Human oversight for AI agents
Human oversight gives qualified people the information, authority, and controls to monitor an AI system and intervene in consequential actions. Effective oversight defines the conditions for review, the responsible role, the decision options, and the evidence retained.
KLA turns a policy outcome into a controlled handoff. The original action pauses, an authorized reviewer receives a complete Decision Request, and the same execution resumes or stops after the decision.
- 01Policy outcomerequire_approval
- 02Controlled holddr_01K0A80D · awaiting review
- 03Named reviewerSenior underwriter
- 04Resolved actionapproved · rationale captured
- Work item
- Decision Request
- Operator surface
- Decision Desk
- Routing basis
- Risk, role, authority, and policy
- Recorded result
- Decision, rationale, and timestamps
01: Concept
How human oversight works in operation
Oversight works when reviewers receive the right decisions, enough context to judge them, and real authority over the outcome.
Human oversight gives qualified people the information, authority, and controls to monitor an AI system and intervene in consequential actions. Effective oversight defines the conditions for review, the responsible role, the decision options, and the evidence retained.
- Route review by risk
- Policy identifies the actions that need review using thresholds, data sensitivity, customer impact, confidence, and operating context.
- Assign a qualified role
- Decision Requests route to named teams or roles with the authority required for the action, tenant, and environment.
- Present decision-ready context
- The reviewer sees the proposed action, policy reasons, source evidence, agent identity, authority, and relevant history in one review surface.
- Bind the decision to execution
- Approval resumes the held action. Rejection stops it. The reviewer identity, rationale, timestamps, and resulting effect stay connected.
02: KLA implementation
How KLA implements human oversight
KLA makes human review part of the runtime path so the handoff carries operational authority and produces a complete record.
- 01
Define oversight conditions
Policy specifies which actions pause, which reviewer roles can decide, and any service-level or separation-of-duties requirements.
Output · Review policy
- 02
Create a controlled hold
A require approval outcome persists the Decision Request and prevents the proposed action from committing while review is open.
Output · Held action
- 03
Route a complete decision packet
Decision Desk presents the reason codes, proposed tool call, evidence, authority, and prior events to an eligible reviewer.
Output · Decision-ready review
- 04
Apply and record the outcome
KLA resumes, stops, or reroutes the action and adds the reviewer decision and rationale to Execution Lineage.
Output · Resolved Decision Request
Example · Credit decision
A material decision reaches the right reviewer
A credit-review agent proposes a limit increase outside its delegated band. Policy routes the action to a senior underwriter with the supporting record.
The reviewer acts on the exact proposed write and its policy context. The final state remains linked to the person, rationale, and evidence available at decision time.
- Action heldheld
core-banking.update-limit · proposed increase EUR 35,000
- Decision Request routedreceived
Senior underwriter · EMEA credit operations · SLA 30 min
- Reviewer approvedapproved
Income evidence verified · exposure remains within portfolio limit
- Execution resumedrecorded
Original write completed · before and after state recorded
04: Evidence record
What KLA records for review
Each oversight action shows who could decide, what they saw, what they chose, and what happened next.
| Record layer | Captured evidence | Review purpose |
|---|---|---|
| Routing basis | Matched policy, risk attributes, reviewer role, queue, and service level | Explain why human review was required and where it was sent |
| Reviewer authority | Reviewer identity, role, eligibility, tenant, and separation-of-duties checks | Show that the person was authorized to decide |
| Decision packet | Proposed action, reason codes, evidence references, relevant history, and tool parameters | Reconstruct the information available during review |
| Resolution | Decision, rationale, timestamps, comments, and resulting execution state | Connect human judgment to the operational outcome |
05: Connected controls
Follow the complete governed action path
The four concepts operate together across one action. Continue with the control layer closest to your next question.
06: FAQ
Questions about human oversight
Definitions, runtime behavior, integration, and evidence boundaries for this control layer.
- What does human oversight mean for an AI agent?
- Human oversight is the operating model that gives qualified people visibility into consequential agent actions and the authority to approve, reject, interrupt, or escalate them. The model defines when review occurs and what evidence it produces.
- Does every agent action need human approval?
- Oversight can be risk-based. Routine actions can proceed under published policy while material, exceptional, low-confidence, or sensitive actions create Decision Requests for a qualified reviewer.
- What information does a reviewer see in Decision Desk?
- A Decision Request can include the proposed action, agent and principal, tool parameters, policy outcome and reason codes, supporting evidence, relevant history, and the authority required to decide.
- What happens to the agent while review is open?
- The governed action stays in a controlled hold. An approval resumes the original action from the checkpoint. A rejection stops it. Timeouts and escalations follow the configured operating policy.
- How is human oversight proven later?
- Execution Lineage connects the Decision Request, reviewer identity and authority, evidence presented, decision, rationale, timestamps, and downstream result in one replayable record.
Start with one action
Design the oversight path for one high-stakes decision
Define the review trigger, reviewer authority, decision packet, service level, and evidence record with the KLA team.