Good afternoon, Mr. Chair and members of the committee. Thank you for the invitation. I'm very grateful for the opportunity to discuss AI policy issues with you here today.
My name is Laurent Carbonneau. I'm here today as the director of policy and research at the Council of Canadian Innovators, or CCI.
CCI is a national business council representing 150 of Canada's leading technology companies. We are dedicated to advocating for policies that promote innovation, economic growth and long-term prosperity for all Canadians. Our member companies are all headquartered here in Canada. They employ north of 52,000 employees across the country and are market leaders in the sectors of health, clean and financial technologies, cybersecurity, and of course AI.
AI will be a defining challenge of our time for policy-makers. A new, genuinely general-purpose family of technologies like AI could well have impacts on the world of work and the economy like those created by industrialization and electrification. I'll stress here that those transitions posed profoundly difficult policy challenges to governments, challenges that many were not able to meet equitably. It is good that this issue is getting active parliamentary scrutiny.
With that said, I think it is very premature to worry about things like large-scale job losses. Canadian businesses as a whole are facing the opposite problem—low productivity and an immense appetite for more labour. This is not normal for advanced economies. We should take a quick look under the hood of Canada's overall economic picture.
In terms of productivity—GDP per hour worked, by one measure—we recently clocked in under the OECD average, just behind Italy and just ahead of Turkey and Spain. We look much worse than they do on measures of work-life balance, where we're tied at 30th with the United States for leisure time, once again below the OECD average. Our net income, which counts taxes paid and services like health care received, has us 13th in the world, behind rich countries like the U.S. but also behind small economies like Belgium.
Canadians are working a lot to earn modest incomes even after accounting for services like health care and education. According to recent Statistics Canada data, productivity has actually just dipped below where it was at the same point in 2018. There's been no growth over the last five years. There's no getting around the fact that addressing the big challenges of our time—poverty, climate change and reconciliation, to name a few—requires us to be a richer and more productive country than we are now, and to do more with the same or fewer resources.
AI is fundamentally a family of technologies that makes both labour and capital inputs more efficient. Research, development, commercialization and adoption of AI collectively present an important opportunity for Canada to correct our worrying economic trajectory. We should work to make it a priority to adopt AI technologies that make our businesses more efficient and our economy better off overall.
What is important to understand about the economics of AI is that while AI is a novel technology, it does not defy the general way in which the economics of innovations work. Companies that are commercializing new innovations, particularly in information technology, succeed because they own intangible assets like patents that exclude rivals, they control vast amounts of data, and they leverage network effects to make their products and services more useful to users. Because of those fundamental drivers of success, today's innovation economy is characterized by superstar firms equipped with the IP assets, data and networks they need to fend off competitors.
AI is a heavily IP- and data-dependent business. The successful AI-driven businesses of the near future will replicate that winner-take-most pattern. Policy-makers focused on creating lasting and inclusive prosperity should prioritize growing Canadian competitors into global champions and leveraging their success into broad-based gains for the country.
The broad AI sector is currently valued at around $200 billion, and by 2030 will likely expand to around $2 trillion. Canada is well positioned in the industry in terms of highly qualified personnel and leading research, but Canadian companies face significant barriers while scaling. A lack of scaling Canadian companies means that many of the benefits created from public investment and research and training, including intellectual property, are accruing to firms outside of Canada.
For example, nearly 75% of intellectual property rights, including patents, generated through the federal government's pan-Canadian AI strategy are owned by foreign entities, including American tech giants like Uber, Meta and Alphabet.
The Scale AI global innovation cluster recently published a report that identifies barriers to adoption for Canadian companies. Companies face serious issues of access to top talent, despite our impressive research strength, because of lower wages compared with American competitors, among other issues. Canada's AI talent pool has actually shrunk by nearly 20% over the last three years. This is showing up in low rates of adoption: 48% of Canadian companies report not using AI compared with below 36% in the U.S., 38% in the U.K., and nearly 39% in France.
It's still unclear what AI will mean for the future of work and broad employment patterns, but one thing that is most immediately clear is that in a potentially era-defining niche in a winner-take-most sector, Canada cannot afford to move into the future as a late adopter of AI with little domestic capacity. That is a recipe for stagnation. Canada's innovators want to build the next generation of global AI players here in Canada.
I look forward to your questions.