The most direct Canadian evidence on this question comes from Statistics Canada, and it is more specific, and more mixed, than either the claim that AI is already coming for entry-level jobs or the opposite claim that nothing has changed.
Key takeaways
StatCan’s own study looked at employment from November 2022 — when generative AI applications started gaining traction following the mass availability of ChatGPT — through December 2025, comparing jobs by how exposed they are to AI and how complementary AI is to the work. Its headline finding: “employment generally grew regardless of potential occupational exposure to and complementarity with AI.” (StatCan, Canadian employment trends in the era of generative AI) That is not a finding that AI has had no effect on anyone — the same study is specific about where the effect actually showed up, and it showed up by age, not by whether a job touches AI.
“However, job growth varied across worker characteristics. Younger employees and those less educated generally saw weaker job growth over this period.” (same study) Coding work is the clearest single example StatCan gives: “coding-intensive professions (e.g., software engineers and web designers) grew at a similar rate as other jobs” overall, but “gains in coding-intensive jobs were concentrated among workers aged 30 to 49, while the number of coding professionals younger than 30 stagnated.” The pattern is age-shaped, not exposure-shaped — the jobs did not shrink, the growth simply did not reach the youngest workers in them.
StatCan attaches its own caveat directly to these findings, and it has to travel with any use of them: “it is unclear whether more recent trends reflect the advent of AI, other economic factors such as labour market adjustments after the COVID-19 pandemic, rapid demographic shifts, recent trade tensions with the United States or a combination of factors.” (same study, its own caveat) A junior employee reading headlines about AI and entry-level hiring is looking at a period that also contains a post-pandemic labour market reset and a trade shock — the data cannot cleanly separate the three.
Context worth holding onto: as of the second quarter of 2026, 19.2% of Canadian businesses reported using AI to produce goods or deliver services in the preceding 12 months — a proportion StatCan says “has tripled since the second quarter of 2024 (6.1%)”, but still a minority. (StatCan, AI use by businesses in Canada, Q2 2026) Adoption is also uneven by business age: businesses more than 20 years old used AI at 15.0% versus 21.7% for businesses two years old or less, and StatCan notes plainly that “businesses that are more than 20 years old were less likely to use AI in the last 12 months, compared to younger businesses.” A junior employee’s actual exposure to AI at work still depends heavily on which kind of employer they land at, not on their occupation alone.
Adoption is far from even across sectors, and a junior role inside a high-adoption industry meets a different reality than the same title elsewhere. Over the last 12 months to Q2 2026, information and cultural industries led AI use at 42.3%, finance and insurance at 40.4%, and professional, scientific and technical services at 32.4%. (StatCan, AI use by businesses in Canada, Q2 2026) At the other end, agriculture, forestry, fishing and hunting sat at just 4.5%, wholesale trade at 7.9%, and construction at 9.2%. A junior analyst starting at a financial-services firm and a junior tradesperson starting in construction are, on this evidence, entering AI-adoption environments roughly nine times apart — the first is far more likely to have an AI tool built into their daily workflow from day one, for better or worse, than the second.
Consider two people starting their first job in the same month: a junior data analyst at a Canadian bank, and a first-year apprentice electrician at a small construction firm. On StatCan’s own industry figures, the analyst joins a sector where 40.4% of businesses already use AI, likely for data or text analytics given those applications’ dominance industry-wide; the apprentice joins a sector at 9.2%, where physical, on-site tasks dominate and AI adoption of any kind remains rare. Neither StatCan figure predicts what happens to either person’s career — but they do predict how soon each is likely to be working alongside an AI tool as a normal part of the job, which is a different and more answerable question than “will AI take my job.”
Canada’s own federal AI strategy treats skills as one of its three deliberate pillars, alongside commercialization and standards, rather than leaving talent development to chance. The Pan-Canadian Artificial Intelligence Strategy, launched in 2017 with $125 million through Budget 2017, funded the Canada CIFAR AI Chairs program and the three national AI institutes — Amii, Mila and the Vector Institute — and its second phase, backed by Budget 2021 and the 2024 Fall Economic Statement, names three pillars: Commercialization (helping businesses use AI), Standards (advancing AI-related standards), and Talent and Research (supporting research and growing the talent pool). (ISED, Pan-Canadian Artificial Intelligence Strategy) That a national strategy treats talent as a standing pillar, a decade into the strategy’s life, is itself a sign the underlying concern for junior workers is being taken seriously at the policy level — not proof of any particular outcome for any one junior worker.
Ontario gave junior applicants themselves a specific, checkable right starting January 1, 2026: any employer that advertises a publicly advertised job posting and uses artificial intelligence “to screen, assess or select applicants for the position shall include in the posting a statement disclosing the use of the artificial intelligence”. (Employment Standards Act, 2000, s.8.4) The duty does not reach every employer: a regulation exempts any employer with fewer than 25 employees on the day the posting is advertised. (O. Reg. 476/24, s.1) A junior applicant is therefore more likely to actually see that disclosure at a larger employer than at a small one — its own kind of unevenness, layered on top of the industry gap StatCan’s data already shows.
StatCan’s own data does not show that. Employment grew regardless of a job’s AI exposure over the period studied — what it found was weaker growth for younger and less-educated workers specifically, and it says plainly it cannot separate AI’s effect from other economic forces over the same window.
StatCan reports the fact without a confirmed cause: gains in coding-intensive roles concentrated among workers aged 30–49 while the count of coding professionals under 30 did not grow — a real, specific, but unexplained pattern in the data.
It is Canadian, drawn from Statistics Canada’s own employment and business-survey data — it should not be assumed to describe every labour market, and StatCan does not make that claim either.
Related: will AI replace Canadian jobs, which work tasks AI changes first, and planning AI adoption around your actual workforce.
A short call is enough to separate what the Canadian data actually shows from the headlines around it.
