Sonic and Healius are both well out of the post-covid doldrums but will AI and government policy be kind to these normally robust but conservative businesses?
Our two biggest pathology groups – Healius and Sonic – seem to have shaken off their post-covid volume blues and talk of imminent disruption by government healthcare data initiatives and technology, with both reporting solid first-half 2026 performances for their relative market positions.
Here’s a summary table comparing the results of each.
| Metric | Sonic Healthcare (SHL) | Healius (HLS) |
| Revenue | A$5,445m | A$688.1m |
| Revenue Growth | +17% | +3.8% |
| EBITDA | A$907m | A$122.2m (Underlying) |
| EBITDA Growth | +10% | +13.1% |
| EBIT (Underlying) | – | A$7.9m (vs $2.7m loss pcp) |
| Net Profit (NPAT) | A$262m | A$(30.4)m (Reported) |
| Cash Position | A$557.1m | Net cash A$11.6m |
| EPS (Basic) | 53.1c | Negative (statutory loss) |
Sonic shares rose an impressive 12% on its reporting announcement this morning.
Healius is still dusting itself off from near death and the need to dump assets to survive, but the markets are essentially saying it is back, albeit the share price didn’t do anything much today.
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The summary might be, the markets love Sonic and like Healius. They like pathology again.
But there’s virtually no hint that either business faces some significant strategic headwinds in the form of a government very determined to reduce pathology waste and incur additional data cost (and therefore test volumes) through a big agenda on interoperability (“sharing by default”), and by the new AI agents.
The story on where government wants to go with its sharing by default plumbing and legislation plans is largely detailed in this article, but in summary, the government thinks there might be up to 25% waste in our pathology testing regimes and a lot of it can be overcome with better data-sharing protocols across the healthcare system.
Even at 10-15% that would be pretty catastrophic for the pathology groups’ margins.
But the government’s plan for “sharing by default” is grand and goes way beyond making pathology a lot more efficient.
Some of it involves the pathology groups sharing a lot more data easily with other providers and with patients, a lot of it in real time, and, at a minimum, getting it all loaded into the My Health Record, more or less in real time.
As things stand today, nearly all of this does nothing for the pathology groups but adds a fair bit of cost.
In the longer term, the idea that patients should be able to have all their data in real time and start making their own decisions on healthcare could significantly disrupt pathology’s core business model of getting GPs to resell their services to patients, who have no idea that they can shop around for their pathology services.
Of course, there are wins as well losses in all this for pathology. If they can manage to create their own direct relationships with patients by better data sharing, they will lock in an even better model of selling than through GPs – direct to patients, where they might start selling other related services such as genetic analysis.
The thing is pathology can’t be seen in its old market light – steady as she goes, robust and conservative business model with a few great moats that may never be disrupted.
No, there’s more strategic challenge on the horizon for pathology than probably in the history of these largely aggregated-by-acquisition-to-scale monoliths.
The market dynamics to the model of buying up lots of smaller labs, consolidating and creating economies of scale with big centralised pathology testing gear, isn’t going to see them through the next decade.
They are going to need to innovate a lot more.
AI, of course, is another potential challenge with lots of unknown unknowns.
In one respect AI should offer a lot of possibilities for significant productivity gains for the pathology groups: lots less workforce for interpretation, processing and data analytics, augmented diagnostics, especially for complex testing in the case of cancer and genetics, and generally, faster turnaround times.
But there are lots of potential problems in the new AI agents for the pathology groups too.
They include stuff like disintermediation of their current reselling network – GPs – by the bigger corporates, the new platform players and health insurers – all of whom might be able to use AI to go around a lot of what the current path groups offer.
Then there’s a lot of risk in the groups incorporating AI from a regulation and privacy viewpoint, the possibility of agile new all AI-architected competitors, and more cyber security and data governance headaches.
A group like Healius may be getting too small to buy their way out of these headwinds.
Likely Sonic isn’t going to have the problem. With smart enough leadership, which it has had for a long time, it can buy its way out of most of the AI disruption coming its way, if indeed it turns out to be as disruptive as some people are predicting.
