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John Kelleher is a partner at McKinsey & Co. and the co-chair of Next Canada. Laura McGee is an engagement manager at McKinsey & Co. and co-founder of #GoSponsorHer.

There's no doubt that Canada could lead the planet in artificial intelligence (AI). Canadian academics such as Geoffrey Hinton and Yoshua Bengio essentially created the field of deep learning and put Canada on the map; today, Edmonton, Toronto and Montreal are globally important centres of AI research. The best AI talent in the world is also increasingly coming to Canada to launch AI businesses such as integrate.ai and others.

All these companies and researchers are convinced of the technology's enormous commercial potential. If AI develops like other technologies, most of these benefits will flow to the country that builds the first good ecosystem. This is a huge opportunity for Canada.

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At the same time, AI poses clear challenges to business and government. Over the next 10 to 20 years, nearly half of Canada's jobs are at high risk of being affected by automation. Women hold a lot of these jobs and are especially at risk – the World Economic Forum says that globally, women will face about twice the rate of job loss as men in what it calls the fourth industrial revolution.

How can Canadian companies gain the benefits of this disruptive technology while ensuring that large segments of society are not left behind? In our view, the public and private sectors should take six steps to outsmart AI and avoid its dislocations:

Commit to building the world's best AI ecosystem: The winning AI cluster will create many high-paying jobs and create spillover effects for the middle class – but the also-rans will not. Half-measures won't work. Canada must play to win. If there is going to be a steam engine that disrupts the status quo – and AI is shaping up that way – then Canada should develop and build the very best steam engine it can, right here at home.

Create at-scale AI training programs: Industry can form coalitions to collect data, oversee curriculum development and rapidly retrain workers in the skills needed to succeed in nascent AI applications.

Take Generation, a McKinsey-supported initiative that works with employers to quickly train and place young workers in sectors like health care and technology. Graduates have an 84 per cent employment rate within 90 days of completing the program and earn two to six times more income than before. Similarly, Prominp in Brazil trains 30,000 youth each year for positions in the oil and gas industry, with 189 skill-profile "tracks" and an 80-per-cent postgrad employment rate.

In Canada, such a program could be built in partnership with new research groups such as the Vector Institute in Toronto or with incubators such as Communitech, Next Canada and the Creative Destruction Lab.

Launch innovative new training models: The government could launch and fund a "venture capital lab" to create innovative training programs, so new training ideas can be tested, validated and scaled up (as recommended by the Advisory Council on Economic Growth). Startups such as Ryerson's Magnet have great potential to address labour-market challenges. A so-called "FutureSkills Lab" could help scale great ideas and share learnings across provinces.

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Build real links between companies and research schools: Large companies could partner with universities and vocational schools to provide equipment, facilities and expertise to prepare students for AI. In exchange, these companies could receive preferential recruiting.

For example, TAFE SA in South Australia trains approximately 500,000 students each year in high-demand areas such as aged care and nursing, trades and information technology. It partners with hundreds of businesses each year, which provide apprenticeships and traineeships. TAFE also orchestrates "reverse co-op" program where large corporations and small-to-medium-sized enterprises send workers back to campus for a term to learn critical AI skills.

Urgently reinvent curriculums for software and AI: Elementary, high-school and university programs have to develop the skills that empower students to be leaders in the coming AI tsunami – critical thinking, teamwork, coding, algorithmic understanding and math. Some jurisdictions (e.g., Chicago and Queensland, Australia) are already moving to make software-coding classes mandatory. Canada should consider doing the same.

Government may want to consider practising what it preaches and adopt AI itself: A technology-enabled, AI-smart public service could not only be more efficient and provide better services. It might also create a product that Canada could export to the world.

Canadian companies have a real opportunity to leverage AI for growth – but not without an inclusive work force. We all have a stake in getting this right.

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