SAS Canada’s AI Executive event on Wednesday focused on how Canadian companies can best use AI to drive business outcomes. However, SAS also emphasized data that indicate that to date, that hasn’t been happening in Canada, which lags globally when it comes to adoption in production environments.
TORONTO – When it comes to artificial intelligence [AI], Canada is something of a paradox. On the one hand, the country’s universities are a top source of AI related talent, and there is a lot of research and development activity taking place in Canada. On the other hand, Canadian businesses aren’t really taking advantage of this, as when actual industry deployments are looked at, Canada lags significantly behind international numbers in most aspects of AI use. That was one of the themes of an all-day event on AI here Wednesday, hosted by SAS Canada, which focused on how companies can best combine AI and human intelligence to derive actionable intelligence that impacts business outcomes.
“Canada is recognized as a hotbed of activity and investment in AI R&D,” said Ajay Agrawal, an economics professor at the University of Toronto’s Rotman School of Management, in the event’s opening keynote. When it comes to the generation of talent that’s certainly true. Canadian industries produce more than their fair share of grad students in this area, many of them from the University of Toronto. The Rotman itself is the centre of an AI incubation hothouse with its Creative Destruction Lab, a pre-seed stage start-up program with a heavy emphasis on machine learning. However, most of the individuals that Agrawal cited as exemplars of the Canadian AI and machine learning community are actually Canadian expatriates, who ply their trade in Silicon Valley for companies like Google.
Steve Holder, National Strategy Executive, Analytics and AI, SAS Canada, said that his experience in the Canadian market confirms Canada’s excellence in AI research.
“We are a leader in the research angle, creating AI techniques that will be embedded in solutions within a two to three-year timeframe,” he said. “I see a lot of venture capital in Canada around AI, and a lot of incubators.”
When it comes to the actual adoption of AI in production applications, that’s another story however. Holder presented data to the event from a global study conducted in July 2018 by Forbes Insights and commissioned by SAS, Intel and Accenture. It surveyed 300 C-level executives, mainly at larger organizations, across ten countries. On the key issue of how they characterized the status of their organization’s deployment of AI, the study found that 47 per cent of the overall study were fully deployed around either multiple or a single AI use case. The equivalent number in Canada was 30 per cent. That was last among the ten countries assessed.
“We lag behind our global peers in adoption,” Holder told his audience. “From a deployed business impact, we are behind our global peers in deployed applications.”
Holder said that the data don’t show that Canada is ignoring key AI use cases. The issue is rather that they aren’t doing anywhere near as many of them.
“Canadian organizations are a little more conservative,” he said. “In the countries that were leaders, we might see a company doing five implementations of a specific use case. In Canada it would be two or three. Canada looks at the same things, but in a more measured way. There were no blind spots in terms of use cases.”
Other metrics from the study told a similar story of comparative lag. Globally, 77 per cent saw analytics as critical in AI success. In Canada, the number was 50 per cent.
“Disconnecting analytics strategy from AI is a mistake,” Holder said. “Leaders from around the world say this. There, the correlation between analytics and AI is very high.”
Where Canada was did measure up was in the question of ethics training around AI. Globally, 92 per cent of successful AI deployments had ethics training conducted around it. The equivalent number in Canada was 91 per cent.
“We have the ethical piece nailed,” Holder said.
