Is the AI training gap dulling your transformation edge?

Canadian organizations are deploying artificial intelligence (AI) faster than they’re preparing their people to use it – and the cost of that gap is becoming impossible to ignore, according to a report. 

A recent Express Employment Professionals and The Harris Poll survey found that 79 per cent of Canadian job seekers say companies need to formally train employees on how to use AI, rather than expecting them to learn on their own. Hiring managers largely agree, with 77 per cent saying formal AI training should be a company priority. Yet policy and practice remain stubbornly out of step at many organizations, as a 2024 Survey on Employment and Skills by the Future Skills Centre found that 44 per cent of employed Canadians using AI tools at work haven’t received any formal training. 

Matthew Clarke, Vice-President of Training and Development at FGF Group in Toronto, says the most important decision his organization made was creating a dedicated training team before rolling out any tools. 

“We have an AI transformation department,” says Clarke. “There's a strong, dedicated team to work with us internally around how we can leverage AI to create impact and efficiencies, which creates a structure for us when it comes to training.” 

Building an AI training structure first 

That team, led by FGF Group's Vice-President of Digitalization and AI Transformation, also owns the training function for internal tools and agents, according to Clarke. He describes a blended learning model – an approach that combines self-directed digital content with human-supported coaching – built around two layers: general literacy content through partners like LinkedIn Learning and role-specific instruction for each tool or agent the company deploys. 

“We have an internal team that really focuses on the specifics around how that tool, that bot, that agent, will impact their specific work,” Clarke says. “As people are starting to get over their fear or uncertainty about AI, we didn't want to throw that all to just a digital or e-learning component. We wanted to make sure that we had some human experts that would sit with you and work with you.” 

Clarke also flags a principle that shapes how FGF Group approaches access and governance: employees won’t be introduced to tools they can’t then use on the job. That commitment shapes what gets deployed and to whom, he says. 

“We don't want to expose people to technologies and tools, and then never give them the opportunity to apply that learning – that's just not our philosophy or our way of working,” says Clarke. 

All team members at FGF Group have access to Microsoft CoPilot, and the company has also built a private internal environment for training that allows staff to analyze data without exposing it outside the enterprise, says Clarke. Anyone can request additional tools by submitting a brief business case, and he says most requests are approved where the use case is clear. 

Phasing the rollout and tying it to strategy 

Keri Fraser, Chief People Officer at Westland Insurance in Canada, believes in taking a tiered approach to AI training that starts at the top. Her organization recently put its leadership team through an AI training program and role-based training for the broader workforce will soon follow, she says. 

“We're deploying it in a phased approach, really looking at champion employees first and then we're working with some partner vendors where we would do a tiered training,” Fraser says. 

On governance, Fraser is clear that the Chief Information Officer (CIO) and Chief People Officer (CPO) must be working in close alignment for a successful rollout. 

"The CIO and the CPO have to be really tied together on this, which we are,” she says. “So our CIO and technology leader own the governance piece and all of the rules around it, but then we work together on how that's deployed and how that looks – it’s really a collaboration and it has to be.” 

Fraser believes that when organizational momentum outpaces training strategy, leaders need to use cases that tie directly to business strategy, not the most visible or exciting applications, to close the gap. “We're prioritizing where the most value is; otherwise it just gets too overwhelming,” she says. 

That principle – focus over breadth – is one HR teams across Canada are having to learn quickly. The national AI strategy unveiled by Prime Minister Mark Carney in June 2026 has accelerated that pressure, committing $2.3 billion in federal investment and targeting a jump in business AI adoption from roughly 12 per cent today to 60 per cent by 2034. 

The harder problem: harnessing productivity at the business level 

Tara Lockyer, Chief People, Culture, Brand and Communications Officer at ATB Financial in Alberta, has one of the most candid assessments of where even well-resourced organizations get stuck when rapid transformation leaves a knowledge gap around effective AI use. 

According to Lockyer, her organization gave its entire workforce access to AI tools early, and saw quick individual adoption – but translating personal productivity gains into organizational benefit has proven more difficult. 

“We've definitely seen huge individual productivity uptake,” says Lockyer. “But we're having a really hard time harnessing that for the organization – how do you harness that productivity at the team level or at the line of business level so that it can be redeployed? We haven't figured that one out at all.” 

ATB built awareness and capability through change management, but it didn’t set clear accountability expectations around usage from the start, says Lockyer, and the result is a wide gap between employees who have integrated AI into their daily work and those who have barely touched the tools. It’s a gap that’s common, as only 29 per cent of companies provide a list of approved or preferred AI tools, according to the Express Employment Professionals survey. 

Addressing AI anxiety 

The anxiety question is one Lockyer says keeps her up at night – and it isn’t unique to ATB. 

“I hear this from other HR leaders – the angst in the organization around, is this putting my job at risk? So if I get really good at this and automate a large portion of the tasks in my role, what does that mean for the role that I have?” she says. 

Her answer positions HR at the centre of the response. Lockyer believes that people teams must understand what’s being automated and redesign roles accordingly – ensuring employees aren’t simply left with a lighter task load, but with higher-order work that demands new capabilities. 

“We're taking away some of the boring, repetitive work, which means the work that's left may be higher order, higher cognitive, and higher creative,” she says. “So we also have a responsibility to develop skills and capabilities – not just on the use of the technology, but now how do employees become more creative or create more value, now that they have this extra time in their day?” 

Assessing transformation readiness 

Clarke, reflecting on the pace of change and the pressure on smaller or less-resourced organizations, offers a straightforward caution: understanding your organization's risk tolerance and pace of readiness matters more than chasing the leading edge. 

“Don't rush. It's so early on,” he says. “For me, it's always about building a business case for it – you've got to look at your people and make sure that you've got the right structure in place.” 

That advice – structured, paced, and grounded in organizational reality – may be the most transferable lesson from all three HR leaders. As employers navigate the growing AI skills gap and the pressure to keep workforce readiness in step with their organization’s transformation, those getting it right aren’t necessarily moving the fastest. They are moving with the most intention.