New research from Accenture reveals that 86 per cent of organisations plan to increase AI spending, but only just over 40 per cent plan to upskill their people to use it. The gap is visible in financial results: the 18 per cent of companies Accenture calls "Talent Reinventors" - those with a talent strategy fully integrated with AI - grew revenue 1.8 percentage points higher than peers in 2025.
"Only about 18 per cent of the organisations kind of showed six key characteristics that would drive revenue increase and profit increase for them as a result of the AI programs they're putting in," said Tenielle Colussi, managing director of talent and organisation at Accenture Australia and New Zealand. "Which is kind of concerning when you flip it and go, well, what are 82 per cent of those organisations doing?"
The upskilling gap in the numbers
Workers are already feeling AI's benefits at the task level - 68 per cent say it saves them time on routine work - but only 19 per cent feel they have the skills to succeed with it, according to Accenture's data. Colussi argues that's exactly where organisations lose value. She is sceptical that classroom-style training changes behaviour on the job. "When people get back onto their jobs, onto the tools, they've probably only got about 10 per cent retention of what they learned in an academy or an online course or like a face to face training," she said.
Instead, she pointed to organisations building learning directly into daily workflows - for instance, giving a call centre worker AI-generated prompts to choose between in real time, with the system learning from each choice. That kind of embedded upskilling is central to effective AI for Human Resources strategies, where skills development happens continuously rather than in isolated events.
Rebuilding jobs around AI, not bolting it on
Colussi warned against layering AI on top of existing roles without changing how work is structured. "How do we decompose the jobs and then rebuild them with AI in the loop and human in the lead, and make sure that we're getting the best out of the employees and the best out of our tech investment as well," she said. The more effective approach, she argues, is to break down roles and redesign them so humans and algorithms complement each other rather than compete.
Leadership visibility makes experimentation safe
At Lucid Software, Chief Evangelist Bryan Stallings described how openness from senior leadership drove grassroots adoption. The company's chief marketing officer shared his own AI experiments broadly. "He's sharing his experiments and he's talking about it frequently with everyone, and he's encouraging us to try things out as well," Stallings said. "At first when we had access to the tools, it felt a little bit like cheating to check it out. But then he comes in and he's like, here's what AI did for me this weekend and look at these results."
That culture of sharing extends to failure, too, said evangelist Jessica Guistolise. "We had somebody come up with - they vibe-coded an app so that nobody would ever have to argue about what's for dinner anymore as a family," she said. "It's that kind of thing that makes experimentation safe across the organisation." Guistolise stressed that naming ambiguity directly, rather than glossing over rapid change, is what lands AI transformation successfully. "AI transformations are not going to work if we are not paying attention to the people who are in the midst of them," she said.
Dave Garrison, CEO and co-founder of Garrison Growth, sees many executives treating AI adoption as the objective itself rather than a tool for business purpose. "The issue is not how do we implement AI," he said. "The issue is how do we position AI within our firm as it relates to our compelling purpose, our values, and our business objective? How do we allow people to see AI as a tool to accomplish things we already know, as opposed to a new thing?" He described AI as a "freedom tool" for time-poor employees: "If we start to think about AI as a way to give us time to get to more important things, it suddenly is not a technology tool at all. It's a freedom tool."
What successful adoption actually looks like
Garrison recalled a multi-billion-dollar company that initially appointed AI advocates in every department to find problems AI could solve, only to see tepid results. "They are retreating to say, okay, let's break into small groups instead of meeting as a large group, let's break into small groups and share ideas on what's working," he said. The shift toward low-risk, informal sharing mirrors a manufacturing-era analogy Stallings offers: factories that replaced a single steam engine with one electrical engine but kept the same long drive shaft missed the real gains until smaller motors were distributed across the floor. "It feels like we're at that stage where we still have a lot of individual use, and we're trying to help companies understand how to adopt it as an institution," Stallings said. Guistolise summed up the implication: "Essentially, we have to redesign the factory floor again."
Colussi tied the same idea back to Accenture's data, noting that Talent Reinventors built talent mobility into their strategy more often than they relied on external hiring. She also referenced a case of an organisation that let go its entire junior workforce to capture short-term productivity gains from AI, only to face a capability shortfall years later. For senior HR leaders tasked with these transitions, an AI Learning Path for CHROs can provide a structured way to rethink workforce planning around AI, rather than chasing immediate efficiency cuts.
Why this matters for HR professionals
The throughline from all four conversations is that culture and communication, not the sophistication of the tools, determine whether AI investments deliver real performance gains. Garrison put the risk plainly: "The risk is it fails not because the technology doesn't work, the technology is great. It's because it's one more item on a long list of to-dos, and we're under pressure, and I'll get to it when I get to it."
HR leaders can step into this gap by surfacing employee anxiety and repositioning AI as an invitation, not a mandate. "There's really an opportunity for HR to partner and be the voice of, here's what people's suspicions are," Garrison said. When time is the biggest barrier, framing AI as a way to free people for higher-value work - what Garrison calls a freedom tool - can shift adoption from a forced march to a shared discovery. The organisations pulling ahead are those investing at least as heavily in their people as in the technology itself.
Your membership also unlocks:
