A Research Fellowship – Mapping Responsible AI in Healthcare: Evaluating Guidelines and Leadership Perspectives

Start Date

5 May 2025

End Date

23 July 2026

Project Participants

University of South Australia

Status: Completed

Tags: AI governance, artificial intelligence (AI), capability uplift, clinical governance, health system, healthcare leadership, hospital, innovation, workforce

Opportunity 

Artificial intelligence (AI) is increasingly being adopted across healthcare, yet healthcare organisations face uncertainty about how AI should be governed, implemented and used safely in clinical practice. A learning from the PreHaRM experience was that when healthcare leaders and decision makers are uncertain of how AI technologies should be assessed, governed and implemented this can result in delays to the adoption of potentially beneficial AI-enabled technologies. 

This fellowship project investigated how senior healthcare professionals and executives interpret and apply Responsible Artificial Intelligence (RAI) guidance in real-world settings with the aim of identifying barriers to translating policy into practice.

Project Objectives  

The research project examined Australian government AI publications, then sought to how these were understood by Australian health service leaders to identify points of convergence and disconnect between policy and practice. By exploring healthcare leaders and staff perceptions in relation to Responsible AI in healthcare, this helps illuminate where healthcare professionals require additional support and training to adopt AI safely and effectively.

By cross-referencing a desktop review of Australian Commonwealth Government AI guidance documents with interviews of senior healthcare leaders from across Australia, the project identified four key challenges affecting AI adoption: responsibility versus accountability, AI governance cascade, platform and context alignment, and workforce education and training. The research produced practical evidence to inform future governance frameworks, policy development and implementation models. 

The project contributes toward an evidence-based foundation for responsible AI adoption in Australian healthcare. The findings identify AI implementation barriers and governance gaps that suggest the need for improving workforce capability and strengthening AI governance in health services at multiple levels. Addressing these may help accelerate safe deployment of AI technologies that can improve patient outcomes and health system performance. 

Integrity, Excellence,
Teamwork and Authenticity

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