Will AI’s ‘war on workers’ come to Canada?

According to a U.S. Senate minority staff report released last month by Senator Bernie Sanders, artificial intelligence (AI) and automation “could replace nearly 100 million jobs over the next 10 years.”

Could Canada see the same massive wave of job loss?

As Piers Steel, professor of human resources at the University of Calgary, explains, although Canada has traditionally adopted new technologies slower than its neighbours to the south, in taking a more cautious approach, the trend may no longer be the case.

"America is more aggressive that way, it likes to be on the cutting edge," he says, adding that the scale of investment globally means Canadian employers can no longer hide behind a slower pace, assuming they have years to develop a response strategy.

“They're putting literally trillions of dollars into this. So, we haven't seen exactly what AI is going to be able to do eventually. It hasn't leveled off; the bubble hasn't burst.”

Canada's SME economy offers different dynamics

Sanders’ report reveals that major U.S. corporations are aggressively implementing AI-driven workforce reductions.

For example, Amazon, which made $59.2 billion in profits last year, has laid off 27,000 workers since 2022 while explicitly stating that generative AI (GenAI) and AI agents “will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company."

Walmart, the report details, has cut 70,000 jobs over the past five years while revenues increased by $150 billion.

Simon Blanchette, lecturer at the Desautels Faculty of Management at McGill University, explains that Canada's economy differs fundamentally from the States’, meaning shifts in the workforce won’t be as drastic here, but it will happen.

“As an economy, Canada and the US are structured really differently … we're an SME backbone economy compared to the U.S., which is almost 50-50 [employed by] large corporations,” he says.

Instead of the unbridled shifts in workforce demographics that Sanders’ report predicts for the U.S., Blanchette says Canada’s transition will be “a slow but very uneven restructuring of work. Some jobs will be deeply transformed, some will not necessarily be as impacted, depending on levels of AI exposures.”

Skills gaps create dangerous organizational blind spots

For Steel, one of the most pressing challenges facing Canadian employers with AI adoption is the erosion of critical skills needed to oversee and validate those systems. As entry-level jobs disappear, he says, talent pipelines are being eroded, and the consequences of that will be sorely felt when current knowledge-holders retire.

“What is our career path for getting people up to this level of skills, where they can start to vet AI?” he asks, adding that it’s experience-based knowledge that will become more valuable and needed as AI dependence continues to grow. “That is a disappearing resource that you're not replacing.”

Without employees experienced enough to evaluate AI output, organizations will lose the ability to catch errors and misuses, Steel adds – unless they intentionally preserve and develop it: “Skills that don't get used, atrophy.”

AI automation about augmentation, not replacement

According to Sanders’ report, ChatGPT-based analysis predicts that artificial intelligence and automation could replace tasks accounting for 60 to 70% of employees' time across the U.S. economy.

However, as Blanchette points out, task elimination does not directly equal job elimination; in fact, this difference is a key point for employers and HR to know. He advises employers to be proactive in future planning, recommending a granular approach: “Map exposure, try to analyze every single job to see, how can they be either complemented or potentially replaced by AI?”

This mapping exercise creates the foundation for strategic decision-making, he adds, stressing that by being intentional and proactive, HR leaders can develop targeted upskilling programs instead of reacting to external conditions with hasty layoffs.

Blanchette has a stark warning for employers who doubt the importance of strategic workforce auditing: do it now or get left behind.

“Any organization who is introducing AI without investing in building skills, in redesigning roles and doing workforce planning, they're not doing transformation,” he says.

“They are doing layoffs with extra steps, because they're losing expertise, and they're not really planning for what's going to come after … we need to be pairing any automation with a transition plan. If you know ahead of time, you can decide in advance who will stay, who is useful, who will be deployed between upscales.”

Training and supervision become core competencies

Steel emphasizes that rather than seeing AI automation as cost-cutting measures, employers should be investing in training and supervision; any gains in productivity will depend on workers being capable of using AI effectively.

Without this supervisory investment, he adds, organizations gain a tool but lose the human oversight that ensures it is being used appropriately.

This means incorporating AI use into regular performance assessment, not seeing it as an “extra” that isn’t regulated or monitored, says Steel: “You have to manage that performance: Are they performing with AI correctly? Are they using it correctly? Are they vetting it correctly? And that's going to be a large thing."

Blanchette emphasizes a final critical point: for many Canadian organizations, the stakes are heightened by the reality that they cannot simply recruit their way out of skills shortages. This places even more emphasis on upskilling, which he says is not being done enough by Canadian employers.

“They still hope that they will be able to recruit the person with the right skills, and that's wishful thinking,” he says.

“AI is here to stay, so we need to really create the ecosystems to explore it and implement it in a healthy, ethical and also sustainable way.”