Identity & access
Define who can use the system, what they can reach and which actions require stronger authorization.
Security & privacy
Security and Privacy by Design
A secure AI environment must protect more than files. Identity, permissions, data, models, knowledge, agents, logs, retention and infrastructure all shape the real security boundary.
Security architecture
Minimize, separate, protect and document
The exact controls depend on the information, workflow, environment and consequences involved.
Data & knowledge
Classify information, preserve permissions, minimize unnecessary exposure and control which repositories can be used.
Models & agents
Evaluate model suitability, define tool permissions and constrain what intelligent systems are allowed to do.
Logs & retention
Decide what must be recorded, how long it should remain and who can review the evidence.
Sovereign architecture
A sensitive workload may require more than enterprise cloud controls
Depending on risk, contractual requirements, intellectual property, data residency, operational continuity or institutional policy, a workload may be better suited to a private, on-premises, hybrid or specially governed environment.
AFA does not treat any single deployment model as universally superior. The environment should match the workload.
The right question is not “Is this AI secure?” It is “What controls are appropriate for this workload, information and responsibility?”
Engagement
Design assurance around the real system
Security is scoped from the beginning and revisited as the system changes.
Classify
Identify information sensitivity, users, external dependencies and consequences.
Architect
Map identity, access, models, data flows, retention, logs and infrastructure.
Validate
Test expected controls, failure modes and operating boundaries.
Operate
Document ownership, monitoring, change management and human escalation.
Continue the journey