AI Workforce / Controls

# Control is part
of the work.
Build identity, permissions, approvals, evaluation, observability, and retained evidence into every AI worker from the beginning.
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AI workerPolicyApprovalMonitorEvidence

Governance by design
Governance defines what a worker may know, what it may do, when it must stop, and what evidence the organization retains.

Six control layers

## Boundaries around every action.

Controls are connected to the role and workflow, not applied later as a generic policy document.

01

### Identity
Every worker operates as a named role with accountable ownership.

02

### Access
Knowledge, systems, and actions are limited to what the role requires.

03

### Approval
Consequential decisions pause at an explicit control gate.

04

### Evaluation
Representative work tests quality, policy adherence, and failure behavior.

05

### Observability
Activity, errors, latency, decisions, and outcomes remain visible.

06

### Escalation
Missing context, uncertainty, and exceptions follow a defined stop path.

Authority model

## Stronger consequence. Stronger control.
Read access and irreversible action should never carry the same operating authority.

Low
Read + analyze
Scoped access

Moderate
Draft + recommend
Reviewable output

High
Update + communicate
Approval gate

Critical
Commit + irreversible action
Explicit authority

Governance lifecycle

## Define. Evaluate. Control. Assure.

- 01

### Define authority
Document the role, systems, data, actions, risk level, owners, approvals, and evidence requirements.

- 02

### Evaluate behavior
Use representative tasks and scenarios to test expected work, edge cases, policy adherence, and failure response.

- 03

### Control production
Apply access boundaries, human approvals, monitoring, exception handling, and revocation paths.

- 04

### Assure continuously
Review production performance, investigate exceptions, update controls, and document operating evidence.

Production evidence

## Trust needs a record.
Visible activity makes investigation, evaluation, coaching, and carefully expanded responsibility possible.

01Inputs and retrieved context
02Actions and system changes
03Approvals and escalations
04Errors and exception handling
05Evaluation and quality results
06Business outcomes and cost

Deployment-specific assurance
Security architecture, data handling, retention, and assurance requirements are evaluated for each deployment. We do not represent certifications or controls that have not been formally verified.

Governed from the beginning

## Design the authority before deployment.

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