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AI people need to work in teams with those who can anticipate how users will interact with machines that are getting smarter and smarter, experts say.

AndreyPopov

The most obvious route to a career in AI is through studying STEM, but it is not the only one.

"We're looking for people who are actually going to help create and develop the algorithms for AI, so we're looking for STEMs [students in science, technology, engineering and math]," says Shak Parran, partner, strategic analytics and modelling at Deloitte Canada.

“Computer scientists, mathematicians, physicists and statisticians are all good. There are also specific university programs that teach about AI directly,” he says.

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At the same time, the hot job market “is not just for nerds and mathematicians,” Mr. Parran adds. There’s a need for people with skills in other fields, such as graphic design and communications.

"There's a general sense in the marketplace that demand for people with AI skills has outstripped supply," says Joe Greenwood, executive lead, data, at MaRS Discovery District's Data Catalyst in Toronto, which works with tech startups.

AI people need to work in teams with those who can anticipate how users will interact with machines that are getting smarter and smarter all the time, he says. “You need people who understand how to deploy an application and how to deal with change management,” Mr. Greenwood says.

"AI today is really a broad, overarching term," says Michael Bliemel, dean of UOIT's Faculty of Business and Information Technology.

"I like to think of it as 'big' AI and 'little' AI. I think of little AI as a helper, for example, when you finish the call and a screen pops up on your phone and asks if you want to add me as a contact," he explains.

"There's lots of research and development in little AI in computer science and related programs," Mr. Bliemel says.

Big AI seeks to answer more complex questions. For example, artificial intelligence can be applied to develop predictive models for diseases, to determine what people are susceptible, at what ages and why.

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“These models would use sensors to look at people’s heart rates, blood pressure and other measurements,” Mr. Bliemel says. They would be big, funded research projects and require experts – and graduates – from other fields, such as medicine and health policy.

AI is changing so quickly that the question is becoming not just where are the jobs in AI, but also how quickly can new types of artificial intelligence be deployed for practical purposes.

"We've just had meetings to look at robots to help take care of people in home care. The technology is developing so fast that the questions in five years might be: 'Why doesn't everybody have one of these robots, and if they don't, is that fair?"' Mr. Bliemel says.

That suggests the need for AI-savvy grads will be bigger than ever. "You may have a smart vacuum cleaner now, but the one you have in five years will probably be a lot smarter," Mr. Bliemel says.

The trend toward recruiting more and more well-rounded grads with diverse skills beyond math and science is likely to continue, says Adam Froman, founder and CEO of Delvinia Interactive Inc., a Toronto-based data research company that deploys digital analytics to serve its clients.

"You still need the mathematical ability to visualize algorithms and models. But the ability to collaborate and communicate with non-technical people is also a real need," he says.

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"A lot of engineering programs in universities are getting better at building the soft skills now, " Mr. Froman adds. Business schools are also paying attention to AI, developing programs to help industries and managers know how to use artificial intelligence.

"AI doesn’t have to be the domain of hard-core scientists anymore," says Henry Kim, associate professor and co-director of the Blockchain Lab at the Schulich School of Business at York University in Toronto.

Schulich, like some other business schools, is developing a master's specialty in AI management. It is important in a world where the financial sector is embracing blockchain, which relies on big data, and where more and more financial decisions are being made by robo-advisors.

The irony is that as AI becomes more sophisticated, "The way AI interfaces with people is less and less technical," Mr. Kim says.

In the future, it may come to pass that most jobs have a connection to artificial intelligence.

For students, the way to get involved is, well, to get involved, Mr. Greenwood says.

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“If you’re already studying computer science, enter science competitions,” he suggests.

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