Higher rates, soft growth and AI screening tools are changing how employers hire and retain office talent in Canada, says expert
If recent headlines and around employment and hiring are to believed, the main challenge currently facing white collar employees — and the organizations that employ them — is mass layoffs due to the replacement of jobs by artificial intelligence (AI).
However, recent U.S. economic data shows a different picture: the white collar labour market is being shaped more by a slower economy and higher borrowing rates than the tidal wave of AI technology in the workplace.
Canadian statistics show a similar effect here: as reported by Statistics Canada (StatsCan), the Canadian economy shrank by 0.3 per cent in October, the largest monthly drop in almost three years, pulled down by weakness in both goods and services.
In the United States, the mix of slower growth and higher borrowing costs has been described as a “white-collar recession” that sees office and knowledge workers facing tougher job searches and reduced mobility.
This runs contrary to a common narrative that has dominated headlines of late: that mass AI adoption in workplaces is the culprit, causing employers to hire less and layoff more as they replace workers with tech.
Interest rates and policy choices, not AI, behind hiring restraint
As a result, Lars Osberg, professor of economics at Dalhousie University, argues that employers are reacting to forces largely beyond their own control, such as policy and trade rules set elsewhere.
In Canada, manufacturing output fell by 1.5 per cent, driven in part by a 6.9-per-cent decline in machinery production, while wood product manufacturing suffered its steepest decline since early 2020 after new U.S. tariffs took effect, according to Statistics Canada.
Construction also slipped, and residential building decreased for the third consecutive month, even as the services side of the economy was disrupted by a nationwide Canada Post work stoppage and a teachers’ strike in Alberta.
“[Employers] respond to the interest rates that they have to pay on what they're borrowing, they respond to the sales they're experiencing. They respond to the uncertainty that's generic in our current trading environment with the United States,” he says.
“So, the individual employer can't actually solve the problem, the problem of macroeconomic policy, those decisions are made in Ottawa.”
Osberg describes AI not as an overnight disruptor, but as a gradual force building in the background. Even as macroeconomic forces dominate the month-to-month headlines, artificial intelligence is quietly altering what white-collar jobs look like, and who gets them.
“It's not as big a deal as the impacts of higher interest rates or cutbacks in government spending, but it's more long lasting,” he says.
“It adds up, little bit by little bit, month by month over many years. That gets to be a very big deal. But, at any point in time, it's not nearly as big a deal as the level of interest rates.”
Survival, profit and hesitation by employers
Within that macro framework, Osberg is blunt about what motivates employers: survival.
Rather than deep cuts, employers may opt for slow attrition, tighter performance management and selective hiring freezes. The result is a labour market that feels stagnant to many professionals even when the unemployment rate does not spike dramatically.
In sectors such as technology, this has already changed the calculus around entry-level hiring – Osberg describes the computer science job market as an example of this flux: “People coming out of computer science programs that were, five, 10 years ago, they were hot tickets, because there were lots of jobs for coders. Now, we discover that artificial intelligence does a lot of coding pretty well.”
That shift may help explain why some employers that once recruited aggressively from universities are now more tentative, relying on smaller cohorts and more specialized roles rather than broad-based intake.
White-collar job market: when AI writes cover letter
Exacerbating the situation, Osberg stresses, are the changes to the job funnel itself as more individuals and organizations use AI to write, read, filter and eliminate job applications.
Add to this the phenomenon of “ghost postings,” and the result is an increasingly frustrating environment for both job seekers and the employers trying to hire them.
“You find a bunch of job seekers who are logging on to ChatGPT to draft their application letters, and you find a whole bunch of employers who are using AI to screen out applicants,” he says.
“So it's a more frustrating labour market for people who are on the outside, because it's harder to know when you're actually applying for a real job and who's actually looking at your application.”
Osberg is wary of employers relying too heavily on automated filters at the front end of recruitment. While acknowledging that humans also carry biases, he argues that direct review brings a different kind of accountability: “You may not be perfectly conscious of all your own biases, but still, you're a human.”
In that environment, long-term unemployment can become more entrenched, especially when public supports are limited; Osberg notes that “that breeds a lot of despair out there.” For HR departments, this means that how they communicate about hiring — and whether postings are genuine — can have real consequences for people with few buffers.
