Secure AI operating model
What is Secure AI operating model?
The structure, roles and processes that decide who proposes, approves, builds, secures and monitors AI across an organisation.
A strategy says what will happen. An operating model says how the organisation delivers it. It defines a governance forum, named roles such as system owner, AI security lead, privacy lead, engineering lead and audit lead. It also outlines decision rights at each step and handoffs between teams. Finally, it covers skills, training and funding.
A secure AI operating model is essential to any secure AI rollout, as it defines common standards across the entire AI lifecycle and all business units.
Why organisation needs Secure AI operating model?
AI cuts across teams that rarely share a process. Business units buy tools, engineers build, security reviews, privacy assesses, risk reports. Without agreed handoffs and a single source of truth, reviews get skipped or repeated and nobody owns a system once it’s live.
APRA’s April 2026 letter expects ownership and accountability across an AI system’s whole lifecycle, plus staff training on secure use. A clear model also speeds up approvals, because each team knows its step and deadline.
How to build secure AI operating model?
- Map who touches AI today and where decisions stall.
- Set up a governance forum with authority to approve and stop.
- Assign roles and decision rights for each lifecycle step.
- Define handoffs, time targets and escalation paths.
- Train people in their roles and review at least quarterly.
