Canada launched a national artificial intelligence (AI) strategy on June 4, promising 250,000 jobs, while UC Berkeley reported record failing grades in computer science classes that professors trace to student overreliance on the same technology.
Prime Minister Mark Carney unveiled the AI for All strategy in Toronto with AI Minister Evan Solomon. Days earlier, Berkeley faculty disclosed failure rates suggesting AI is reshaping how students learn.
Canada Bets Big on Its AI Strategy
The strategy targets up to $200 billion in added growth and 250,000 new jobs over five years, according to the official release. It aims to lift business AI adoption from just over 12% to 60% by 2034.
That gap is the point. Canada ranks among the slowest G7 nations to adopt AI at scale, despite holding a fast-growing digital sector.
The plan succeeds the 2017 Pan-Canadian AI Strategy, the world’s first national AI plan, which seeded the Vector, Mila, and Amii research institutes.
It also promises free AI literacy for 1 million post-secondary students and trusted AI agents for every learner. That promise now meets a cautionary signal from California.
“AI is here. The question is whether it will improve the lives of all Canadians or benefit only a few… That’s why we need an ambitious new strategy: AI for All,” Carney said in a statement.
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Berkeley Shows AI’s Classroom Cost
Elsewhere, at UC Berkeley, 35.3% of Computer Science 10 (course code) students failed in spring 2026, up from under 10% in prior years, per Berkeleytime data. The department expects only 7% to fail.
Teaching professor Dan Garcia traced the spike to a sharp rise in AI-enabled cheating. Nearly 30 students were caught using large language models (LLMs) on take-home exams.
“One professor discovered a student’s linear algebra class had an “open AI” policy for homework and exams. That student then couldn’t do basic linear algebra in the next course,” noted Hedgie, a financial markets analyst.
Garcia said his office hours, once full, now often sit empty. Faculty warn the failures signal weaker fundamentals, not only misconduct.
The risk compounds when automating skilled jobs meets graduates who never mastered the basics.
“Companies are firing experienced engineers while the pipeline that produces new ones is being gutted by the same technology,” one user quipped.
A Workforce Squeezed at Both Ends
The timing is stark. AI-cited layoffs hit a record 38,579 in May, 40% of all U.S. cuts and the leading reason for a third straight month, outplacement firm Challenger, Gray and Christmas reported.
AI has been blamed for 87,714 cuts so far in 2026, already past the 54,836 logged in all of 2025. Critics call the label cover for routine cost-cutting.
Some tech workers now seek refuge in other sectors as employers restructure around automation.
Block confirmed layoffs tied to AI, while Wall Street opened stable digital asset roles for displaced talent.
Can Canada be able to build skills faster than AI erodes them? The coming months of AI-driven job restructuring and promised legislation will offer the first test.
