There's a palpable appetite for AI across the Australian Public Service (APS).

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With agencies exploring how AI can help them deliver better outcomes, quicker and more efficiently, enthusiasm grows. However, so does caution.

Many public sector leaders recognise that while AI offers great potential, it also introduces new ethical, operational, and security-related risks that can't be ignored.

What's emerging now is opportunity in a more pragmatic phase of AI adoption. Instead of focusing on bold, citizen-facing services, they're looking internally, at quieter but equally powerful projects that improve productivity through automating administrative tasks, streamlining case management, and optimising resource allocation to deliver immediate value.

Agencies are aiming to do more with less.

But for this promise to last, AI needs lasting capability built on trust, transparency, and visibility across its lifecycle.

Launching an AI pilot is not the hard part. The real challenge is moving from isolated successes to a sustainable, scalable ecosystem.

Without the right foundations, AI initiatives risk becoming siloed experiments failing to deliver long-term value.

That foundation starts with observability. Just as modern digital infrastructure depends on continuous monitoring and feedback loops, AI capability depends on knowing what's happening across the full pipeline. Organisations need practices to maintain visibility into how AI systems perform, whether they are performing as intended, where data comes from and where it goes , and how models evolve over time.

Without solid footing and a clear path to scale, AI will remain stuck to pilots with little predictability of success. Even successful pilots can create hidden long-term risks - goal drift, fragile dependencies, and loss of oversight - entrenching bias, inefficiency, and governance failures as they scale. But with a strong........

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