‘AI-skilled workers won't be able to add value if AI is simply an add-on or a response to market hype’
Canadian HR leaders should overhaul how they hire and train for artificial intelligence — treating AI as a technology that redesigns existing jobs and building AI fluency across the entire workforce rather than acquiring a handful of technical specialists, according to experts.
That’s because the people side of AI adoption – not the technology itself – has become the main obstacle to turning AI investments into business value, according to skills experts at the Future Skills Centre, the Information and Communications Technology Council (ICTC) and CPHR Canada.
Employers should first decide where AI adds value, then hire for skills, says CPHR Canada board chair Erin Polcyn Sailer.
"AI-skilled workers won't be able to add value if AI is simply an add-on or a response to market hype,” she says. She cautions that "too often, organizations focus only on hiring technical specialists," adding: "Technology alone doesn't create value – people do."
That points HR toward a skills-first model. "Look beyond degrees and job titles to what people have done or can do," Polcyn Sailer says, urging employers to "use practical assessments and work samples" to test whether candidates can apply AI in meaningful ways. Legere agreed competitive pressure is driving the shift: "many employers are shifting toward skills-based hiring that values demonstrable capabilities over traditional credentials or job titles."
Information and Communications Technology Council (ICTC) Research and Policy Analyst Todd Legere says.
Legere says leading employers are also widening their talent pools, "seeking adaptable candidates with adjacent skills and strong learning mindsets, rather than relying solely on experienced AI specialists," while valuing "domain experts with deep knowledge in specific sectors."
Currently, organisations are deploying AI into core operations faster than they can recruit and reskill the workers needed to run it – reframing the AI conversation as a hiring and retention problem before it is a technology problem, according to a recent report from CGI.
Build fluency through hands-on training
On training, the experts said employers should start broad. "The starting point should be building baseline AI fluency across the organization," Polcyn Sailer said, calling it "a core workplace capability, not just for technical teams, but for leaders, managers, HR professionals, and frontline employees."
The goal is bounded, she said: "The objective isn't to turn every employee into a data scientist. It's to ensure every employee can be an informed, ethical, and effective user of AI in their role." Legere said literacy must reach executives and managers, who need to be "AI-literate enough to identify meaningful opportunities for adoption."
Both said training works best as practice, not theory. "The most effective training tends to be experiential rather than theoretical," Polcyn Sailer said. The Future Skills Centre adds that the most valuable profiles are "AI-plus" skill sets pairing technical competency with critical thinking, communication and empathy — attributes that "cannot be developed through curriculum alone."
Keep humans at the centre
The experts stress keeping human judgment in control. Employees must grasp "both the potential and the limits of AI, and how to use it responsibly with appropriate human oversight," Legere says, calling it essential to building trust.
The Future Skills Centre frames oversight as a business case, not just an ethical one: "Humans need to be centred in AI processes as an economic necessity." It also warns HR that training must be designed so technological shifts "do not disproportionately impact vulnerable populations" or reinforce existing labour-market inequities.
Its research with the Diversity Institute into small and medium-sized firms suggests AI can also improve recruitment itself, through bias-aware tools that help employers compete for diverse talent.
Recently, Amazon founder Jeff Bezos said that AI adoption will lead to a "labour shortage," as he rejected assumptions that the technology will cost humans jobs.
