Governance

Govern automation before autonomy becomes risk.

Create a unified view of ownership, controls, policy adherence, audit trails, risk signals, approvals, and human oversight across bots, agents, and automated workflows.

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As automation becomes more autonomous, governance becomes more important.

Enterprises need to know what each bot or agent can access, what decisions it can make, when it needs human approval, and whether it is operating within policy.

Without a unified governance layer, risk accumulates silently. Audit trails are incomplete. Ownership is unclear. Policy violations go undetected until they become compliance issues.

Governance gaps as autonomy increases

No single view of what agents can accessHigh
Approval checkpoints inconsistently appliedHigh
Audit trails incomplete across platformsMedium
Agent permissions not regularly reviewedHigh
Policy adherence not systematically trackedMedium
Human override patterns not monitoredLow

Governance Dashboard

Governance Dashboard · 3 items need attention
Active Risk Events
3
2 critical, 1 medium
Policy Violations (MTD)
7
+3 vs prior month
Audit Trail Coverage
94%
6% gap — 4 agents
Owner Coverage
89%
11 workflows unowned
Active Risk Events
CriticalProcurement Agent accessed vendor payment API without approval
CriticalHR data sync bypassed human review checkpoint
MediumCustomer triage agent exceeded permitted scope
Approval Checkpoint Status
Invoice >$10K approval
100%
New vendor onboarding
100%
Employee data access
72%
Customer data export
98%

What Governance tracks.

Automation ownership

Track which teams and individuals own each bot, agent, and workflow — and ensure coverage across the full automation estate.

Agent permissions

Monitor what each AI agent can access, what actions it can take, and whether permissions align with current policy.

Approval checkpoints

Track where human approvals are embedded in automated workflows and whether they are being triggered correctly.

Risk events

Surface governance risk signals: policy violations, unusual access patterns, control failures, and escalation triggers.

Audit trails

Maintain complete, tamper-evident records of automation decisions, actions, data access, and human interventions.

Policy adherence

Monitor whether bots and agents are operating within defined boundaries, access controls, and workflow policies.

Control failures

Detect when governance controls — approval gates, access restrictions, or override policies — fail or are bypassed.

Decision traceability

Track AI agent reasoning paths, decision inputs, tool selections, and outcome quality for audit and review purposes.

Key governance metrics.

Policy violations
Automations operating outside approved policies and rules
Approval checkpoints
Human approval steps triggered and completed per workflow
Risk events
High-risk automation actions flagged for governance review
Audit trail completeness
Coverage of full audit logs across automated processes
Escalation events
Governance-triggered escalations requiring manual action
Control failures
Governance controls that failed or were bypassed
Human override rate
How often humans override or reject automated decisions
Owner coverage
Percentage of automations with an assigned responsible owner
Sensitive data access events
Automations accessing PII, confidential, or restricted data
Compliance evidence completeness
Readiness of audit evidence for regulatory requirements
High-risk workflow count
Workflows flagged as high-risk by active governance rules
Governance review status
Outstanding reviews, approvals, and sign-off completion

Related platform capabilities

ROI
Governance supports the reliability of value-creating automations.
Observability
Observability surfaces the operational signals that feed governance.
Integration
Governance data comes from integrations across all platforms.

Strengthen automation governance.

Build a clear view of ownership, controls, risk, and compliance across every bot, agent, and automated workflow.

Strengthen automation governance