Healthcare AI is having a moment. In the first half of 2025, AI-enabled startups captured 62% of digital health venture funding, which totalled US$6.4 billion. Nine of the eleven biggest deals went to AI companies, and some hospitals are reporting 90% usage rates for certain AI tools.
This investment reflects a sector under pressure. Australian hospitals are facing wage pressures, soaring energy costs, and high interest rates on debt. Health insurers are battling over reimbursements that aren’t keeping pace with operating costs. Mental health and community healthcare providers are stretched thin managing growing caseloads with static government funding.
Meanwhile, more Australians are living with chronic conditions that require ongoing management than ever before. This is driving a shift from fee-for-service to bundled payment models, meaning providers now manage entire patient populations efficiently, not just individual visits.
Healthcare providers are consistently being asked to do more with less. AI offers a path forward: automating routine tasks, monitoring populations between visits, and helping stretched teams work more efficiently.
But rather than rushing to market with premature AI products, MasterCare is taking a considered approach. One that prioritises getting the foundations right before promising transformation.
Our approach to AI
Twenty-five years of building healthcare software has taught us that the solutions that stick aren’t always the ones that get the most headlines. Plenty of “revolutionary” software platforms fail to perform, particularly in Australia, because the vendors aren’t sector specialists, and don’t grasp our regulatory framework or understand how a headspace centre operates compared to a private hospital.
Rather than betting on a single AI vendor in a rapidly changing landscape, we’re building with multiple AI tools internally, including Co-Pilot, ChatGPT and Claude, because each has different strengths. We’re purposefully maintaining flexibility instead of vendor lock-in.
This multi-vendor approach requires robust security foundations. We’re one of only three healthcare brands in Australia that meet the highest interoperability and security standards, and AI implementation doesn’t alter that commitment.
Our approach for protecting commercial and customer information includes using private AI environments, vectorisation to scrub personally identifiable information, and maintaining domestic data storage.
And when it comes to using AI to enhance our products, we’re innovating responsibly. That means thoroughly testing technology internally first. We’re developing locally trained large language models (LLMs) trained on our product knowledge, and our customer support teams are testing AI automation through parallel runs that compare time taken, quality of work, and validation against traditional methods.
3 areas where automation could make a difference
Our end goal is to use AI to help our customers do more with less. To work smarter, not harder. We firmly believe a responsible, well-managed AI adoption strategy will help us achieve that.
To ensure we’re solving real problems, not just demonstrating technical possibilities, we’re collaborating with clinicians, administrators, and care teams to understand where and how automation could genuinely make their jobs easier. Three areas consistently emerge in these conversations: AI scribing, intelligent triage, and chronic disease monitoring.
- AI scribing tools address one of clinicians’ biggest time drains. Instead of your clinicians spending precious consultation time typing notes, voice-to-text AI technology can capture those conversations accurately, filter out small talk, and extract relevant clinical information for your MasterCare+ records. We’re exploring integration with multiple scribe providers to give our customers a choice, with some even generating referrals and suggesting diagnoses.
- Intelligent triage could vastly improve appointment preparation. AI asks patients pre-determined qualification questions and evaluates the responses. Whether in GP, psychology, or specialist contexts, better patient information before a consultation reduces wasted time spent gathering background and can improve care quality.
- Chronic disease monitoring could be transformative for conditions like diabetes, which require daily management. Typically, clinicians only see patients every few months and rely on their recall or basic device downloads for data. With AI integration into glucose monitors, patients could be continuously monitored, provided with real-time coaching when levels spike, and notified about any spikes or concerning patterns. Not only could this empower patients throughout their health journey and help maintain engagement between appointments, but it could also provide clinicians with more detailed and accurate patient data.
We’re targeting the first half of 2026 for releasing these advanced customer-facing AI applications. This timeline reflects our approach – we’re ready to adopt AI meaningfully, while maintaining the responsible approach our customers expect from us.
If you’d like to find out more about how we’re shaping the future of Australian healthcare, book a discovery call with our team today.
