The artificial intelligence boom presents Canada with unique opportunities and risks as we seek to benefit from a technology that could reshape how we live.

In this special series, Canada’s AI Advantage, The Logic examines how Canadian companies, investors, institutions and workers can gain from the country’s early lead in AI, even as Canada’s pioneers in the field become the world’s most powerful voices of caution.

Deon Nicholas was in high school when he was initiated into Canada’s emerging AI industry. It started with back-to-back summer internships at the renowned Alberta Machine Intelligence Institute (Amii). There, Nicholas worked alongside some of the world’s greatest AI thinkers, including Richard Sutton, known as the godfather of reinforcement learning, whose research laid the foundation for technologies like ChatGPT. 

After that first internship in 2010, Nicholas—who said he barely knew what AI was before—was hooked on machine learning. He went on to study computer science and math at the University of Waterloo, and worked on AI projects off the side of his desk. He took online courses outside the university on natural language processing, and co-authored an academic paper with researchers back at Amii. 

Despite his early exposure to Canada’s AI pipeline, when it came time to start his own company, Nicholas opted to launch it in San Francisco—pulled into the Bay Area orbit surrounding Big Tech. “I didn’t actually think about going anywhere else,” said Nicholas, now the co-founder and CEO of venture-backed generative AI startup Forethought. 

Nicholas is among the sprawling network of global AI experts whose careers began in Canada, many of them getting their start at one of the country’s three AI institutes, which—along with Amii in Edmonton—include the Vector Institute in Toronto and Mila in Montreal.

This hotbed of talent—much of it developed under the supervision of world-class AI researchers including Sutton, Geoffrey Hinton and Yoshua Bengio—has helped establish Canada as a global leader in the sector. Over 4,000 people in the country enrolled in or graduated from AI programs in 2022–23, according to a recent Deloitte Canada report, ranking it first among G7 nations in the number of AI research publications per capita that year. “Of the world’s most elite AI researchers (i.e., the top 0.5 per cent),” the report reads, “six per cent call Canada home.” 

In the past year, however, following the launch of ChatGPT, competition for this talent has become fierce. Job postings on LinkedIn that mention AI or generative AI more than doubled globally between July 2021 and July 2023. Big Tech companies offer hundreds of thousands of dollars for AI engineer jobs, while a product manager at Netflix could earn up to US$900,000 a year. Amazon plans to train two million people globally by 2025 through its “AI Ready” program, after an AWS survey found that while 73 per cent of employers said hiring AI workers was a priority, almost three-quarters of those employers said they can’t find the AI-related talent they need. The Biden administration plans to bolster Washington’s “data and technology strategies” through a “government-wide AI talent surge.” 

As more companies, investors and governments outside Canada funnel massive resources into the sector, the country is at more risk than ever of losing its homegrown talent. 

“A lot of U.S. companies are really willing to invest and go hard in the area,” said Amii CEO Cam Linke. “A lot of that talent that wants to build big, interesting things is evaluating whether or not Canada is the place that they can do that.” 

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Brain drain is of course not unique to Canada’s AI sector. The country’s robust research institutions have generated large talent pools in STEM (science, technology, engineering and mathematics) fields in particular. After earning an education and research experience in Canada, some of that talent inevitably moves south, where there tends to be a greater abundance of high-paying jobs. 

The dynamic often leaves Canadian companies scrambling for the very talent the country’s universities trained. 

But the consequences for Canada of losing its AI talent are potentially more severe than with other industries. AI promises to transform virtually every aspect of the economy and society—from education, to health care, to law and transportation. “If we are not attracting talent, developing talent, our companies are not going to be able to be good adopters of this technology,” said Salim Teja, a partner at Toronto-based AI venture capital firm Radical Ventures. “And our innovators are not going to have access to the talent that they need.” 

Nicholas said he was drawn to Silicon Valley after working two co-op placements as an undergraduate student there—the first with Facebook and later at the data-analytics giant Palantir. The prestige of those firms and generous wages made them hard for Nicholas to resist. When he began thinking of starting his own company—having by then established a peer network in the Valley—San Francisco was an obvious choice. “One of the things I found about the Bay Area was that the network, that connectivity, and the culture of people starting companies is unparalleled,” he said. 

Since launching Forethought, which uses generative AI for customer service, in 2018, Nicholas has recruited other Canadians to work for him. The company has hired University of Waterloo co-op students and graduates, sponsoring visas to relocate some of them to the U.S. It also has a partnership with Amii to collaborate on research and access talent to help fill jobs at Forethought.

Nicholas said he’s keen to hire more remote workers based in Canada. It means he can pay lower salaries than what’s typical in Silicon Valley, and he hopes it will help him qualify for Canada’s flagship research incentive, the scientific research and economic development tax credit. 

Chris Welsh, founder and partner at the Toronto-based staffing and recruiting firm People Machine, told The Logic that companies can hire two employees in Toronto for the price of one in Silicon Valley, when including the exchange rate. 

While earning a handsome salary is important for AI professionals, they’re also driven to work on exciting new technologies, and opportunities that give them purpose. There are growing opportunities in AI aimed at tackling issues related to climate change and the health-care industry, Welsh said. People want to “feel like they’re making society better, as opposed to just selling more product.”

At Toronto-based Promise Robotics, many applicants are drawn to the company’s mission to help solve the housing and climate crisis, according to co-founder and CEO Ramtin Attar. The two-year-old software company uses AI to train robots to build energy-efficient houses through processes that cut back on material waste. Since raising close to $21 million in October, Attar said Promise has had a flood of job applications. But the company—which Attar said has grown its workforce by 200 per cent since May—has still found recruiting for senior AI experts challenging. “Either, as a startup, you cannot afford it in the early days,” he said, “or they’re just more comfortable on the research side.” 

The excitement that ChatGPT has created around large language models (LLM) is another obstacle for Promise, said Attar, with some applicants dropping out of the hiring process in favour of jobs that focus on LLMs. 

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That’s not to say Canada hasn’t tried to get ahead of the AI talent wars. In 2017, Ottawa launched the Pan-Canadian AI Strategy, a core focus of which was to attract, train and retain AI talent. The federal government selected the Canadian Institute for Advanced Research (CIFAR) to lead the talent part of the strategy, arming the think tank with over $200 million for the initiative. CIFAR’s strategy centres on appointing research chairs to Canada’s three AI institutes. It’s sponsored 122 chairs since 2018, and in 2023 alone, 254 students supervised by those chairs graduated from master’s, PhD or postdoctoral programs. 

While generous salaries and prestigious work with tech giants may lure some of this talent to the U.S., there’s some indication the volume of Canadian AI talent staying at home has actually been increasing. According to Deloitte Canada’s recent AI report, the vast majority—about 92 per cent since 2018—of AI master’s program graduates affiliated with the Vector Institute in Toronto stay in Ontario after graduation. 

Canada’s big banks, for instance, rely on talent from academic institutions and research organizations when recruiting. Foteini Agrafioti, head of RBC’s research centre, Borealis AI, said the centre understands the “value, thought leadership and information” they bring and is focused on strengthening relationships with them, including CIFAR and the Vector Institute, as well as other accelerators and organizations in the Canadian AI ecosystem. (RBC was recently recognized for outpacing its global banking peers in AI adoption, by the Evident AI Index.) Similarly, National Bank has numerous partnerships with universities and research centres, such as the Montreal-based Institute for Data Valorization, as a way to attract AI expertise. 

Teja warned against getting comfortable with rosy talent numbers. “The danger we have is, if we all feel like our mission is done, we’ll lose our stature globally,” he said, “because other regions and other countries around the world are equally as focused on ramping up their talent-development initiatives.” 

Retention rates also don’t necessarily mean these AI employees are all working for Canadian firms. The rise of remote work has created opportunities for Canadians to take U.S. jobs without relocating. Other U.S. companies have set up offices in Canada to take advantage of local talent. Unilever, for example, this month launched its global AI lab in Toronto. The London-based consumer-goods giant said in a press release that it chose the city because of its “concentration of AI expertise.” 

Canadian companies’ cautious adoption of the technology doesn’t bode well for local talent, either, said Teja. “If we’re creating a talent engine, and then there’s no receptors for all of the talent that we’re trying to scale, they’re going to go elsewhere.”

That could change as Canada’s AI ecosystem matures, opening the door to bigger opportunities and salaries that can better compete with global firms. A growing cohort of AI startups and scale-ups in Canada could serve as landing pads for talent coming out of the country’s research institutions. Attar said Promise, for instance, has hired exclusively from Canada’s talent pool, given the immense interest to work for a domestic AI company. 

“As more and more of our companies are getting into the Series B and Series C stages of their growth, their talent demands are much higher,” said Teja, whose fund, Radical Ventures, backs some of Canada’s most promising AI startups, including Promise, Cohere—which develops LLMs for business applications—and the autonomous-truck company Waabi. Some of those firms, said Teja, are hiring aggressively. 

For Canada to keep its AI lead, said Linke, policymakers need to be far more ambitious. “If we really want to win at the talent piece, if we want to win in this overall, we need to stop thinking about [being] 10 per cent better.” Rather, Canada should aim to increase AI jobs and the talent to fill them tenfold, he said. “That’s how we get to global scale and global impact.”