On June 4, 2026, Prime Minister Carney launched “AI for All”, Canada’s first comprehensive national AI strategy. For anyone working in tech, watching this sector evolve, or considering a move into AI and data, this is a significant moment worth paying attention to.
Here are our thoughts.
At the heart of this strategy lies a paradox. Canada is the birthplace of some of the world’s most influential AI researchers: Geoffrey Hinton, Yoshua Bengio, and Richard Sutton. It is also home to internationally recognized institutions like Mila in Montréal, the Vector Institute in Toronto, and Amii in Edmonton. The country has invested $4.4 billion in AI and digital research infrastructure since 2016, with an additional $2.4 billion sovereign compute initiative now underway.
Yet, only 12.2% of Canadian businesses currently use AI to produce goods or services, well behind Denmark (42%), Germany (26%), and France (18%). Among SMEs specifically, that number falls to 8%. Overall, a mere 2% of businesses report a measurable return on investment from these technologies.
This is the gap the strategy sets out to close. The ambition: bring business AI adoption from 12% to 60% by 2034, create up to 250,000 new jobs, and train 1 million post-secondary students.
The strategy is organized around six pillars, built on three core values: trust, opportunity, and sovereignty.
On trust: modernizing privacy legislation, building AI safety infrastructure, protecting Canadians — particularly children — from AI-related harms, and ensuring democratic institutions remain resilient against AI-enabled misinformation.
On opportunity: building a national AI literacy initiative, training post-secondary students, creating 90,000 AI-related work placements for young Canadians, and supporting mid-career upskilling. This is where the strategy speaks most directly to individuals.
On sovereignty: investing in Canadian compute infrastructure, anchoring world-class research talent, scaling domestic AI champions, and building trusted international alliances.
It’s a broad, ambitious vision. The honest read: the strategy sets important direction and backs it with real investment. But it is still primarily a framework. Concrete implementation will come through programs, partnerships, and institutions.
The KPMG-University of Melbourne global trust study, cited in the strategy itself, ranks Canada 44th out of 47 countries on AI training and literacy. Fewer than one in four Canadians report having received any AI training. Less than half feel they can use AI tools effectively.
The most significant gap remains human: too few workers have access to practical AI training.
The strategy’s National AI Literacy Initiative commits to reaching 1 million post-secondary students with free, accessible AI training and placing 90,000 young Canadians in AI-related roles by 2031. That’s a necessary foundation, but it’s only part of the picture. Every job will require some level of AI literacy, not just the 250,000 the strategy explicitly targets.
Mid-career professionals are the underleveraged piece. They’re already inside the organizations the strategy wants to transform. Upskilling them is how sectoral adoption actually happens.
The urgency is real. Since 2022, hiring freezes, layoffs, and rapid automation have compressed career timelines and raised the stakes for professionals navigating change. The geopolitical pressures accelerating AI investment globally aren’t slowing down. Canada cannot afford a slow start on this.
Le Wagon has been training professionals in tech and AI skills since 2013, across more than 27 cities across the world, including markets where AI adoption is already well ahead of where Canada stands today.
In Montréal, we’ve trained close to 1,000 people since 2017, across shifting market cycles. The profiles, the motivations, and the career outcomes have shifted, but one thing hasn’t: professionals who build practical, applicable skills find a way forward.
Our Montréal cohorts reflect this reality. They’re primarily composed of professionals between their late twenties and mid-thirties, people with existing careers who made an active decision to pivot or level up. During the tech boom of 2020-2021, our alumni found roles quickly and in volume (97% placement rate in 43 days on average, according to our 2020 outcomes report). After the market correction of 2022-2023, the path was harder, but they adapted. In both cycles, the underlying pattern held: practical training in real demand translates into real outcomes.
When alumni do find roles, the majority land in SMEs and tech startups (86% of hires in 2020, according to the same data). Those are exactly the organizations the strategy is trying to reach. The talent pipeline and the adoption challenge are the same problem, approached from two sides.
We strongly welcome this strategy. Establishing a national framework is exactly what Canada needs to effectively embed AI into businesses.
We believe that for AI to generate real and lasting impact, the entire organization must be brought on board: leaders who guide and inspire change, internal AI champions who implement and transmit it, and functional teams who make AI a reflex in their day-to-day work.
For over a decade, Le Wagon has been training professionals across every continent through successive waves of technological transformation, in markets at every stage of adoption. We offer bootcamps (400 hours) and short upskilling courses (40 hours) in data and AI, designed for individuals ready to make a move or level up fast. We design and deliver practical training programs, tailored to the specific needs and context of each organization.
We know what works at the individual level, and we know what organizations need to move from experimentation to lasting integration. We want to help bring this national strategy to life. We have the expertise to act right now.
Ready to move? Discover our bootcamps and short courses at lewagon.com/montreal.
Building AI skills across your organization? Reach out to our team
Read the Canada’s National Artificial Intelligence Strategy: AI for All.
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