Canadians can be proud of our thriving artificial intelligence (AI) ecosystem.

Built on a foundation of world-class research, the pan-Canadian artificial intelligence strategy, launched in 2017, was designed to build an AI ecosystem that fosters talent and brings together researchers, private-sector partners, startups and venture capital to advance research, training and ultimately to build new AI-based products and services to deliver social and economic benefits for this country.

The strategy, along with the efforts of other key players in the area, is paying off.

Industry adoption and commercialization of AI is still lagging other nations, but Canada’s AI ecosystem has been growing steadily over the last five years, according to a recent report by Deloitte Canada that was commissioned by the Canadian Institute for Advanced Research (CIFAR) and our three national AI institutes.

Early-stage companies come and go, of course, but the Deloitte report estimates there are more than 670 AI startups in Canada with real staying power and a solid trajectory.

That is contributing significantly to the Canadian economy, with more than 140,000 jobs in AI nationwide, the report added. Indeed, Canada ranks second in the world for new hires in AI, according to Stanford University’s global AI vibrancy tool.

This deep pool of individuals with AI skills and expertise enables Canadian companies to integrate AI into their business models. That talent pool is Canada’s most valuable AI resource – one in which we have invested significantly and which pays us back in spades.

But talent can’t thrive in a vacuum. It takes an entire ecosystem approach and a full suite of policy measures and investments to support an economic sector that has the potential to deliver so much for society and the economy.

The missing voices at AI conferences

Series | How should artificial intelligence be regulated?

Towards regulating AI: A natural, labour and capital resources perspective

This is particularly critical to the growth of the AI startup ecosystem, which has been strong over the last decade, as has venture-capital investment. By 2022, more than $8.6 billion in venture capital investment in Canadian AI startups accounted for 30 per cent of all Canadian VC activity.

The success of our startups is a strong indicator of the success of our AI ecosystem. Still, some significant policy gaps need to be addressed to realize the full social and economic benefits of AI.

Canada has a lacklustre track record of private-sector investment in research and development (R&D), innovation and technology adoption.

Technology adoption is not just for large enterprises. There is a real opportunity for policy innovation to incentivize AI adoption by small- and medium-sized enterprises – another area where Canada lags its international peers.

We also need more government funding for early-stage startups because Canadian venture-capital firms cannot afford to maintain the same risk profile as their U.S. counterparts.

While small early-stage funders such as MaRS investment accelerator fund are trying to make a difference, this is a drop in the bucket. Too many early-stage AI startups with high-risk/high-return profiles must knock on the door of U.S. venture capital firms to get funded.

SIGN UP

The inner workings of government

Keep track of who’s doing what to get federal policy made. In The Functionary.

Read it now.

SUBSCRIBE

The Functionary

Our newsletter about the public service. Nominated for a Digital Publishing Award.

Many are successful, but that also means a larger portion of the returns will eventually leave Canada.

While many of our AI startups are doing well, they are not able to make their mark on the global stage without deeper and more strategic investment and targeted government policies.

That means thinking about the whole picture of critical resources, expertise, capital, access to domestic and global markets and a thoughtful regulatory approach that Canadian AI startups need to scale up their businesses and deliver meaningful impact.

Computational power is one of the biggest costs for any AI-based startup. Furthermore, as the global competition heats up for a limited supply of GPUs (graphical processing units, the primary chips used in AI), the ability of Canadian companies and public-sector institutions to access the computing power they need to stay at the leading edge of AI is at risk.

Following the lead of the U.S. and the U.K., other G7 countries have pledged deep investment in computing infrastructure to support their AI ecosystems. Canada must do the same.

The absence of meaningful investment in AI computing infrastructure played a significant role in Canada dropping to fifth position in last year’s global AI index. Without a national AI computing strategy, we run a serious risk of losing our most promising and innovative companies to competing jurisdictions.

Of course, any technology startup needs to protect its most valuable asset – its intellectual property (IP). The good news is that as Canada’s AI ecosystem has grown, so has our patent activity.

There has been a significant increase in AI patents filed by Canadian inventors over the last several years – an indicator of the level of innovation activity within our ecosystem. A detailed analysis of Canada’s AI patenting landscape shows that historically Canadian companies account for the vast majority (82 per cent) of AI patents in this country.

While some of Canada’s largest companies are the biggest drivers of these patents, Canadian AI startups are especially active in protecting their IP through patents. Here, Canada’s national intellectual property strategy is a first step toward making the process faster and easier to navigate for Canadian startups, but there is much more to be done.

Patents don’t tell the whole story of how value is generated in a knowledge-based sector such as AI. Simply filing patents is not enough. It’s what you do with the ideas that counts, and thus we come full circle back to the value of talent.

Great ideas come from talented people working in stimulating environments, where they have the freedom and resources to experiment, and other talented people with whom to collaborate.

Such an environment is a magnet for other leaders in the field and Canada has excelled in top-tier talent attraction, ranking second in the world for positive AI skills migration.

These people are where the true value of our AI ecosystem lies and they bring about a virtuous circle in which strong talent attracts, develops and retains yet more strong talent. With the necessary resources, those talented people take those great ideas and build them into innovative companies such as AltaML, BrainBox, Cohere and Signal1.

What about the many large multinationals that have established dedicated AI R&D labs in Canada? Drawn here by our talent, these investments deliver significant returns to our economy by creating jobs for our highly skilled AI workforce, along with generating tax revenues.

If we can mobilize our strengths – great people with great ideas – and support them with the tools they need to bring their advances to the world, Canada’s brand of responsible AI could become a dominant force shaping the future of this technology. That would be something to celebrate.