Why AI Governance Should Be the Starting Point for Public Sector AI

 AI is moving quickly — and so are governments. Across Australia and the Pacific, public institutions are adopting artificial intelligence for service delivery, planning, regulation, and decision-making.

But as the tools evolve, so must the systems around them. Governance is no longer an afterthought — it’s the starting point 

  What we mean by governance

AI governance refers to the frameworks, policies, and institutional processes that shape how AI is introduced, managed, and held accountable. It includes:

• Clear roles and responsibilities for oversight
• Principles around ethics, transparency, and fairness
• Procurement rules that reflect national priorities
• Data and infrastructure choices that align with public interest

It’s not just about technical compliance — it’s about ensuring AI works within the social contract.

Why now

Governments are under real pressure to adopt AI — to improve services, increase efficiency, and demonstrate innovation. But as AI systems are embedded into public institutions, the consequences of weak governance become more visible.

Without clear frameworks, governments face:

• Difficulty explaining or justifying automated decisions
• Exposure to legal and ethical risks
• Dependency on external platforms and infrastructure
• Public trust issues — especially when systems make mistakes

In both large and small jurisdictions, these challenges are starting to emerge.

Australia and the Pacific: different contexts, shared imperatives

In Australia, formal policy guidance is beginning to take shape. The federal AI in Government framework is an early step, and state-level initiatives are also evolving.

In the Pacific, many governments are working from earlier points — updating digital strategies, considering national AI policies, and reviewing institutional readiness.

But the imperative is the same: to ensure AI is introduced in a way that aligns with national goals, respects local values, and serves the public good. 

What’s needed 

AI governance isn’t a one-size-fits-all framework. It’s a set of questions each government must answer in its own context:

• Who is responsible for AI oversight?
• What risks are we prepared to accept — and which are off-limits?
• How do we protect local control over data and decision-making?

These are not only technical questions. They are questions of policy, sovereignty, and public leadership. 

Final thought

AI doesn’t arrive in isolation. It lands inside institutions — with all their strengths, gaps, and public responsibilities. Governance is how we make sure those institutions remain accountable, capable, and trusted.

It’s not about slowing AI down. It’s about making sure it moves in the right direction.

We’ll be sharing more reflections and guidance on AI governance in Australia and the Pacific over the coming months.