AI Governance & Compliance Consulting
Australian organisations are, by their own admission, adopting AI faster than they can govern it. That gap is where the real risk sits – not in the AI technology itself, but in the absence of audit trails, access controls and accountability structures around it. Saipals works with Australian businesses, particularly in healthcare, finance and insurance, to build AI governance frameworks that are practical enough to actually be followed – not a compliance document that sits unread until an incident forces everyone to read it for the first time.
What You Get
- AI governance framework design – policy, access controls, audit logging – matched to your industry's regulatory expectations
- Assessment of existing AI tools and vendors already in use across your organisation (including "shadow AI" adoption)
- Board and executive reporting structures that make AI risk visible before it becomes an incident
- Practical, staged implementation – not a framework so exhaustive it never actually gets adopted
Frequently Asked Questions
What does an AI governance framework actually include?
Typically: an inventory of AI systems and vendors in use, data handling and residency policy, access controls, audit logging requirements, human-in-the-loop review points for high-risk decisions, and a reporting structure so leadership has visibility.
We already have staff using AI tools without formal approval – can you help assess that risk?
Yes – this "shadow AI" assessment is one of our most common starting engagements. Most organisations are surprised by how many AI tools are already in use once we map it.
Is this only relevant for large enterprises?
No – small and mid-sized Australian businesses in regulated sectors (healthcare, financial services, insurance) face the same underlying obligations, often with fewer internal resources to manage them, which is where external governance support tends to be most valuable.
How does this relate to your Sovereign AI & Data Residency service?
They're complementary: data residency is about where AI systems and data physically and legally sit; governance is about the policies, controls and accountability structures around how AI is used day to day. Most clients need both.
Can you help us respond to a specific regulatory requirement?
Yes – tell us the framework or regulator context (APRA, Privacy Act, industry-specific) and we'll scope an assessment against your current AI governance posture.