Recommendation proposed
The AI system provides its proposed action with available context and source information.
PROCESS / END TO END
A decision journey you can inspect
Follow an AI-assisted action from registration to governance checks, human review, evidence capture, and subsequent assurance.
Five stages of accountable AI
The workflow is presented in plain language so technical and nontechnical visitors can understand their roles.
- 01ConnectIdentify the AI system and owner
- 02GovernApply policy and risk controls
- 03OverseeEscalate sensitive cases to humans
- 04VerifyCollect evidence and trace context
- 05AssureReview outcomes and remediate gaps
A practical decision example
Consider an AI-assisted credit recommendation. The model proposes a result, but an organization still needs accountable rules and approval authority.
Policy condition met
A control flags a high-impact or low-confidence decision for review.
Human review
An authorized reviewer examines evidence and makes an accountable determination.
Decision captured
Relevant timestamps, policy versions, reason codes, and review references are retained according to policy.
Exception management
A disputed, incomplete, or failed decision can be investigated through a defined process.
Not autonomous enforcement
A public workflow diagram alone cannot establish that a live customer system is controlled.
Where human judgment belongs
Oversight should be proportional to the risk of the decision. A low-impact workflow may follow an approved automatic rule; a material adverse decision should have clear review and escalation provisions.
Follow one decision from trigger to review
Consider a proposed AI-assisted action that exceeds a policy threshold. This example describes a review pattern, not an assertion of an active customer integration.
Before the decision
The triggering system provides a minimally necessary request with its purpose, asset identifier, owner, and relevant context. A missing or untrusted identity must be treated as an exception rather than assumed to be valid.
During the decision
A defined policy version determines whether the action is permitted, blocked, or referred for human review. The reviewer needs the underlying reason, information needed to decide, and a visible record of their own authorization.
After the decision
The resulting outcome should be linked to the actor, time, governing rule, evidence references, and any override rationale. Later correction should be recorded as a new event, not by silently replacing the earlier decision.
This scenario is illustrative. The exact approval model depends on sector requirements, customer policy, and verified integrations.