Catherine Fortin LeFaivre is vice-president, strategic policy and global partnerships at the Canadian Chamber of Commerce. Ulrike Bahr-Gedalia is senior director, digital economy, technology and innovation at the Canadian Chamber of Commerce.
Canadian government officials often describe our nation as being a “global leader in AI.” In fact, it’s more accurate to say that Canada is a leader in artificial intelligence (AI) research, but a laggard in AI adoption. Our strength in AI has unfortunately not translated into high rates of adoption and recent statistics make clear that we’re trailing behind peers like the United States and the European Union.
Given that we’re facing a productivity “emergency” – the exact word used by Carolyn Rogers, the Bank of Canada’s senior deputy governor, in a March speech – it’s become a policy imperative to prioritize tangible productivity enablers, AI included.
A string of recent reports speak to AI’s potential, including Accenture’s forecast in a June report conducted for Microsoft that by 2030, generative AI could boost labour productivity in Canada by 8 per cent and deliver $180-billion per year in productivity benefits. Additionally, the Canadian Chamber of Commerce’s Business Data Lab said in a May report that generative AI has the potential to overcome historical business investment barriers, such as financial resources.
It’s no surprise that AI adoption and its productivity potential was a dominant theme at a recent gathering of AI leaders in New York. Participants, who hailed from business, academia, civil society and government, convened to discuss how Canada could leverage its 2025 Group of Seven presidency to demonstrate leadership on AI policy and ultimately enhance economic growth through responsible AI adoption. A few key points emerged.
First, we need to stop talking about “AI” generally. Different types of AI, as well as the context or sector in which this AI is being used and its respective risk factor, need to be evaluated. The very mundane, more traditional AI deserves much less legislative consideration than generative AI, or even the very futuristic “frontier” AI models. As we debate adoption benefits, risks and related governance needs, it’s become unhelpful to lump all AI into the same category. Is this AI used to recommend movies, to make hiring decisions, or to deploy weapons systems? As society engages in AI discussions, being precise is important.
Second, we need to recognize that the hype era around everything AI is dying down, making room for more pragmatic conversations about managing risks and incentivizing beneficial adoption. Such discussions are critical at a time when there is much concern that Canada’s proposed Artificial Intelligence and Data Act (AIDA) would undercut AI adoption and related productivity gains. Businesses of all sizes have expressed concern that AIDA regulates the technology too generally instead of regulating AI where there is risk of significant harm. The proposed legislation also sets out one of the broadest and most prescriptive regulatory frameworks within the 38 Organization for Economic Co-operation and Development (OECD) countries and lacks interoperability with the approach of other key G7 countries.
There’s also concern about the impact that AIDA could have on our relationship with key trading partners such as the United States, at a time when we would be wise to enable North American business opportunities rather than introducing more barriers.
Third, we need much more awareness and public education among Canadians around the use and benefits of AI. If Canada is to reap the benefits of AI adoption to make productivity strides, building trust and understanding of AI is critical. Demonstrations of useful and low-risk use cases is a helpful start.
With the world’s eyes on Canada at next June’s G7 Leaders Summit in Kananaskis, Alta., we have an opportunity to show that Canada is taking meaningful steps to propel productivity by proposing specific, targeted measures that will allow for greater AI adoption, move beyond the hype to the pragmatic, and build public trust around low-risk AI usage in sectors that could benefit the most – think construction, agriculture and transportation.
The result could be living up to our global AI leadership ambitions, with resulting productivity benefits and economic growth that raises Canadians’ standard of living, all while making us a leader instead of a laggard.