Canada's AI for All strategy sets a national ambition — but the real work happens inside your organization
Prime Minister Mark Carney's AI for All plan, launched June 4, 2026, in Toronto, commits $2.3 billion in federal investment and targets a jump in business AI adoption from just over 12 per cent today to 60 per cent by 2034. It creates opportunity — and it places accountability squarely on HR leaders who can’t wait for Ottawa to tell them what to do next.
The strategy's workforce ambitions are significant: 250,000 new AI-related jobs, up to 90,000 placements for young Canadians, and employer-led training commitments for mid-career professionals and frontline workers. But the plan omits mandatory retraining obligations, union notification requirements, and job displacement modelling. The gap between what the government has announced and what needs to happen inside organizations is where HR leaders must operate.
Here are five transformation priorities for HR leaders brought into focus by the national AI strategy, according to two executives who work at the centre of AI-driven workforce change.
Map your workforce exposure before someone else does
The strategy projects 250,000 new jobs but doesn’t model how many jobs could be displaced by AI. Research from Statistics Canada and the Future Skills Centre estimates that close to 60 per cent of all Canadian jobs will be affected by AI — split between roles at risk of automation and those AI will augment. HR leaders who aren’t already building that internal picture are operating without a compass, says Lewis Curley, Lead Partner, People and Change for Ontario and Atlantic at KPMG Canada.
“Build a clear view of workforce exposure and identify where AI can enhance work in a way that improves productivity without eroding trust,” says Curley. “Then invest in manager readiness, because managers are the ones translating strategy into employee experience.”
That exposure map should go beyond a simple automation risk score. Curley believes in framing it around value: which roles create the outcomes the organization exists to deliver, which tasks within those roles can be accelerated by AI, and which decisions must remain with a human. That framing shifts the conversation inside a business from threat to design, he says.
Stop treating AI adoption as a technology project
The federal strategy's ambition to move adoption from 12 per cent to 60 per cent by 2034 won’t be achieved by deploying tools and ignoring people, according to Curley. He says KPMG’s research shows Canadian businesses are already engaging with AI — but very few are seeing meaningful returns, with only a small share reporting clear return on investment. That’s due to the failure to connect AI tools to how work is actually done, he says.
“Many have AI in pockets of the business, but it's not always embedded into value creation at scale,” says Curley. “The organizations making real progress are the ones starting from a point of understanding the value they can bring to the business, then considering how AI can enhance that value and how humans can work with AI and bring the intrinsically human attributes to that value creation — then people move from ‘having to adopt AI’ to ‘wanting to adopt AI.’”
AI is already reshaping which teams exist, which are shrinking, and which didn’t exist two years ago, and HR leaders need to be ahead of that movement, not reacting to it, says Willson Cross, CEO of Borderless AI. “The type of person you bring into your marketing organization literally 800 days ago is completely different than the type of individual in marketing that you bring on today,” says Cross. “There are some teams that didn’t even exist a couple years ago that now need to exist because of AI, and on top of that, there are some teams that don't need to exist anymore.”
Build trust through visible guardrails
The national strategy's optimism about AI-driven job creation runs headlong into a significant data reality. The Ipsos AI Monitor 2026 — a 32-country survey of 23,532 adults conducted between March and April 2026 — found that 67 per cent of Canadians say AI makes them nervous, among the highest rates globally. Just 20 per cent of Canadian workers believe AI will improve their job and only 18 per cent are comfortable with AI screening job applicants, despite 53 per cent admitting they already use AI tools at work.
HR leaders working on building trust and transparency in AI-enabled workplaces can’t close that gap with just reassuring messaging, says Curley. “Trust-building at scale comes down to visible guardrails — our research shows 83 per cent of Canadians would be more willing to trust AI if there are clear assurances in place like human oversight, the ability to opt out of data use, and accountability when something goes wrong,” he says. “Those aren’t abstract ideas — they need to show up in policy and day-to-day practice.”
Organizations need explicit, published positions on where AI will and won’t be used in decisions that affect employees — performance reviews, scheduling, recruitment screening, and promotion — before employees start asking the questions, says Cross. “Show employees how it improves a specific part of their job,” he says. “When people see it helping them do better work rather than being assessed by it, the conversation shifts quickly.”
Design employer-led training around roles
The strategy's National AI Literacy Initiative targets one million post-secondary students and commits to employer-led training for mid-career professionals and frontline workers. The government has framed employers as the primary vehicle for bridging the skills gap — which means HR owns the delivery, even as public programs develop in the background.
Curley is unambiguous about what effective programs look like. “Employer-led training needs to be tied directly to work, because the strongest and most effective programs are role-based, not generic,” he says. “What that looks like in practice is frontline employees getting practical guidance on how AI fits into their workflow, managers learning how to redesign work and lead AI-enabled teams, and technical teams building deeper capability around data and governance.”
The business case, he argues, is already made. “The employees who are resisting AI today often do so because they lack confidence in how to properly use it,” says Curley. “Investing in skills isn't just about future-proofing — it's about unlocking productivity from the tools organizations are already investing in."
For Cross, the business case for AI training is obvious. “It’s such low hanging fruit that just those few steps down the field will pay dividends long term — there are day-to-day efficiencies to be gleaned from very rudimentary training on how you onboard employees and how you train employees on a new job,” he says. Even in a heavily regulated future scenario, those early training investments would still pay off, because the operational efficiency gains are immediate and durable, he says.
Plan for the roles that don’t exist yet
The national strategy projects substantial new job creation, and Cross believes that HR leaders who wait for those roles to be clearly defined will always be behind. “There are going to be new job titles in the next two weeks that weren't around two weeks ago — AI implementation engineers, AI specialist trainers to run learning and development programs, AI product designers, AI sales engineers — there are literally new job titles and new job descriptions popping up everywhere,” he suggesting that HR leaders can build a forward-looking recruitment map.
Cross is also emphatic that the transformation can’t be led from a distance, and leaders must use the tools themselves. “It’s going to be very hard for organizations and companies to become truly what I call ‘AI native’ without leaders actually using the tools themselves,” says. That expectation extends to the HR function: people leaders who have not personally engaged with AI tools are poorly positioned to counsel executives, assess vendor claims, or design credible training programs for others, says Cross.
For Canadian HR leaders keeping pace with how organizations are approaching workforce transformation, the Canada’s AI for All strategy signals that workforce readiness is now a strategic pillar, not a supporting function. The federal government is measuring it, employees are watching, and the organizations that move now — with a clear view of workforce exposure, role-based training, and visible employee guardrails — are the ones that will have the internal momentum to meet the curve the strategy is setting.
“HR will be key to redesigning skilling programs — not just skilling to use AI, but skilling to support where the earlier career activities are automated, so that experience becomes key,” says Curley.
