The numbers tell their own story. In 2019, roughly 7% of healthcare organisations reported meaningful AI use. By 2024, AI had become baseline capability across clinical workflows, operations and patient management. FTI Consulting Health director Ryan Nindra, reflecting on conversations at Australian Healthcare Week, says the adoption question has been settled. The one that remains is whether the sector can deploy AI safely at the pace it's now moving.

Beneath the enthusiasm — clinicians wanting relief from admin overload, executives under cost pressure, vendors racing to ship new products — Nindra points to a quieter concern: many organisations are adopting AI faster than they're building the governance to manage it.

The Shadow AI Problem

The clearest symptom is what Nindra calls "shadow AI." When organisations don't offer clear policies or approved tools, staff simply find their own: a clinician summarising consultation notes through an external AI tool, a manager uploading operational data for quick insights, a team automating documentation without formal sign-off. None of these look dramatic in isolation. Collectively, in an environment as data-sensitive as healthcare, they add up to real privacy and compliance exposure — and once patient data leaves controlled systems, Nindra notes, that exposure is hard to undo.

Vendors Are Getting More Focused

Interestingly, the vendor landscape is adapting in a more disciplined direction. Rather than promising to transform healthcare wholesale, many newer AI products at AHW targeted specific operational pain points — automated clinical note generation, custom agents for rostering and service coordination, and dedicated telehealth access for youth mental health. The pitch is narrower, and arguably more credible: return time to frontline workers, not reinvent the system overnight.

Data Is Still the Bottleneck

Even well-targeted tools run into the same wall, though: fragmented data. Patient records, workforce systems and financial platforms across much of the health system still sit in disconnected environments, which is why Nindra sees so many AI pilots succeed in isolation but stall when organisations try to scale them. The technology usually works. The surrounding data ecosystem often doesn't.

What's Next: Agentic AI

Looking further ahead, Nindra flags agentic AI — systems that can autonomously coordinate workflows and make operational decisions — as the next frontier already gaining traction in finance and logistics. Healthcare, he argues, will follow, but the consequences of getting it wrong are considerably higher than in most other industries.

His conclusion is a pointed one for health executives: the organisations that come out ahead won't necessarily be the fastest adopters. They'll be the ones that invest in data infrastructure, assign clear accountability for AI deployment, and build governance into the technology lifecycle from day one.

Read Ryan Nindra's full reflections on LinkedIn: Reflections from AHW 2026: Healthcare's AI surge is outpacing its guardrails

Conversations like these are exactly what Healthcare 2040 Expo (co-located with Australian Healthcare Week) was built for — bringing together the leaders shaping AI, digital health and the future of care across Australia. Join us 17–18 March 2027 at ICC Sydney.

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