Canada has made huge waves in the research of artificial intelligence in recent years, but some in the industry are saying that this is not enough and that we must now take the next vital step: actual implementation.

A study by Forbes Insights late last year ranked Canada last out of the 10 countries they surveyed for the adoption of AI.

The study, which surveyed over 300 executives, found that only 31 per cent of Canadian organizations that attempted to implement AI tech were successful, compared to 59 per cent and 58 per cent in India and Germany, respectively.

Jodie Wallis, managing director of AI for Accenture.

The findings are tough to dispute, according to Jodie Wallis, the managing director of AI in Canada for Accenture, who has talked with international peers about the survey’s findings.

“It’s hard to disagree with the statistics that they collect. When I talk to my colleagues internationally, I do think that Canadian organizations are slower to adopt,” said Wallis in an interview with ITBusiness.ca. “I think if we look back historically, we would see that Canadian organizations generally adopt new technologies a little bit slower than their global peers. I think they’re moving, they’re just moving at a slightly slower pace than some of their global peers. ”

Although she is quick to note that Canada has done quite well in AI research – evidenced by its growing AI research hubs – it’s implementation and integration of AI that Canada finds itself so far behind the ball.

“I think that the government at all levels, including the provincial government, have done a very good job of investing in AI research and fundamental research. But that alone does not get us adoption,” said Wallis. “What fundamental research gets us is breakthrough algorithmic techniques that are published in papers. I think that they’re now trying to figure out ‘how do we do an equally good job at incentivizing organizations to adopt AI?’ Because they really haven’t had big programs of investment in adoption.”

And this is a sentiment that Canada’s Minister of Innovation, Science, and Economic Development, Navdeep Bains, agrees with. He said that Canada has clearly established itself in AI research, the key is to now leverage that research and development into concrete results via implementation and commercialization.

“We’ve turned the corner. And so the idea is, how do we build on that momentum?” said Bains in an exclusive interview with IT World Canada at the MaRS Discovery District in April. “We’re an incredible leader when it comes to researching AI.”

Wallis says she sees three major roadblocks that need to be addressed for Canada to achieve its true AI goals. Government support and incentives for investment in adoption, a talent shortage for supporting positions outside of those actually developing the AI technology, and a hesitancy for larger companies to collaborate with AI startups.

Government support for the development and research into AI is strong, according to Bains, but even he admits government support for actual adoption is lacking.

“Now we need to step up and really develop that AI ecosystem.”

Wallis believes we should look internationally to how some other countries have taken action to kickstart the adoption of AI.

“Some other countries like Singapore have taken a pretty aggressive approach in terms of offering incentives to companies to adopt AI. That is always an option,” said Wallis. “My hope is that we can continue to make sure barriers are cleared for companies from a regulatory standpoint and not make it onerous to adopt AI.”

Collaboration

Much of the calls for AI adoption relate to Canada’s larger businesses. But what some may not see is the proactive work being done by startups in the field of AI.

Executives from TD Bank Group and Layer 6 (an AI startup they acquired late last year) spoke on a panel at the Collision conference in Toronto last week. They discussed the benefits larger corporations see when joining forces with AI startups to collaborate on AI solutions.

This is a strategy that Wallis strongly supports.

“In my business life, I am trying not to do any AI work without involving members of the ecosystem; whether it be a startup or people from academia. I think that is the absolute key to success,” indicated Wallis. “First of all, I think it’s a great way to bring new and different perspectives together. Second of all, I think it’s a great way to feed back into the startup ecosystem; real-world examples and revenue that they could use to grow. And the third thing, I just think it exposes people to I think it exposes the large companies to ways of working faster and it exposes the startup to understanding how complicated it is to get things done in large organizations. And with that exposure, both types of organizations are going to improve on their own.”

Talent Shortage

While much has been said about the need to develop the skills of the future, including those used for developing and creating AI technologies, Wallis argued there is an area just as important that is being completely overlooked: the less flashy supporting roles that help insert AI into work processes.

“The algorithms themselves don’t change business processes. They don’t deliver services, right? They are techniques that need to be combined with other technologies in order to deliver results,” explained Wallis. “It’s not enough for us to increase the number of AI researchers or developers we have. We also have to look at supporting them with the right kind of data engineers, product managers, business analysts, and have all of them trained in their own ways on how to bring AI solutions to market.”

The example that Wallis used is an insurance company using AI to detect fraud. While the algorithm to detect the fraud may already be developed, it’s next to useless unless employees are trained to understand what the algorithm is doing and how to fits into the business.

“That is kind of the secret sauce, if you will,” she said. “There’s a whole bunch of business change now because your process is going to be different than it was before. So we need to be thinking about all of those skills. And I think that is perhaps something that our organizations here in Canada and probably around the world are still just coming to terms with.”