The biggest barrier to AI in aged care isn’t the technology. It’s change management.

Providers across home, community and residential care are under pressure to move on AI.

The case is compelling: workforce shortages are worsening, margins are tightening, and reform is reshaping how care is delivered and funded. AI offers a way to do more with the resources already in place.

So, the investment is happening. The technology is being purchased, configured and rolled out. And in too many cases, the value isn’t following.

When that happens, the instinct is to look at the technology. Was it the wrong tool? The wrong vendor? The wrong use case?

Speaking at AlayaCare’s recent roadshow series, Darren Gossling, CEO of Rohling, made the case that providers are looking in the wrong place.

The technology is rarely the problem. What’s stalling value is something harder to budget for and easier to underestimate: organisational change.

Watch Darren speak at AlayaCare’s recent roadshow, AI and Efficiency: Protecting margins in a changing care landscape:

AI is not intended to save you (but it can save you time)

Before getting into why implementations stall, it’s worth being direct about what AI actually does.

It augments. It does not replace.

“In reality it will help. It will augment. It doesn’t replace,” Darren told the room. That distinction matters more than it might seem. Fear of replacement is often the first barrier care workers encounter, and if leadership doesn’t address it clearly and early, adoption stalls before the program has a chance to prove itself. The conversation needs to happen at the start, not after resistance has already set in.

Once that’s established, the real opportunity comes into focus. And it looks different depending on where in the care continuum you operate.

In home and community care, the value sits in reducing documentation burden, improving billable time and tightening package utilisation. Care workers spend significant time on administrative tasks that pull them away from direct care. AI can change that, but only if workers actually use it.

Darren Gossling, CEO, Rohling speaking at the AlayaCare roadshow, AI and Efficiency: Protecting margins in a changing care landscape

In residential care, the opportunity is in smarter rostering, tracking funded minutes, reducing reliance on agency staff and keeping compliance documentation current. These are areas where small improvements in consistency compound quickly into meaningful financial and clinical outcomes.

Neither of these happens automatically. They require people to change the way they do their jobs, day to day. And that is where the change management challenge begins.

Expect an 18 to 24 month return on investment. Not a quick win, but a compounding one, for providers prepared to treat AI as a program, not a project with a go-live date.

The iceberg: 80% of the work is invisible

Most providers see the AI tool. They evaluate it, they procure it, they implement it. What they often don’t see is everything that has to be in place underneath it for the tool to do anything useful.

According to Darren, 80-90% of the work in an AI implementation happens below the surface: data infrastructure, governance, ethics, regulatory alignment, risk and compliance. The visible part (the interface a care worker interacts with) is a fraction of what makes the whole thing function.

In a sector currently navigating the new Aged Care Act and the transition to Support at Home, the regulatory and compliance layer is not a formality. It is load-bearing. Getting it wrong isn’t just an IT problem.

Data is the most consistent blocker, across both home and residential settings. Darren put it to the room directly: “Who here doesn’t have a data problem?” No hands went up.

Clean, accessible, integrated data is a precondition for meaningful AI, not something to sort out after go-live. Providers who skip this step find themselves with capable technology sitting on top of a shaky foundation. The outputs are unreliable. Trust erodes quickly. And adoption drops.

Where value stalls (and it’s not where most people look)

Here is the part that most providers don’t budget for.

“The biggest part for organisations is change management,” Darren said. “We’re changing the way in which we work. We’re changing workflows. We’re changing business processes. It takes time for people to adapt to that.”

The technology can be made to work. The harder question is whether people will use it.

According to Gartner research cited by Darren, 60% of employees look to their managers and leaders for support when it comes to adopting new technology. They want reassurance, guidance and a clear sense that the people above them understand what’s changing and why.

But roughly half of those managers aren’t equipped to provide it.

That gap is where the value of an AI investment can quickly erode. When middle managers can’t answer questions from their team, can’t model the new behaviours, and can’t explain the rationale, workers default to what they know. In home and community care, that means reverting to old documentation habits, package utilisation doesn’t improve, and the administrative burden AI was supposed to lift stays exactly where it was. In residential care, rostering decisions get made the old way, funded minutes go untracked, and compliance documentation continues to be done manually, at exactly the moment the new Act is demanding more rigour.

Middle management enablement isn’t a nice-to-have. It is the program.

Funding the technology without funding the people and change support alongside it is one of the most common reasons AI implementations fail to deliver. The investment decision gets made at the executive level. The results, or the lack of them, play out on the floor.

Know who’s in your workforce, and use it

Not everyone in a care organisation responds to AI the same way. Understanding the split is one of the most practical things a provider can do.

Darren referenced Gartner data pointing to three distinct groups. Around 20% of the workforce are AI achievers. They’re already using it, they want to use it more, and they’re motivated by the idea of providing better care with less friction. In home and community care, these are often the workers with the strongest billable productivity. In residential care, they tend to be the clinical staff pushing for better documentation, sharper oversight and more consistent outcomes.

Around 50% are ambivalent. They’ll use AI if the conditions are right. They’re watching what happens to the people around them and making a quiet calculation about whether it’s worth the effort.

And then there are those who disengage. Without active intervention, this group can represent up to 60% of the workforce: a majority of people not getting value from an investment the organisation has already made.

With a deliberate approach, you can see around 70% adoption across the organisation

The ambivalent group is where the real opportunity sits. They will move in the direction of whoever influences them most. When AI achievers are actively championed, given visibility, a voice in the rollout and recognition for the outcomes they’re driving, they shift the ambivalent group. And the ambivalent group, in turn, reduces the dropout rate.

The realistic outcome, with a deliberate approach: around 70% adoption across the organisation. That number changes the financial picture of the investment entirely.

What makes AI programs actually work

Darren was clear on this: there is no shortage of examples in aged care of AI programs that have worked and programs that haven’t. The difference is rarely the technology.

The programs that work share a few consistent characteristics.

Ownership sits across the C-suite, not just with the CIO. When AI strategy is led by IT alone, it reflects a technology point of view. When other executives are co-owners (operations, finance, clinical) the program reflects the operational realities of the organisation. That breadth of ownership matters more in care settings than in most industries, where home, community and residential services each carry distinct workflows, workforce profiles and regulatory requirements.

Middle managers are the most important change agents, in any setting. They set the tone for every shift, every visit, every care interaction. A residential care manager who understands the AI tool and backs it visibly is worth more to adoption than any communication campaign.

The vision has to run from the board all the way through to the front line. “It’s not just ‘let’s implement the technology and then we’re going to get all the whiz-bang benefits out of it’,” Darren said. “We need to make sure there’s a vision, that we’ve got the foundation, and that it’s supported at the board level all the way through the organisation.” AI cannot be a project that the executive team endorses and then hands off. It needs governance, ongoing maintenance and a willingness to adapt as the organisation changes: as client needs evolve, as the regulatory environment shifts, as the technology itself develops.

Pilot, embed, then scale. Resist the temptation to roll out broadly before the change program is ready. The providers who get into difficulty are typically the ones who move fast on technology and slow on people, and then can’t understand why the results aren’t there.

The organisations getting results aren’t doing anything extraordinary

They’ve aligned their leadership. They’ve prepared their middle managers. They’ve invested in their data. And they’ve given their AI achievers room to influence the people around them.

That holds true whether they’re managing Support at Home packages, rostering a 120-bed residential facility, or somewhere in between.

The challenge of change management isn’t unique to aged care. But the stakes are. Providers are operating in an environment where the margin for error is already thin, where workforce shortages are real, where reform is ongoing, and where the people receiving care are among the most vulnerable in the community.

Getting AI right in this context isn’t just an operational question. It’s what determines whether providers can sustain the care they’re there to deliver.

The path forward isn’t complicated. But as Darren put it: “Give it time, but don’t just set and forget. It needs to have a focus. It needs to be led within the organisation.” That requires treating change management with the same rigour as the technology itself.

Darren Gossling, CEO of Rohling, presented at AlayaCare’s AI and Efficiency: Protecting margins in a changing care landscape roadshow series.