Secure AI architecture review
What is secure AI architecture review?
A technical evaluation of an AI system’s architecture against three questions: is it secure, does it perform and will it scale. A design review checks a proposal for security flaws before build. An architecture review looks at a detailed or running architecture more broadly. Reviewers assess identity and access, data paths, model hosting, integrations, response time, cost per request, capacity limits and failure modes.
The output is a report that outlines a target architecture, highlighting the prioritised fixes needed to achieve it.
Why organisations need secure AI architecture review?
Pilots hide problems. A system that works for twenty users can fail at four hundred through slow responses, vendor rate limits or runaway cost. Security gaps also widen as integrations grow.
APRA’s April 2026 letter expects active management of concentration risk, including tested exit options for critical AI providers. Finding those limits before rollout costs far less than an outage in production.
How to build secure AI architecture review?
- Document current architecture and expected load.
- Assess security: identity, secrets, trust boundaries, logging.
- Assess performance: response time, accuracy, cost per request.
- Assess scalability: capacity, vendor limits, failover.
- Prioritise fixes and agree a target architecture.
