As AI spending climbs, organizations are creating dedicated AI enablement roles to bridge technology and business outcomes
The number of AI enablement job postings on Indeed Canada has grown approximately 80-fold since early 2024 while the overall number of job postings has declined, according to data provided to HRD Canada by the job-search company – a signal that Canadian employers are no longer treating artificial intelligence (AI) as an information technology (IT) project. Instead, they’re treating it as an organizational transformation that demands dedicated, cross-functional leadership to determine how to successfully implement AI and determine its true return on investment (ROI).
When Krista Swanson, Senior Vice President of Corporate IT at supply chain software company Kinaxis in Ottawa, describes how her organization defines AI ROI, she’s quick to move past the familiar fixation on hours saved. "I think organizations can get very hyper-focused on productivity as an uplift, but we're almost past that point now,” says Swanson. “The question is, as with any IT investment: how is that going to make the business materially better?”
According to Swanson, the “hype cycle for AI” has moved from trying to rationalize the investment to treating it like any other technology investment relative to the value it’s adding back to the company.
Not just engagement with AI, but embedding it
Valli Musti, Senior Vice President and Chief Information Officer of Enterprise Data and AI Platforms at Toronto-based Scotiabank, puts a finer point on what failure to ask that question looks like. "One of the biggest lessons we’ve learned is that usage alone is not a substantial measure of success," says Musti. "High engagement with AI tools is encouraging, but it doesn't necessarily mean meaningful value is being created."
According to Musti, the most durable AI use cases are those that embed themselves into core workflows over time. This is where most HR leaders are not seeing meaningful ROI from AI adoption – a gap this new generation of enablement roles is designed to close.
At Connor, Clark & Lunn Financial Group (CCL), an investment management firm in Vancouver, the recognition that AI requires focused stewardship came through direct experience, according to Ankur Saxena, Director of Technology Strategy at CCL. The firm built a dedicated AI enablement team and has been actively hiring for AI-specific roles, he says.
"Early on, the realization that this is largely a business change impact initiative and less of a technology initiative – that was key," says Saxena. "Without having this type of awareness – someone really putting their arms around this – you could be injecting a 10-times risk even though you have a very strong risk management framework.”
Saxena cites the danger of shadow adoption of AI without proper oversight: teams connecting unauthorized tools that inadvertently expose sensitive data, compounding governance failures that a centralized enablement function is specifically designed to prevent.
Helping the people side of AI adoption
A dedicated AI enablement team and roles have their value not in technology terms, but for the workforce, according to Diana Bartolic, Head of HR at CCL. "There's a lot of transformation and change happening in workplaces now, probably more so than we've ever seen before," says Bartolic. "I think less about job loss and more about roles really changing – people doing different things."
Bartolic adds that with much of leadership doing AI tasks “off the side of our desk,” dedicated AI enablement roles help streamline transformation pieces within the business more quickly as the organization thinks through processes and changes its workforce.
Musti describes Scotiabank's AI Enablement Engineer position as the connective tissue the organization needed once foundational elements were in place. "Roles like the AI Enablement Engineer provide an important connective layer between technology teams, business teams, and governance functions," she says. "They help establish common practices, accelerate knowledge sharing, and ensure that adoption is happening in a way that’s both effective and responsible."
A big risk in AI adoption is that it becomes fragmented without dedicated ownership, which can lead to inconsistent or duplicate use with silos of knowledge rather than organization-wide progress, according to Musti.
AI adoption leads to three types of people in the workplace, says Saxena – the quick adoptive leaders, the laggards, and those in-between. “Our enablement function is primarily the biggest response to harmonizing those three different paces,” he says. “And I think what we’re realizing is that it's been a good segue because now we actually have a structure of how you can see who's in which quadrant and how to help them.”
The enablement role also brings needed focus to AI adoption when everyone is busy with other things, says Saxena. “We’re always constantly prioritizing things, so not having focus to this would have not done it a good service,” he says. “So we had to actually have a core group to figure it out, demystify some of the stuff, and actually gain some hands-on experience.”
Indeed Hiring Lab data published in July 2026 found that 63 per cent of AI-touched job titles in the US are now outside traditional technology occupations – spreading into healthcare, marketing, operations, and management. The Canadian job-posting data reflects the same acceleration, with AI enablement roles as a share of total postings reaching their highest recorded level in June 2026.
What the AI enablement role actually requires
What should organizations look for in an AI enablement professional? Not just a pure technologist, according to Saxena.
"AI becomes a three-legged stool," he says. "You've got to have the technology toolkit; you understand the digital impact of the organization's assets – your data, your workflows, your processes; and the third thing is: what's the business problem you're trying to solve? If you bring the three together, you can see it becomes that sort of triad."
Swanson adds governance and change management to that profile. "This is technology that exposes data to different data sources," she says. "And when you're doing it at scale, change management is really key. You need to find leaders that have that whole breadth of understanding and are really thinking about that human impact at the end of the day."
Musti points to the blurring of traditional boundaries between technology and people leadership as the defining context. “What's interesting about this role is that it sits at the intersection of technology, business operations, and change management,” says Musti. “The strongest AI enablement professionals are those who can operate comfortably in both worlds, combining technical fluency with business acumen, industry knowledge, and a strong understanding of client needs.”
The challenge, as Swanson sees it, goes well beyond individual hiring decisions. The way AI is helping HR get back to its human core illustrates the broader point: technology without people strategy is incomplete. "AI isn't a one-time technology deployment like we're used to," she says. "We're not just deploying a [customer relationship management] system. It's an organizational capability augmented by technology."
Building for long-term transformation
The common assumption Swanson and her organization had to revise was that providing access alone would be sufficient for AI adoption without focused AI leadership, she says.
"It's a false thing to assume that simply making AI tools available to employees is going to lead to business value," says Swanson, who adds that Kinaxis invested in its “engine room” – an internal AI enablement program that brings together employees at different stages of adoption, from enthusiastic early movers to those still waiting to understand what AI means for their specific role.
This is the core lesson from Scotiabank's journey, according to Musti. "Successful AI transformation is ultimately a people-led effort,” she says. “Technology is the enabler, but long-term value comes from empowering employees to use it confidently, responsibly, and in ways that improve outcomes for both the Bank and our clients."
However, although many organizations are moving towards a focused team or role to guide AI adoption, Swanson believes that organizations that distribute AI accountability across senior leadership – rather than expecting a single function to absorb the entire transformation – appear best positioned to convert potential into performance.
“How is AI driving the best outcomes for your business and how do you work with your leadership team to make that happen, and how do you mobilize your employees towards that same mission? – to me, that’s no different than any other technology journey,” says Swanson. “Conversely, if you’re bringing that officer into the organization, are you missing some of that, are they going to be more focused on the technology and are they going to have the breadth of business understanding they need to do it?”
For Swanson, she believes that an AI enablement officer has to understand fundamentally how the business operates to make sure the organization is making the right AI decisions for its needs.
“Organizations that have the greatest long-term value with AI are going to be the ones that invest just as much in their people and processes and training as they do in the technology themselves,” she says.
