If you’re a healthcare leader, you’ve heard the promises of AI a hundred times over. Faster diagnosis. Predictive insights. Reduced admin. None of this is news anymore. But here’s what isn’t being said: when AI becomes part of the decision-making process, it will change the fundamental ways in which our teams now function.
Our multidisciplinary teams; doctors, nurses, allied health professionals, and managers, are designed to collaborate with people. Not with an algorithm. And that’s where the real challenge of the practicalities lie. Unless leaders prepare for that reality, all these benefits of AI could just end up lost in translation.
AI as a “Team Member”
Australia is already seeing early integration of AI across health:
- Diagnostic imaging pilots are using AI to flag cancers earlier and reduce reporting delays.
- Predictive analytics tools are being trialled in hospitals to anticipate patient deterioration before it happens.
- Primary care systems are experimenting with AI to identify at-risk patients for earlier interventions.
When these systems recommend a pathway or flag a risk, they’re doing more than processing data. They’re actively influencing decision-making. That influence then raises some uncomfortable but important questions:
- Who gets the final say when AI and a senior clinician disagree?
- Will staff feel confident challenging or trusting AI advice?
- Where does accountability sit if AI plays a role in a poor outcome?
These aren’t IT questions. They are clinical governance questions. And right now, very few boards or executive teams have the practical frameworks to answer them.
The Culture Gap
The real risk of AI in healthcare isn’t actually technical failure. It’s cultural failure. Take the My Health Record as a nice reminder. On paper, it was a world-class digital health initiative. But uptake faltered because clinicians and patients weren’t fully brought into the “why” and “how” of using it.
AI risks repeating the same story. If staff don’t understand where AI fits in their practice, mistrust and resistance will follow.
Picture this scenario:
- An AI system detects the early signs of sepsis.
- A junior nurse hesitates to escalate, unsure whether their own judgment or AI should take priority.
- The senior doctor dismisses the alert, assuming it’s another false positive.
In this case, the AI has worked as intended. But the team hasn’t.
This is the hidden gap leaders need to close. AI can only be effective if the people around it know how to work with it, question it, and balance its input against their own expertise.
The study on oncology MDTs highlighted this same dynamic: AI tools may be technically sound, but their effectiveness depends on whether teams trust and integrate them into decision-making. Without cultural alignment, AI becomes noise rather than value.
Governance for Non-Human Colleagues
Healthcare governance has always been designed for people. Now we’re entering a world where one of the most influential “voices” in the room isn’t human at all. Australian health leaders face a new frontier: governing teams that include non-human healthcare colleagues.
That forces leaders to rethink some fundamentals:
- How do we integrate AI into team dynamics without undermining confidence and professional judgment?
- How do we prevent clinicians from blindly deferring to AI outputs?
- What accountability structures are needed when part of the decision comes from a system?
As pilots expand, from imaging and pathology to mental health triage and virtual care, Australian healthcare leaders will need to address these questions sooner rather than later.
This is uncharted territory. And it will demand the same rigour we expect from any other part of clinical governance.
What Success Looks Like
If we get this wrong, AI could fracture care teams, sow mistrust, and put patients at risk. But if we get it right, the impact could be transformative. AI could take pressure off staff, sharpen decision-making, and give teams the confidence to act earlier and more effectively.
The future of healthcare teams won’t be about humans versus machines. It will be about humans and AI, side by side.
Where Leaders Should Start
- Treat AI as a governance challenge not just an IT project.
- Invest in culture, help staff learn how to work with AI and how to integrate it into their teams, not fear it.
- Be clear on accountability. Don’t leave room for any grey zones where AI is involved in clinical decisions.
- Communicate openly, because patients and staff need complete transparency about what AI can and can’t do.
AI is already knocking on the door of every healthcare organisation, from hospital pilots to diagnostic imaging and predictive analytics. The question isn’t whether it will join your teams, it’s whether your culture and governance will be fit-for-purpose when it does. AI is unlikely to replace clinicians in MDTs. But, it will become a contributing “voice.” The challenge, and opportunity, for leaders is ensuring that voice strengthens, rather than destabilises, care delivery.
Leaders who start preparing now will set their organisations up not just to adopt AI, but to truly integrate it into the way multidisciplinary care teams work.
Join us LIVE for a powerful 2 hr webinar | in partnership with the Australian Institute of Digital Health on Strengthening Clinical & Digital Governance in the Age of AI | 30 Oct
