Report shows only 15 per cent of organizations have reached full optimization as workforce skills gap widens
There is a growing divide happening in artificial intelligence (AI) right now, and for most organizations, the gap between where they are and where they need to be is getting harder to close, says one expert.
While businesses and executives might know AI will bring disruption, only 15 per cent of organizations have moved past the development phase. For the first time, a shortage of future-ready talent has overtaken budget constraints as the top barrier, new research finds.
"It's no longer big fish eating small fish — it's fast fish eating slow fish. In the age of AI, if you're a few weeks behind, you could be really, really behind," says Ram Srinivasan, managing director of AI adoption and future of work advisory at JLL in Toronto.
Speaking to Canadian HR Reporter, Srinivasan outlines what successful AI adoption looks like inside organizations, touching on the importance of leadership participation and the right training. The insights are drawn from JLL's Future of Work Survey, based on responses from more than 2,200 C-suite executives and leaders globally.
Too many AI pilots
The reason why some organizations are having trouble moving past the initial AI development phase or full optimization stage isn't necessarily because they don't know how to scale — it's that they don't know how to scale it in a way that accounts for data, regulation and auditability, Srinivasan says.
Before getting to production, having a pilot or minimum viable product could be hard to put into production across legacy systems. Now with AI, that has become easier. It has led to what he calls "1,000 flowers blooming."
"How many of those pilots can you actually scale into production — touching your sensitive data, complying with regulation, meeting requirements for explainability and auditability? That's where the challenge is," he says.
The organizations finding the most success are not trying to scale everything at once, Srinivasan says. They are being surgical and selective about what they move forward with.
"We're seeing CIOs and CTOs who are no longer saying, 'Let 1,000 flowers bloom,'" he says. "They're asking, ‘What are the top ROI-based use cases? Let's implement there — to create customer value, to generate business outcomes, to improve the employee experience, to better support enterprise objectives.’"
Leadership required for deployment
How leaders show up is another factor separating organizations that have made it past deployment, Srinivasan says.
"The best managed transitions are where leadership is actually demonstrating use themselves. When you have an AI-literate leader, things are much, much simpler"
He points out that for many employees, there is a fear and a lack of psychological safety around AI in the workplace.
According to an Express Employment Professionals report, 66 per cent of hiring managers found their employees fear their jobs will become obsolete. A separate report by The Positive Group found only 45 per cent of workers say leadership regularly keeps their teams informed about AI developments.
That fear, Srinivasan says, is exactly what the organizations winning at adoption are working to address.
"Anytime we have a firm that thinks of AI as a force to augment the workforce, a multiplier — that's where we are finding incredible success," he says.
Training much needed
But framing AI the right way is only part of it. How organizations train their people is where many are still falling short, Srinivasan says.
While more industries might be using AI, workers still report they lack support. According to a 2026 report by Punchcard and Angus Reid Group, 68 per cent of heavy industry workers report no formal AI support — including training and approved tools — and 54 per cent reported the same across other industries.
"There's no such thing as generic AI training," Srinivasan says. "Each functional area requires different types of training. You need specific training depending on what your role is."
Rather than making AI training an HR-administered program, he argues it should be owned by business leaders themselves — and delivered using AI.
"With AI, you now have an infinitely available, infinitely patient, infinitely wise tutor. With the right governance in place, — that can be personalized to every individual," Srinivasan says.
What works even better, he says, is finding the people inside the organization who are already using AI well and letting them bring colleagues along.
"Channel that energy positively — so that team members skilled in this subject can bring others along," he says. "For me personally, it's much easier watching someone else on the team who's doing slightly better with AI tools that are actually available, as opposed to watching a ten10-month-old AI training video about ChatGPT. That's chalk and cheese."
Closing AI gaps
Falling behind on AI adoption does not just show up as a technology problem, Srinivasan says. It shows up as lost opportunity — and the longer organizations wait, the harder that gap becomes to close.
"We are spending billions on AI. We should spend a few billion on our people also," he says. "You may have the best AI, but if you have no one to deploy it, you're going to be in deep trouble."
