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In June, Canada released its national AI strategy, AI for All, and it does not think small. One number jumped out at me. Business adoption sits at 12% today. The target is 60% by 2034. I&#8217;m Ozge Yeloglu, VP of Advanced Analytics and AI at CIBC. With me are Jaime Tatis, CIBC&#8217;s Chief Data and AI Officer, and Glenda Crisp, President and CEO of the Vector Institute.
Jaime, Glenda, thank you for being here.
Let&#8217;s start with where we actually are. When we look at Canada&#8217;s AI landscape today, what feels genuinely different from even a few years ago, and what could the ecosystem look like in the next five years? Glenda, maybe we start with you.
Glenda Crisp, President and CEO, Vector Institute: Thanks for having us.
So look, I would say I think pretty much everything is different. You know, whether you&#8217;re looking at geopolitical situation, tariffs or the pace at which AI is advancing itself. I think what is different though is that as Canadians, we&#8217;ve really sharpened our focus on sovereignty. We&#8217;re really paying attention to buy Made in Canada solutions if you will, which I think bodes really well for our ecosystem.
I also think if you look at the national AI strategy and I carry around a copy with me every day, it&#8217;s very much balanced. So it still is looking to maintain our lead in research, but there&#8217;s a definite shift towards adoption and deployment for the benefit of all Canadians. And so that&#8217;s a very different lens than the original pan-Canadian AI strategy from nine and a half years ago.
Ozge Yeloglu, VP of Advanced Analytics and AI, CIBC: Which I&#8217;m very happy to see, frankly, because having friends in startup environments and entrepreneurship, that&#8217;s what we&#8217;ve been talking about for years here, saying like the great research talent and everything, why can&#8217;t we, why can&#8217;t we adopt? Why can&#8217;t we grow? And so on and so forth. So I&#8217;m actually very excited and happy to see that.
Glenda Crisp: So you&#8217;ll see in that strategy, there&#8217;s a lot of programs, whether it&#8217;s the missions based programs that the government&#8217;s going to launch. And I know health is their first one, but there&#8217;s also commercialization programs that they run through the three national AI institutes. So you&#8217;ll see a continuation of that.
But you asked me what&#8217;s my, like, what do I think we&#8217;re going to look like in five years? And I don&#8217;t actually think I can answer that because I don&#8217;t think my imagination is wild enough, to be honest.
But my hope, my hope for Canada would be that not only do we continue to lead in AI research, but I really hope we lead the world in really deploying AI and adopting AI in a way that is safe and ethical and benefits all Canadians, right? So you see that societal impact. And I think there&#8217;s an economic benefit if we do that.
So we did some research a year ago with Deloitte to look at how has AI added to our economy so far. And over the last five years, it&#8217;s added $80 to $100 billion in GDP and the projection is the next decade, another $298 billion and an increase in productivity. But that depends on all of us kind of getting on board and driving that adoption.
And so the government&#8217;s target of a 60% adoption is ambitious, is aggressive, but I&#8217;ll quote one of our researchers at Vector, Raul Krishnan, and he&#8217;s basically saying ambition is not optional.
Ozge Yeloglu: I love it. Jaime, anything you would like to add?
Jaime Tatis, Chief Data and AI Officer, CIBC: Of course. So I&#8217;m equally excited. As Glenda mentioned, in order to go from 12 to 60%, there&#8217;s many things that need to happen. Adoption has to increase. And I find we&#8217;re at a very much pivotal moment where, yes, we have very good experienced research in the country, but we need to get faster, better, more aggressively going at how we translate research into enterprise, into startups, into companies who are going to be able to provide services that not only stay in the country, but they go overseas as well.
We have great examples of many companies that already are getting quite big and doing great work on IP that they created in Canada. These companies are headquartered in Canada and they serve different industries and sectors globally. When you look in the next five years, there&#8217;s so much room to grow.
So this is both industry and government working hand in hand on how we actually can increase adoption and be able to move to a future that is going to be far more effective. And that includes from government services, how we administer health, how we do financial services. There&#8217;s many sectors here, and the more we take advantage of it, the bigger edge it&#8217;s going to give us. For the wellbeing of all the Canadians. If our GDP grows, if our industries are healthy, the only benefit that is going to create is for all of us in this country.
Ozge Yeloglu: True, true. And what do you think about the future?
Jaime Tatis: So when I look into the next five years, I find when it comes to technology, it&#8217;s very hard to predict five years. Even if you look back now, in time in 2021, you take a, time travelling machine and you get now you will be surprised how much you have seen so far. So based on the last five years, I will say two things.
One is there&#8217;s many things that we don&#8217;t know yet how they&#8217;re going to look like because technology is advancing at a rapid pace. But one of the things that we need to also be mindful is regardless of the technology transformation that is happening, being able as a country, as an industry to adapt quicker and faster on how we leverage these best new technologies in order to move ahead, understanding what opportunities we have, what industries we can create, how can we take that research, move it into practice?
If you look at right now, there&#8217;s many, you know, AI companies that are already established. There&#8217;s some quantum ones that are starting, but quantum is at the early stages. So how we actually can take the moment to establish a very good footprint, that we go research into practicality and be able to be a powerhouse when it comes to quantum.
Glenda Crisp: Yeah, yeah. Like if I could just add on that, I tell people that AI is not your last tech shift. True. Right? So as much as we find this disruptive, it&#8217;s not the last one. And because AI is now in all parts of science, I think quantum computing is going to come out as faster. New drug discovery is going to come out as faster. Health practices, right?
So we all need to be working on a mindset of curiosity and figuring out how to adapt, because the pace of change, as much as we want to hit the pause button, it&#8217;s not possible. It&#8217;s going to continue to increase.
Ozge Yeloglu: Absolutely. For companies, I think it goes back to the change management practices and how much more important it&#8217;s becoming because to your point is not just AI, it&#8217;s probably the only the beginning. And yes, we&#8217;ve seen transformational technologies before, but the adoption and the way that they made into our lives, which was much more slower than what&#8217;s happening right now and what will continue to happen to your point.
So how do you make sure that our people are used to it?
So, Glenda, research strength, it&#8217;s settled. We know we&#8217;re good. Holding on to it is hard and the harder part most likely. So our researchers here in Canada are being recruited globally, and discoveries made in Canada can end up commercialised somewhere else. We have seen this over and over in the past and now as well. What has to change for more of that value? The people and the companies to stay here in Canada?
Glenda Crisp: So you&#8217;re absolutely right from a talent perspective. So Canada&#8217;s CIFAR AI chairs, of which there are, I think 41 at Vector, that group of chairs across Canada is a top three global talent pool in terms of publishing research results. And so it&#8217;s not just the publication of papers, it&#8217;s the fact that they get cited. So their inventions get built on by other scientists around the world. So we have that talent pool. And then I think just last week it was that Toronto was ranked as like one of the top third tech talent pools in North America. So beyond the research, we have this this amazing talent pool just in general.
So I think there are two things that are critically urgent to retain. The first is compute. So when I look at when Vector started nine and a half years ago, the first CEO did all the heavy lifting, built out this amazing world class compute. Obviously that compute is out of date, right? And so we&#8217;ve not kept pace as a country in terms of the compute, and that is impacting our ability to retain researchers. So I know that researchers are getting offers from other institutes where they&#8217;re given access, like part of the offer is we&#8217;ll give you access to a supercomputer. Okay. And so how do I compete with that, right? So we need to get faster at deployment of compute. And it&#8217;s not just on the research side. It&#8217;s also making that accessible to our small and medium businesses, to our startups and scale ups at an affordable price point. So compute is a big part of the answer.
So I think the second thing we need is capital. And I&#8217;ll borrow a phrase from Cam Linke, who&#8217;s the President and CEO at Amii, the National AI Institute in Edmonton. And he talks about visible capital. This means to researchers, to founders that it&#8217;s easy to get a hold of seed funding, that it&#8217;s easy to get a hold of scale up funding, because certainly the US makes it very easy, right? And so that ability to get access to capital is key.
This really boils down to opportunity. Do our researchers and our founders see opportunities here in Canada? Meaning do I have the compute to do my research? Do I have the compute to build my small business? Do I have the capital to commercialise my invention? Do I have the capital to scale up my company? And so for me, there&#8217;s there&#8217;s lots of things we need, but compute and capital are the two most urgent.
Ozge Yeloglu: And how much of it do you think is on our government versus our private companies? Citizens?
Glenda Crisp: Look, I think there is a role for all of us to play, and certainly in the national AI strategy, they do call out a $500 million tech growth fund. So it&#8217;ll be interesting to see how that gets built up and deployed. Mila and Innovia announced the Venture Scientist fund, which I believe will help. But we need more of that. There can&#8217;t just be one fund and we need all players in the ecosystem really coming in and working together to try and move and move faster, like speed is critical here and we just need to be faster at all of this.
Ozge Yeloglu: I hear you. Jaime. CIBC has been putting AI to work in the business since let&#8217;s say 90s. Whether it&#8217;s our risk modelling approaches, marketing fraud. So this is not necessarily a new arrival for our bank. How are you thinking about this national moment and what&#8217;s the approach that got you here?
Jaime Tatis: Of course. So, the bank has many other industries as well. It&#8217;s been doing, you know, data analytics, machine learning for a long time. If I look at CIBC, there&#8217;s a long, strong history of innovation. There is leadership on the machine learning space. There&#8217;s hundreds of models running across the bank. The opportunity right now is acceleration. And the acceleration comes from different factors.
One of the main things that we&#8217;ve been able to do to get the adoption that we want is to have champions across the business who can work with their teams to ensure that they understand what are the capabilities the platforms have, or working with our HR partners to ensure we have the educational training required to ensure people feel comfortable using these tools and very importantly is to have the curiosity and open minded way to look at how their work is done today, and how this technology can shift to elevate it and be able to help them in their day to day job.
The other thing we have noticed is we had really good success when we combine expertise through different fields. So you have people that are very business savvy, coupled with software developers and AI experts who actually can work together, combine that knowledge to actually create the best products and solutions that they can come up with.
On the view for researchers and access to compute. I just want to echo Glenda&#8217;s words like researchers are always going to gravitate where they have the tooling, they compute the problems that they want to solve. So they are attracted to being solving like just the hardest problems that they can find. And to solve them, they need to ensure they have the infrastructure, they have all the compute power that they need for that. So we need to ensure there&#8217;s always a reason there that they want to be there because there&#8217;s good problems to solve and they have the compute facilities in order to do this.
I find that we have to double down on how we make research that is really applied. So having researchers working in problems that are very real, that there&#8217;s a very short duration from that research, to be applying to a business is what is going to make us win. That way, we&#8217;re going to be able to see that on the figures that we&#8217;re expecting, like GDP growth. We&#8217;re going to have acceleration of all the talent diversity that we&#8217;re going to get because that attracts more talent. So when you look at all the researchers, many of them are going to whatever geography can provide this for them. So if you want to attract more talent, then you&#8217;re going to have to have good research that comes out of the country. You want to ensure that they see a value that they will get by being here.
Ozge Yeloglu: Yeah. And my experience on researchers and the business values that we will and we are creating with that is what I also find that this whole little bit of, not a new concept, but the new way of integrating researchers into our businesses in a more applied way that I find that gap is closing very fast. And it&#8217;s really good, because now research is not sitting outside of business, so to speak, and working on the ten year far ahead problems, but they are sitting right next to the business partners and really understanding what is it that we can&#8217;t solve today, but we really need to solve it in the next 6 to 12 months, knowing that we can do this in-house. It&#8217;s still that curiosity, bringing that researcher perspective, thinking differently, but creating more immediate business value and outcomes that we have done before.
And I love it.
Glenda Crisp: Yeah, certainly one of the perspectives at Vector is that that there used to be a very distinct line between research and implementation, right? And we&#8217;ve seen that line. It&#8217;s very blurred. And so the idea that there&#8217;s applied research and foundational research like that&#8217;s becoming closer and closer, and certainly something that we do is work on taking those research papers and saying, how do I create a code base out of that that our industry companies can actually accelerate, right? Now, I can&#8217;t do that with thousands of papers, but I can do that with a few key ones every year. But yeah, it&#8217;s that speed to implementation that&#8217;s key.
Ozge Yeloglu: Absolutely. The research is world class, that part we have. Putting it to work and keeping the value here at home, that&#8217;s the homework that we all have. And nobody is doing that homework alone.

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CIBC × Vector: Canada’s AI Moment: From 12% adoption to a $298B opportunity — what has to change

CIBC × Vector: Canada’s AI Moment: From 12% adoption to a $298B opportunity — what has to change

CIBC × Vector: Canada’s AI Moment: From 12% adoption to a $298B opportunity — what has to change

CIBC × Vector: Canada’s AI Moment: From 12% adoption to a $298B opportunity — what has to change

Jaime Tatis

Executive Vice-President, Chief Data and AI Officer

Global Technology, Data and AI

Ozge Yeloglu

Vice-President, Advanced Analytics & Artificial Intelligence

Global Technology, Data and AI