It’s boom times for startups building with or atop AI functionality: The Exchange explored the rise in venture capital dollars for AI startups last week, noting that investment into the business niche set all-time records in Q4 2020, and then successively in quarters one, two and three in 2021.
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Given how heated the overall venture capital market is proving to be, those data points were only so surprising. What did shock us a little, however, was how active the Canadian AI startup market has been this year.
Perhaps it shouldn’t have. Matt Cohen, a managing partner at Ripple Ventures, told The Exchange that “while investment in Canadian startups of all varieties has ramped up lately, AI-enabled startups are certainly leading the pack.”
We’re behind, it turns out. But not so far behind that we cannot catch up on the Canadian AI startup story. Our questions are simple: Why are Canadian startups seeing their fundraising fortunes rise so sharply, what parts of the AI stack are being attacked, what role does public money play in the rising investment totals and what impact do local universities have on artificial intelligence work in Canada?
To help us, we parsed a data set from CB Insights and have clarifying notes from Ripple’s Cohen along with Ali Zahid, an investor at Ramen Ventures, Shawn Chance, a partner at OMERS, Bruno Morency, the managing director at Techstars Montréal AI, and Louis Fischer, a CB Insights intelligence analyst.
We’ll start with data, and then talk about what’s pushing up the numbers.
From the land of milk in a bag, rising AI investment
Let’s start from a yearly perspective. Funding for Canadian AI startups rose to record heights in 2019 before seeing declines in 2020 to just $488 million in total funding. But 2021 is proving to be more than a return to form for Canadian AI startups, with some $1.5 billion raised through the third quarter.
The results are a bit uneven, to be fair. Canada saw $895 million across 21 deals in Q2 2021 AI funding, and just $446 million in the third quarter, albeit from a slightly higher deal count of 24. But as the Q3 2021 dollar result for the country is nearly on par with its full-year 2020 total, it’s hard to be too bearish.
The evolution of Canadian AI funding as a portion of all venture capital funding in the country is impressive. AI companies raised 16% of known venture capital funds in 2021 thus far, a huge gain on the mere 2% that they were worth of total dollar volume in 2016.
But don’t think that it’s just huge rounds pushing Canada’s figures up; smaller rounds put points on the board as well. There were just two mega-rounds, or deals worth $100 million or more, in the third quarter, down from four in the second quarter. At the same time, CB Insights data indicates that median round size for Canadian AI startups reached $3 million in 2021, appearing to tie its prior record set back in 2018.
So, more total dollars, with even the smaller rounds seeing their heft rise. Those are more than healthy gains for the country. (For reference, Canadian AI startups had a median deal size of $2 million in 2020, or one-third less.)
Picking a few examples from the mix, QScale in Canada raised a $24 million seed round in the third quarter, the third-largest seed funding event for the startup category globally in the period. The country’s largest AI round in Q3 2021 was Deep Genomics, which collected a $180 million Series C.
More dollars, rising deal sizes. What’s going on in Canada?
Analysis of underlying factors
Let’s start with some notes on chips, public funding and academia.
Public policy tailwinds
The trend of “increasingly larger bets in AI companies” is global, Fischer recalled. But Canada does have an edge in part of the AI market itself. In his opinion, “Canada’s differentiator is in its breakout AI chip market.”
We didn’t hear this from anyone else, but Fischer had data to back up his point: “In 2021,” he pointed out, “three of the country’s six mega-rounds went to AI chip developers Tenstorrent, Untether AI and Xanadu.” Add that up, and “30% of Canada’s total AI investments went to AI chip companies, compared to 10% globally.”
And this isn’t just a 2021 thing, Fischer predicts: “Given the global chip shortage and Canada’s favorable tariff laws on manufacturing inputs, the country has the chance to emerge as an AI chip hot spot.”
Favorable tariff laws are just another example of how Canada’s public policies are having a positive impact on its tech sector — at least according to our sources. While Canadian AI startups benefit from the boom in private funding we are seeing everywhere, public money is also helping, they said.
“Overall, capital — both public and private — is broadly available, so it’s never been easier to start a startup,” Zahid said.
This public funding is more multifaceted than one may think. Sure, there are grants and tax credits for science and research, but “public funding is also a major LP in the majority of seed/Series A VC funds in Canada,” Morency noted. This includes the Venture Capital Action Plan (VCAP), launched in 2013 with the goal to deploy CA$390 million in new capital. And Canada being federal, there are Canadian dollars flowing both from federal and provincial institutions — not to mention pension funds.
AI support
The above is about startups in general, but it is often done in a way that benefits AI, which is also targeted by specific initiatives. For instance, public funding is supporting dedicated research institutions such as Toronto’s Vector Institute for Artificial Intelligence, which Chance, Cohen and Zahid mentioned.
And it is not just Toronto: Montreal-based Scale AI Supercluster, Morency explained, is “a consortium of private entities, research centers, academia and high-potential startups supporting and advancing AI in Canada,” which is “a good example of the government of Canada and Québec investing in a joint initiative.
“Public funding plays a large and important role in the rise of AI in Canada,” Morency said. Why?
“I would guess a key driver is a desire to create the opportunity for that talent to stay and flourish here,” he ventured.
Indeed, there’s a lot of AI talent being formed in and attracted to Canada. “Particularly in Toronto, the talent pool in this area [AI] is extremely rich,” Cohen said. But that doesn’t mean there’s a shortage in other Canadian hubs.
“The leadership of professors such as Doina Precup and Joëlle Pineau at McGill University and Yoshua Bengio at Université de Montréal resulted in a critical mass of world-renowned AI talent in Montréal. The same can be said for Toronto and Edmonton with Geoffrey Hinton and Rich Sutton at the University of Toronto and University of Alberta, respectively,” Morency said — with Chance also name-checking the University of Waterloo and McGill for their “reputable academic focus.”
A feedback loop
As usual with critical masses, it generated “somewhat of a feedback loop,” Zahid said, “where the best researchers wanted to come work in these labs due to their foundational research papers.” This also translates into the entrepreneurship ecosystem’s attractiveness: Morency told TechCrunch that “a majority of applications are coming from startups based outside Canada, with European companies well represented in the alumni group.”
One of the things that caught our attention is how several initiatives are building bridges between research and entrepreneurship. “I would point to organizations such as CDL, DMZ, MaRS and the Vector Institute, among others,” Chance said. “Together, they form the basis for many up-and-coming AI startups.”
With other initiatives aimed at “closing the gap between academia and corporate labs, and financing SMEs to take more risk buying products from AI startups,” as Morency put it, this paints a pretty flattering picture of the Great White North.
“This mix of talent, academic and corporate research leadership, and early-stage venture capital creates a fertile ecosystem for entrepreneurs to build and grow AI companies,” Morency told us. But what kind of companies are they building? Well, this is where the investors we heard from veered quite far from Fischer’s perspective on chips. Instead, they insisted that AI was now being applied to a vast range of industries amid increased demand for automation.
OMERS’ Chance was perhaps the most vocal about it. “Safe to say, AI is touching almost every sector,” he said. “Much like ‘cloud,’ I believe AI is becoming a core technical competency and not a standalone feature.” Forget about standalone AI: It’s applied AI that accounts for the bulk of startups in a variety of sectors. “Startups that have gone through our program since it started in 2018 apply AI in a very wide range of industries such as agriculture, legal, health, pharma, clean energy, fashion, and diversity, just to name a few,” Morency said of Techstars Montréal AI’s program.
Private and public capital driving valuations up
The impact of the wave of capital is higher valuations, which is largely good news for founders. Sure, you don’t want to raise at a price so high that you can’t grow into it, but generally speaking, higher valuations mean lower founder dilution, and that’s not bad.
Connecting more dollars and higher startup prices isn’t just our perspective. Zahid was clear on the matter, connecting “exploding” startup valuations to the “amount of public and private money available per startup [never being] higher.” But they added that as the “terminal values” of startups are also growing, the math can check out. Zahid also thinks that those terminal results push more capital into the startup market.
So what to expect in the coming quarters? The same thing that we’re expecting in myriad startup niches, in a great number of startup hubs: more. More rounds, more dollars, at greater prices. Something will eventually slow the startup game this cycle, but we’re not there yet. Until then, it’s full speed ahead for AI startups — their Canadian cohort in particular.
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