ASX health imaging stocks view AI as a growth tool, not a disruptor. Pic: Getty Images<\/p>\n
ASX health imaging firms see AI as an opportunity, not a threat, with growth potential intact
\nPro Medicus caught up in tech sell-off as investors question impact of AI
\nMorgans says AI is a powerful tool for workflow efficiency but won\u2019t replace radiology or enterprise-grade imaging\u00a0<\/p>\n
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Artificial intelligence (AI) has become a major talking point for investors and analysts in recent months, contributing to volatility across global software stocks as markets weigh the technology\u2019s potential to disrupt the sector.<\/p>\n
The rise of powerful AI coding tools from companies such as Anthropic has fuelled speculation that software development could become faster, cheaper and easier to replicate, raising questions about the durability of traditional SaaS business models<\/a>.<\/p>\n Pro Medicus (ASX:PME)<\/a> has long been one of the standout growth stories on both the S&P\/ASX 200 Index and the S&P\/ASX 200 Health Care Index.<\/p>\n With a market cap of ~$14.5 billion, the company is the largest of ASX-listed medical imaging software names and has delivered strong earnings growth for many years, supported by global demand for its Visage imaging platform.<\/p>\n Like many tech companies, however, the share price of Pro Medicus has been volatile recently as investors question valuations and the potential impact of AI. Despite reporting a strong first-half result, the stock has fallen roughly 40% year-to-date.<\/p>\n \u00a0<\/p>\n Pro Medicus software can\u2019t be readily replicated<\/p>\n Both CEO and co-founder Sam Hupert and Morgans healthcare analyst Iain Wilkie, who covers Pro Medicus, argue the concerns may be overstated.<\/p>\n In commentary released to the market<\/a>, Hupert said Pro Medicus had been caught up in broader tech sector sentiment driven by massive capital spending on AI infrastructure.<\/p>\n \u201cThere are concerns at the huge level of capital expenditure committed to develop AI and build data centres to run it,\u201d\u00a0 Hupert said.<\/p>\n \u201cOurs is a capital-light, software-only model. If anything, we will be the beneficiaries of the infrastructure funded by others.\u201d<\/p>\n Hupert also pushed back on the idea that new AI tools could easily replicate complex industry-grade software.<\/p>\n \u201cThis, in our view, is an overly simplistic generalisation, one that certainly doesn\u2019t apply to us,\u201d he said.<\/p>\n Hupert said Visage 7 was built from the ground up using proprietary technology.<\/p>\n \u201cIt is a very specialised, highly technical, patented suite of software that incorporates more than 30 years of domain knowledge,\u201d he said.<\/p>\n \u201cIt is not a product that can be readily replicated with or without AI. We have not left a roadmap for others to follow.\u201d<\/p>\n Thirdly, Hupert said their offering was more than software but was all the systems and methods built around it enabling Pro Medicus to deliver the \u201chighly sophisticated, deeply integrated solution used by many of the world\u2019s leading medical institutions\u201d.<\/p>\n \u00a0<\/p>\n Still a need for radiologists<\/p>\n Hupert said the view that AI could disrupt the diagnostic imaging market to the point where there won\u2019t be a need for radiologists was an \u201coversimplification and overestimation of the current capability\u201d in the sector.<\/p>\n \u201cBased on recent manpower surveys it is estimated that the efficiencies that AI currently delivers, and is predicted to deliver soon, will be counterbalanced by the increasing workload generated by new forms of imaging and larger data sets,\u201d he said.<\/p>\n \u201cIn other words, it will be used to \u2018play catchup\u2019 rather than replace radiologists who are currently in huge demand.\u201d<\/p>\n Wilkie said radiology was structurally constrained and had been for a decade with CT and MRI volumes growing faster than radiologist supply, which means bottlenecks, reporting queues, and burnout.<\/p>\n \u201cAI is absolutely a powerful tool for workflow efficiency, but it doesn\u2019t replace radiology, and crucially, it doesn\u2019t replace the enterprise-grade imaging backbone these tools depend on,\u201d he said.<\/p>\n \u201cAI still requires robust routing, data management, visualisation, audit trails, and compliance layers \u2013 which is exactly where PME plays. They\u2019re the rails the system runs on.\u201d<\/p>\n \u00a0<\/p>\n Robust regulatory environment<\/p>\n Wilkie said radiology information systems (RIS) and enterprise imaging workflows were among the most heavily regulated categories in healthcare IT.<\/p>\n \u201cIn the US, HIPAA mandates strict privacy, encryption, audit trails and role-based access,\u201d he said.<\/p>\n \u201cIn Europe, GDPR governs every piece of personal health data, and the MDR, along with the incoming EU AI Act, classifies AI enabled radiology tools as high risk, requiring human oversight, conformity assessments and post-market surveillance.<\/p>\n The FDA treats RIS and associated workflow software as Class II medical devices subject to full quality system regulation.<\/p>\n \u201cIn Australia, the TGA regulates anything used for serious disease diagnosis.\u201d<\/p>\n He said globally, hospitals can\u2019t even accredit without meeting standards set by medical bodies like the American College of Radiology.<\/p>\n \u201cAll of this means clinical infrastructure can\u2019t be swapped out quickly or cheaply.<\/p>\n \u201cProcurement cycles stretch for years \u2013 we see it with Pro Medicus and Mach7, where contracts can take years before implementation.<\/p>\n \u201cHealthcare institutions are deeply risk averse. Any AI first challenger must navigate security, explainability, liability and reimbursement hurdles that are orders of magnitude higher than anything consumer AI faces.\u201d<\/p>\n \u00a0<\/p>\n Improving AI may strengthen Singular Health\u2019s position<\/p>\n