Artificial intelligence is supposed to be the next great leap for healthcare, promising faster diagnoses, lighter administrative loads and smarter rostering. Yet a growing number of Australia’s private hospitals say they are in no position to chase any of it, because they are preoccupied with a far more basic problem: staying open.
That is the blunt message from Catholic Health Australia, the country’s largest non-government grouping of health and aged care providers, which represents a significant slice of the private hospital sector. According to reporting by The Medical Republic, the body argues that persistent operating losses, mounting workforce costs and funding arrangements that have not kept pace with reality are squeezing hospitals so hard that technology investment, AI included, keeps sliding down the priority list.
Why the money matters first
The context here is a private hospital sector that has spent the past two years in open financial distress. Several operators have closed wards, handed back maternity services or warned of insolvency, and the Commonwealth was moved to commission its own health check of the industry’s viability. The core tension is familiar to anyone who has followed the dispute between hospitals and health insurers: the fees paid by funds for a given procedure have not risen fast enough to cover the rising cost of staff, energy and supplies that go into delivering it.
When margins are that thin, capital works and new technology become luxuries. AI tools, whether they are ambient scribes that draft clinical notes, imaging systems that flag anomalies, or software that smooths patient flow through a hospital, all require upfront spending, integration work and training before they deliver a return. A hospital running at a loss and worrying about next quarter’s payroll is not well placed to write that cheque, however compelling the long-term case might be.
Catholic Health Australia’s point, as relayed in the source article, is that this creates a timing trap. The very institutions that could most benefit from efficiency gains are the ones least able to afford the investment that would unlock them. The result is not that private hospitals reject AI, but that they keep deferring it while they deal with the fires in front of them.
Two ways to read the warning
There are competing interpretations of this situation, and both deserve airing. On one side sit the hospital operators and their representative bodies, who frame AI investment as impossible without first repairing the sector’s finances. In their telling, the funding model is the root cause, and no amount of enthusiasm for machine learning will matter until the economics of running a private hospital are put back on a sustainable footing. Fix the base, they argue, and the innovation will follow.
On the other side are technology advocates and some health economists who make a more uncomfortable case: that AI is not a reward for financial health but one of the few levers available to achieve it. If an ambient documentation tool can hand a clinician back an hour a day, or if better scheduling can lift theatre utilisation by a few percentage points, then the technology pays for itself precisely because the hospital is under pressure. From this angle, treating AI as something to be done later risks locking struggling hospitals out of the productivity gains that might have helped them survive.
Both positions can be true at once. The investment is genuinely hard to fund when the lights are the priority, and the investment is also one of the more plausible routes out of the squeeze. What neither side disputes is that the current settings make the first barrier very real.
The regional divide
The most consequential part of the warning concerns geography. Catholic Health Australia flags that smaller regional facilities are at particular risk of falling further behind, and the logic is straightforward. A large metropolitan private hospital group can spread the cost of an AI rollout across many sites, negotiate better terms with vendors, and justify a dedicated digital team. A single regional hospital enjoys none of those advantages. It faces the same software licensing costs with a fraction of the patient volume to absorb them, often while already struggling to recruit and retain clinical staff.
That asymmetry threatens to widen a gap that country communities can least afford. Regional and rural Australians already contend with longer waits, thinner specialist coverage and the tyranny of distance. If AI-enabled diagnostics, remote monitoring and workflow tools become standard in city hospitals while regional sites cannot fund them, the quality-of-care divide between the bush and the capitals could harden rather than close, baked in by the economics of who can afford the technology.
What it means for Australia
For the broader Australian health system, this is more than a private sector problem. Private hospitals carry a substantial share of the nation’s elective surgery and specialist care, and when they weaken, the pressure flows straight to an already stretched public system. A private sector that cannot modernise is a private sector more likely to shed services, which in turn lengthens public waiting lists and raises costs for taxpayers. The AI question, then, is really a question about whether a large part of the country’s hospital capacity can keep up at all.
It also complicates the national conversation about digital health. Governments and regulators have been busy drafting guidance on how AI should be deployed safely in clinical settings, with attention to patient safety, data governance and accountability. Those frameworks assume hospitals have the means to adopt the technology in the first place. If a meaningful chunk of the sector is financially frozen out, the policy debate risks running well ahead of the on-the-ground reality, producing rules for a rollout that many providers simply cannot begin.
What’s next
The near-term focus will stay on funding. The ongoing standoff between hospitals and insurers over procedure fees, along with the Commonwealth’s continued scrutiny of private hospital viability, will largely determine whether operators find any headroom for investment. Expect Catholic Health Australia and its peers to keep tying the two issues together, arguing that a sustainable funding model is the precondition for any serious push into AI.
For technology vendors eyeing the Australian health market, the message is a sobering one. The appetite for AI in hospitals is real, but the capacity to pay for it is not evenly spread, and the regional end of the market may need different commercial models, shared-service arrangements or public support if it is to participate at all. Until the sector’s finances stabilise, the most likely outcome is a two-speed rollout, with well-capitalised metropolitan groups moving ahead and smaller players watching from the sidelines, hoping the funding conversation turns their way before the technology gap becomes permanent.
Sources: The Medical Republic
