Initiative overview
The main objectives are to support safer care, reduce manual work, and improve how health information flows across the system. This includes testing practical AI tools that can summarise information, detect patterns and help people find what they need more easily. The initiative also focuses on strong governance, transparency and safeguards so that AI is used in ways that protect privacy and maintain public trust. Over time, the initiative is expected to grow from early exploration into more structured, systemwide solutions. Future work includes developing standards, guidance and processes that help health organisations adopt AI safely and consistently. As confidence increases and successful solutions are identified, the initiative could scale to support national services, clinical environments and consumerfacing tools. The initiative continues to evolve based on feedback from the sector, advances in technology and lessons from early trials. This iterative approach helps ensure that the Agency’s work remains aligned with community expectations, government policy and the real needs of clinicians and consumers.
Results, outcomes and impacts
Looking ahead, the initiative is expected to deliver broader impacts across the health system as tools mature and adoption increases. These expected outcomes include reduced administrative burden, faster access to relevant information, and more consistent application of policy and standards. The initiative aims to support safer and more connected care by ensuring people have access to clearer, more timely insights. Future evaluations are expected to include measurable improvements such as reductions in processing time, increased accuracy of information outputs, and broader uptake of AI supported services within partner organisations. These impacts will help guide where AI investments can deliver the greatest value across the national health
Challenges and lessons learned
From this work, several lessons have emerged. One is that early and ongoing engagement with clinicians, consumers and technical specialists helps build trust and leads to better solutions. Another is that high-quality data and clear policies are essential for safe AI use. A final lesson is that AI initiatives need clear problem definitions—tools work best when they are targeted at specific, well understood tasks rather than broad ambitions. Success in initiatives like this depends on a few conditions: strong governance, access to reliable data, skilled teams, clear communication, and a willingness to learn and adapt. Support from leadership and partners across the health system is also critical to ensure AI is used responsibly and delivers real benefits for clinicians and consumers.
