Agentic Automation Governance Review (QA)

Agentic Automation Governance Review (QA)

1. 01

   Inventory every automation and AI agent deployed across client accounts

   Document the platform, data access scope, and internal owner for each deployment, as recommended in the wake of undisclosed agent incidents.

2. 02

   Verify that each automation has explicit, documented client approval

   Confirm the client signed off on the specific workflow and data handling, not just a general AI services clause.

3. 03

   Test for silent failure modes, especially in data retrieval and reporting

   Use tools like SchemaGate to detect when text-to-SQL queries return empty results due to permission denials rather than genuinely empty datasets.

4. 04

   Check for unauthorized token or API consumption

   Review usage logs for anomalies, as token theft can inflate costs and compromise client data integrity.

5. 05

   Assess the governance and oversight posture of each automation

   With 45% of executives skipping or limiting AI oversight, ensure your agency has a human-in-the-loop review for high-risk actions.

6. 06

   Evaluate the security of any self-hosted or open-source components

   If using self-hosted LLMs or open-source tools, confirm they are patched and configured with least-privilege access.

7. 07

   Document the audit trail and update the client's risk register

   Record findings, remediation actions, and residual risks to maintain transparency and support compliance requirements.