Artificial intelligence is playing an increasingly prominent role in reshaping New Zealand’s healthcare ecosystem—from how clinicians are trained to how patients receive support and early diagnoses. At the heart of this transformation is the Auckland Bioengineering Institute (ABI), which is leading research into AI-powered tools aimed at delivering precision healthcare and improving patient literacy.
Diana Siew, Strategic Relationship Manager at ABI, explained that AI is proving particularly effective in healthcare education. “There’s a lot of opportunity in using AI in simulation and virtual reality environments,” she said, referring to how these tools are creating immersive experiences for clinicians. These range from basic procedures such as inserting catheters to highly complex surgical planning.
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Meanwhile, AI is helping move diagnostics out of the clinic and into more accessible settings. Toku Eyes, co-founded by Dr Ehsan Vaghefi, uses AI to analyse retinal images for early signs of chronic disease. “This non-invasive method can detect early signs of diseases such as cardiovascular disease and chronic kidney disease by identifying subtle changes in the blood vessels of the retina,” Vaghefi said. Toku’s tools are designed to work at scale, particularly in underserved areas, and the company has raised \$13 million to support its expansion into North America.
Siew said ABI’s own research focuses on diagnostic support and digital tools for patient self-management. A key project is the development of DINA—Digital Interactive Navigator Assistant—which is being designed to help individuals manage chronic conditions such as diabetes. “DINA can be integrated with wearables to capture biometrics, activity and blood sugar levels,” she said, adding that the system can be customised to reflect cultural needs and improve engagement within specific communities.
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These advances are being supported by long-standing international collaborations. ABI is recognised globally for its work in computational physiology, particularly the development of digital humans—detailed simulations of human biology built using mathematical models. Led by Distinguished Professor Sir Peter Hunter, the digital human project has received funding from Horizon Europe, the NIH, and New Zealand’s government, and forms the foundation for future digital twin technologies aimed at precision health.
However, the use of AI in healthcare also brings new challenges, especially around data integrity and evolving algorithms. “Transparency around training and validation datasets is important,” Siew said, pointing out that AI tools need to reflect the population they serve. Tools that continue to learn after deployment must be monitored closely to ensure they remain accurate and safe. Most regulators currently allow only “locked” algorithms to be used in clinical settings—those that don’t change over time without further regulatory approval.
New Zealand’s AI healthcare ecosystem is still growing, but its focus on personalised, accessible, and culturally responsive solutions is already drawing global attention. With researchers, startups and institutions working in tandem, the country is positioning itself as a testbed for next-generation healthcare innovation.
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Diana Siew, Strategic Relationship Manager at ABI, explained that AI is proving particularly effective in healthcare education. “There’s a lot of opportunity in using AI in simulation and virtual reality environments,” she said, referring to how these tools are creating immersive experiences for clinicians. These range from basic procedures such as inserting catheters to highly complex surgical planning.
One of the most advanced applications of this is being developed by New Zealand startup Formus Labs. The company has automated the traditionally manual and time-consuming task of surgical planning for joint replacements. “Formus has eliminated days of engineering and hours of surgeon time,” said CEO Dr Ju Zhang, pointing to the company’s AI software that generates personalised surgical plans from patient CT scans. With over 3,000 surgeries completed in Australia, Formus is now expanding into the US and Asia-Pacific, including early trials in India.
Also read: Replacing human with AI is easy, but is it good for the company?
Meanwhile, AI is helping move diagnostics out of the clinic and into more accessible settings. Toku Eyes, co-founded by Dr Ehsan Vaghefi, uses AI to analyse retinal images for early signs of chronic disease. “This non-invasive method can detect early signs of diseases such as cardiovascular disease and chronic kidney disease by identifying subtle changes in the blood vessels of the retina,” Vaghefi said. Toku’s tools are designed to work at scale, particularly in underserved areas, and the company has raised \$13 million to support its expansion into North America.
Siew said ABI’s own research focuses on diagnostic support and digital tools for patient self-management. A key project is the development of DINA—Digital Interactive Navigator Assistant—which is being designed to help individuals manage chronic conditions such as diabetes. “DINA can be integrated with wearables to capture biometrics, activity and blood sugar levels,” she said, adding that the system can be customised to reflect cultural needs and improve engagement within specific communities.
Also read: 'AI isn’t overhyped—it’s underhyped': Prosus CEO on betting big, building bold
These advances are being supported by long-standing international collaborations. ABI is recognised globally for its work in computational physiology, particularly the development of digital humans—detailed simulations of human biology built using mathematical models. Led by Distinguished Professor Sir Peter Hunter, the digital human project has received funding from Horizon Europe, the NIH, and New Zealand’s government, and forms the foundation for future digital twin technologies aimed at precision health.
However, the use of AI in healthcare also brings new challenges, especially around data integrity and evolving algorithms. “Transparency around training and validation datasets is important,” Siew said, pointing out that AI tools need to reflect the population they serve. Tools that continue to learn after deployment must be monitored closely to ensure they remain accurate and safe. Most regulators currently allow only “locked” algorithms to be used in clinical settings—those that don’t change over time without further regulatory approval.
New Zealand’s AI healthcare ecosystem is still growing, but its focus on personalised, accessible, and culturally responsive solutions is already drawing global attention. With researchers, startups and institutions working in tandem, the country is positioning itself as a testbed for next-generation healthcare innovation.
Also read: India emerges as AI patent powerhouse, faces challenges in quality and approval timelines
(Edited by : Akanksha Upadhyay)
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