7 countries by about 30%. To close this gap, salaries and public services have to improve on a national scale. AI is one concrete way to make a difference. The goal is not only to achieve indirect productivity gains, but also to ensure that Canadian companies capture a significant share of the global revenue generated by this growth.

For our clients, the demand for absolute control over their technology culminates in one vital requirement: digital sovereignty, a central focus of this committee. We view sovereignty as technical guarantees ensuring control, auditability and secure operations. As a trusted sovereign AI partner, our key differentiator is unparalleled deployment, flexibility and security. By deploying our models entirely on premise, customers retain absolute control over their infrastructure and proprietary data without any risk of it even being accessed by Cohere.

Take our partnership with Bell as a concrete example. Cohere's platform is actively running on Bell's AI Fabric to enable secure enterprise-grade AI with complete data control. We're proving that Canadian organizations can adopt AI securely, keeping critical infrastructure within our borders.

Our collaboration with Bell is proof that secure AI deployment nationwide is now possible. To extend this success across the country and address broader challenges related to sovereignty, regulation and labour market disruptions, Canada must take concrete action. To that end, Cohere respectfully submits three recommendations.

First, to ensure data sovereignty, Canada must address infrastructure constraints. Cohere is in favour of a broader national strategy for computing and national AI data infrastructure creation. Key to ensuring sovereignty is having models that reflect Canadian data. If Canada owns and manages the data that defines it, Canadian growth-stage companies and researchers will be able to build world-class, commercially viable models that reflect our language and values rather than relying on foreign infrastructure.

Second, we must adopt a risk-based, sector-specific approach to regulation.

Without a thoughtful regulatory framework, Canada risks falling behind. We urge the government to take a measured and globally consistent approach when focusing on broad policy, while relying on existing sector-specific regulations to manage deployment.

Third, the government must lead by example. The best way to protect workers is not to resist adoption but to steer it.

Ottawa must become the first and best customer of Canadian AI. Setting aggressive public sector adoption goals and launching national upskilling programs will transition our workforce effectively, boost productivity and provide domestic firms with the reference customers need to compete globally.

Cohere is ready to be Canada's partner in sovereign AI.

Thank you for your attention. I would be happy to answer your questions.

[The Chair, Liberal, Ben Carr]

Thank you very much, Ms. Pineau.

Madam Dancho, the floor is yours for six minutes.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

Thank you, Mr. Chair.

Thank you for the opening testimony from our witnesses today. It's great to see Canadian companies doing extraordinary work to ensure data sovereignty and our sovereign AI capacity.

To start off, I have a few questions for Cohere.

Madam Pineau, it's a pleasure to have you here.

As I mentioned, I think Canadians are increasingly concerned about our sovereign capacity and critical industries, AI being an emerging and increasingly critical industry, as you well know. They want us to be self-reliant.

It seems that your company has been billed as sort of the sovereign AI company for Canada to build that future and also for government to be a key customer of yours. In brief, can you highlight for the committee what makes Cohere unique vis-à-vis the others here today and other actors in Canada in supporting Canada's sovereign AI capacity, and why is that specifically important?

[Joëlle Pineau]

Quite frankly, to have sovereignty, you really need to think about the full stack, from the data to the models to the infrastructure and to the regulation. Where Cohere is unique is really at the model layer. The ability to build world-class models today, foundation models that are able to incorporate large amounts of information and use that to drive productivity is where Cohere shines. Today we're one of very few global companies that are able to do that.

Where we are very complementary to other companies appearing today is in terms of partnering with them, for example, for the infrastructure layer. Cohere doesn't necessarily have expertise building its own infrastructure. We partner with companies such as Bell to do that.

The model layer is one that's particularly difficult from a technical point of view. Canada invented the original technology for doing that—deep learning and large language models—and we must preserve the capacity to commercialize it.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

Thank you very much. I appreciate that. I'm glad you brought up infrastructure.

I want to ask you about your work with CoreWeave, an American-owned company. Of course, Cohere received nearly a quarter of a billion dollars of taxpayer funding to expand, I believe, your AI compute capacity. My understanding is that those taxpayer dollars were then invested in CoreWeave, the American company that builds and operates the data centre in Canada.

I'm struggling to square the circle there. Do we not have the capacity to build...? Do we not have a Canadian company that could have done that, and doesn't that impact the sovereign capacity argument based on which you were given that money?

[Joëlle Pineau]

That's a really important question.

At the time we built our cluster, we did a thorough analysis of who had the capabilities to build that. You have to remember that this is a cluster used for research and development of said models. This isn't a cluster that's used to distribute that technology to enterprises.

To build that technology at the time when we did it, there were very few players—none of them Canadian-owned companies—that had the ability to do that. In the future, we are always looking for Canadian partners to build those R and D clusters and will continue to do so. The analysis we had at the time indicated no other option. We were glad that we were able to build a cluster in Canada, developing that capacity locally.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

Thank you.

Do you have any concerns, given that it's American-owned and -operated, about the CLOUD Act? Of course, I'm sure you're very familiar with it. It's the U.S. act that would allow American law enforcement and other security apparatus there to really.... If they deemed that there was a security issue, they could access the data from any American-owned companies. That would fall, of course, under the CLOUD Act, I would imagine. Are you concerned about the security implications of that?

[Joëlle Pineau]

I'm sure you probably have witnesses who have more in-depth knowledge in terms of the interpretation of the CLOUD Act.

That being said, that act doesn't circumvent legal processes in terms of access to data. I understand that Canadians, of course, have a right to own their data, and the Canadian government will continue to govern the use of Canadian data.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

Again, I appreciate that there may be others with better expertise on the CLOUD Act, but I think that specific.... You mentioned that we have jurisdiction over it, but there are some questions of whether that's the case when they're American-owned companies. I think that's why a lot of Canadians support investment in sovereign AI capacity, data centres and the like, but it's certainly something this committee should look more into.

With my remaining time, I want to get one more question in. There was, of course, talk in The Globe and Mail recently about a potential merger between Cohere and a German-owned company. Of course, as I mentioned, Cohere received about a quarter of a billion dollars to build our sovereign capacity. We have some concerns. There were not a lot of details in the article. I'm sure you can't comment on specifics, but can you commit, for this committee today, that Cohere will remain Canadian-owned and headquartered in Canada?

[Joëlle Pineau]

As you suspect, I'm not going to dive into speculation.

What I can certainly assure you of is that Cohere was built in Canada. The founders are Canadian. We have growing teams in Canada. We just opened a team in Montreal, an office that I myself am growing. I am fully confident that Canada will continue to be the home for a lot of the work that Cohere is doing.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

Okay. You can't commit that you'll remain Canadian-owned and Canadian-headquartered, but you would have a presence here regardless of any merger.

[Joëlle Pineau]

It's not my role to comment on this.

[Raquel Dancho, Conservative, Kildonan—St. Paul, MB]

All right. Thank you very much.

I have only 20 seconds left, Mr. Chair, so I'll just give it back to you.

Thank you.

[The Chair, Liberal, Ben Carr]

We'll roll that in. Thank you, Madam Dancho.

Mr. Ma, the floor is yours for six minutes.

[Michael Ma, Liberal, Markham—Unionville, ON]

Thank you, Chair.

Thank you to all the witnesses for being here. My questions are for Cohere.

Ms. Pineau, in your submission to the AI task force, you emphasize that sovereignty is safety, including access to domestic compute, data and models. To what extent does reliance on foreign AI infrastructure increase Canada's exposure to both economic and security risks?

[Joëlle Pineau]

There are a few levels at which that applies. That's why our strategy has been to build this capacity within Canada, with Canadian partners.

First and foremost, this year we've seen how much having the ability to control our own destiny and have the ability to possess all of the stack is really important. In many ways, for me, the hardest of these capacities is building the model itself and having the capacity to do that. Given how there are very few players around the world, that remains very important.

The other point on which I'll insist is on the type of deployment we do. I mentioned these on-premise deployments. That means the model is deployed locally, whether it's with a government agency or a commercial partner. That means the company is running that model locally on-premise. Their own data stays local. It doesn't have to travel to the cloud. As you can imagine, there are many partners who are very interested in this type of set-up and capability.

[Michael Ma, Liberal, Markham—Unionville, ON]

You argue that safety should not be seen as competing with economic progress but rather as a source of competitive advantage.

What does a regulatory framework look like that both builds trust and accelerates innovation?

[Joëlle Pineau]

I'm glad you're picking up on this point.

Often, safety is seen as intention with innovation. We really have to move to a point where we can build models in a way such that safety is built into the model itself, and security is built into the system and how it's deployed. By having that approach, we have the ability to innovate and actually bring value.

We're about to move into a world where security concerns are a real liability for many companies. There are many things that can be done in terms of the model. One of the things is building safety guardrails right into it. Another one is how the models are deployed. Deployments on the premises are what we call “air-gapped”. There is essentially a full layer protecting the data. That and also how the model is used prevent any intruder from seeing that.

In that sense, from a technical governance point of view, there are solutions whereby we can provide some very strong guarantees from a privacy, safety and security standpoint.

[Michael Ma, Liberal, Markham—Unionville, ON]

That's great. Thank you.

You also cautioned against broad and vague regulatory approaches. Instead, you recommend sector-specific, risk-based frameworks.

How important is it for Canada to avoid one-size-fits-all AI regulation in order to remain competitive?

[Joëlle Pineau]

This is an issue we are facing as a company that wants to build here in Canada and of course play a role commercially on the global scale. The ability to have interoperable standards and regulation makes it a lot easier to ensure that we are compliant with regulation.

The challenge, often, isn't that we are afoul of regulation. It's the burden of proving that level of compliance. As much as we can, in fact, be compatible with international standards, it's very much preferable.

The other thing with AI is that in many ways there's been an attempt to regulate the future. We know from many other domains...you can imagine all sorts of things in terms of speculation. The idea of a risk-based framework is that we're actually trying to regulate the technology based on evidence and measurement, which tends to lead to a much better technology and quite likely a better regulatory framework as well.

[Michael Ma, Liberal, Markham—Unionville, ON]

In terms of trust, your memo highlights that public trust in AI in Canada remains relatively low. To what extent is this trust deficit currently acting as a barrier to adoption across businesses and institutions?