- Canada’s federal AI strategy tracks jobs created by AI but completely ignores workers displaced by automation.
- The federal AI strategy has been criticised for presenting an incomplete picture of AI’s real economic impact.
- Economists warn that counting only AI job gains without measuring losses distorts the true cost of automation.
- Without honest workforce data, Canadian policymakers risk designing AI policy that fails the workers it should protect.
A Strategy That Only Counts the Good News
Canada’s federal AI strategy has a metrics problem. The government is keeping careful score of how many jobs artificial intelligence is helping to create — but when it comes to the positions being eliminated by the same technology, the official count goes completely quiet. It’s a selective form of bookkeeping, and economists and labour advocates are starting to notice.
The strategy, which positions Canada as a global AI leader partly on the strength of its homegrown talent and research infrastructure, points to job creation figures as evidence that the country is navigating the AI transition well. What it doesn’t do is measure, track, or even formally acknowledge the workers on the other side of that ledger — the ones whose roles are being automated out of existence.
That omission matters more than it might seem. A policy framework that only measures wins is, almost by definition, one that can’t respond to losses.
What the Federal AI Strategy Actually Says
The federal AI strategy leans heavily on economic opportunity as its central narrative. AI investment, the argument goes, will generate new industries, new roles, and new export revenue. That’s not wrong — it’s just incomplete. Canada has genuine strengths here: the Vector Institute in Toronto, Mila in Montreal, and the Alberta Machine Intelligence Institute form a research triangle that’s attracted significant international attention and investment.
But the strategy’s success metrics are built around inputs and outputs that make the picture look tidy. Jobs created. Dollars invested. Companies scaled. There’s no equivalent tracking mechanism for jobs eliminated, sectors destabilised, or workers left without a clear retraining path.
This isn’t a uniquely Canadian problem. Governments worldwide have struggled to build honest AI workforce accounting. The OECD’s ongoing work on AI and the labour market has repeatedly highlighted the gap between job creation narratives and the more complicated displacement data that national strategies tend to underreport. But Canada’s approach is particularly striking given how much the strategy emphasises
