Change request approvals tied to your CMDB,
rollback decisions in the audit chain.

The reality

What the change advisory board is defending.

• Change request drift: the change record is created in ServiceNow / Jira Service Management, but the actual configuration change happens later, sometimes out of band.
• Approval gates skipped: emergency changes go through a verbal CAB and the formal approval happens after. The audit trail shows retroactive approval.
• Rollback ambiguity: the change is rolled back, but who decided? When? Based on what signal? The post-incident report is a reconstruction.
• CMDB inconsistency: the change record says one CI was changed; the CMDB says another. The reconciliation is manual.

The tailor-made agent loop

From change request to recorded state.

1. Request: the AI agent proposes a typed action against the change record, with the affected CI(s), the rule set, and the system-of-record target (ServiceNow, Jira SM, Cherwell, Ivanti).
2. Stage: the action enters the approval DAG. Standard changes follow the CAB route; emergency changes follow the eCAB route; both are recorded.
3. Approve: a qualified CAB member whose identity differs from the requester signs.
4. Execute: the change management system confirms the write. CMDB reconciliation: change record ↔ actual configuration state.
5. Record: every state change lands in the append-only bi-temporal audit log with hash chain. Rollback decisions are entries; not deletion.

What you save

The pilot is where the numbers become real.

Industry estimates (not a benchmark) for an AI-governed IT change workflow:

• 40-60% reduction in CAB coordinator time on change record chasing.
• 60-80% reduction in post-incident reconstruction time.
• CMDB consistency: the audit trail is the CMDB reconciliation; not a separate process.

Pilot pricing: $1,500 flat for the first three customers. Enterprise quotes for ITIL-aligned or stricter environments.

Pilot

Bring one change type in scope.