Businesses are investing in AI and technology faster than they are investing in the people expected to use it, according to Sara O’Connor, Head of Training at Altis Consulting.
O’Connor, who has worked in workplace training for more than two decades, says she has watched training budgets shrink even as technology spending accelerates. “Twenty years ago, a training program might have run for a week. Then it became two or three days,” she said. Now, she’s increasingly hearing a different line from employers: “There’s no way we can take people off the tools for two days.”
That shift, she argues, pushes learning to the margins of people’s lives. “You’ve got a full working week to deliver and then education happens somewhere around that,” O’Connor said. “There’s an assumption that learning is something that employees should somehow squeeze into evenings and weekends.”
She says that assumption carries a cost well beyond wellbeing. “That is not only detrimental to work-life balance and well-being, it is detrimental to workplace productivity,” she said.
The capability gap, by the numbers
The gap O’Connor describes shows up in the data. Research from KPMG and the University of Melbourne found just 24 percent of Australians have undertaken AI-related training or education, with more than 60 percent reporting low knowledge of AI and fewer than half believing they have the skills to use it effectively.
O’Connor says technology is moving faster than most workplaces can support people through it. “They need guidance, discussion, collaboration and the chance to apply what they are learning with others,” she said. “Simply giving employees access to a course and expecting them to work it out in their own time is not the same as building capability.”
She’s also sceptical of after-hours learning as a substitute for structured training. “Squinting at a laptop at the kitchen table at 10pm after a full day of work and family commitments doesn’t cut it,” she said.
Tech and training, together
O’Connor compares investing in AI without investing in training to a familiar parenting trap. “Investing in AI without investing in the people expected to use it is a bit like buying your child a top-of-the-range musical instrument and never booking them a lesson,” she said. “You can spend as much as you like on the equipment, but without guidance, practice and support, you are unlikely to get the result you hoped for.”
She says the problem often starts with where attention goes first. “The ‘shiny, sexy bit’ is the technology, the AI, the platforms, the data infrastructure,” O’Connor said. “Too often, capability building comes later, almost as an afterthought.”
Her advice for business leaders is to tackle two things at once: understand what capabilities the business already has and will need, and genuinely invest in building them, rather than treating training as a follow-up step once the tech is in place.
That forward planning matters, she says, because roles can shift before people are ready for them. “Employees can suddenly find themselves being told ‘You’re now responsible for this’, simply because technology has taken the organisation in a new direction,” O’Connor said. “The expectation changes before the capability has been built.”
She points to organisations that bring technology and people leaders together from the start, building tech and capability roadmaps side by side rather than sequentially.
What SMEs can do differently
For smaller businesses without a dedicated learning and development team, O’Connor’s framework still applies, just at a different scale. Practical starting points include:
Audit before you buy. A short team survey on existing skills and confidence with current tools can flag gaps before a new platform is purchased.
Train on one tool at a time. Rolling out several AI tools at once multiplies the learning load and makes it harder for staff to build real fluency in any of them.
Protect paid training time. Even 30 to 45 minute sessions during work hours, rather than left for evenings, signal that learning is part of the job, not an extra.
Use peer learning. Pairing a confident user with a hesitant one costs nothing and often works faster than formal courses.
Lean on vendor training. Many SaaS and AI platforms now bundle onboarding webinars, certifications or support content at no extra cost, worth checking before paying for external training.
Choose tools with the problem in mind, not the trend. O’Connor’s broader point, that technology and workforce planning should move together, applies directly to stack decisions: pick the tool that solves a specific bottleneck, rather than adding software because competitors have it.
The retention cost of standing still
O’Connor also points to a less obvious cost of underinvestment: staff turnover. “People are motivated by a sense of mastery, the feeling that they are getting better at something, building their skills and progressing,” she said. “When employees can see themselves developing, it gives them another reason to stay.”
She says the reverse holds too. “If development stalls, people can start to worry that staying put means falling behind,” O’Connor said. “The cost of underinvestment in learning may not show up immediately, but it can appear later in disengagement and attrition as employees leave in search of opportunities to keep growing.”
O’Connor isn’t calling for a return to lavish, week-long training programs. “I’m not suggesting organisations return to the heady days of overseas training junkets and week-long courses for everyone,” she said. “In the current economic climate, purse strings are tight and every investment is being scrutinised.”
But she says the pendulum has swung too far the other way. “We have swung too far in the other direction,” O’Connor said. “Expecting people to build major new capabilities around the edges of a full working week is not a serious workforce strategy.”
Her conclusion is straightforward: businesses that want AI and technology investment to translate into productivity need to treat staff capability as part of that investment, not an afterthought to it. “If organisations are serious about productivity, they need to be just as serious about investing in the capability of the people expected to deliver it.”