Trustworthy AI operating model
Trustworthy AI has to operate—not merely read well.
The governing unit is the complete AI-enabled business process: data, model, agent, identity, memory, tools, suppliers, people, decisions and downstream effects. A model assessment is necessary in many settings, but it cannot prove that the surrounding process remains authorized while it runs.
Seven phases from visibility to repeatable assurance
- Foundation. Map AI, data, vendors, business processes, owners and jurisdictions.
- System of record. Establish an attributable registry and evidence baseline.
- Guardrails. Translate policy into enforceable identity, data, tool and approval rules.
- Defense. Detect and contain adversarial behavior and runtime deviation.
- Assurance. Convert operating controls into current executive and examiner evidence.
- Protect. Preserve the integrity and controlled exchange of models, xBOMs and evidence.
- Scale. Reuse the operating model across the portfolio without transferring accountability.
What leadership should be able to answer
| Executive question | Required evidence | Accountable decision |
|---|---|---|
| What AI exists and what can it affect? | Current use-case, dependency, data and authority inventory | Whether the exposure is understood well enough to approve |
| What stops a system from exceeding its mandate? | Independent action gates, scoped identities and tested denial paths | Where autonomy ends and human authority begins |
| How will we know behavior changed? | Behavioral baselines, correlated telemetry and outcome checks | Which deviation requires intervention |
| Can we reconstruct a consequential event? | Protected event lineage, versions, policy decisions and execution receipts | Whether evidence is sufficient for response and disclosure |