GV-1.7 Processes and procedures are in place for decommissioning and phasing out of AI systems safely and in a manner that does not increase risks or decrease the organization's trustworthiness
Processes and procedures are in place for decommissioning and phasing out of AI systems safely and in a manner that does not increase risks or decrease the organization’s trustworthiness. Retirement is a governed event w
4
artefacts
0
held by a system
2
at each review
hard
to go live
Document repository
where the evidence lives
teal = a system already holds it · olive = produced at each review
system holds itEvidence a system already holds
none for this control
periodic reviewEvidence produced at each review
- User and downstream consumer notification records for retired systems · Document repository
- Completed decommissioning records for systems actually retired · Document repository
governing documentDocuments that govern the control
- The documented decommissioning procedure, including retention and legal hold steps · Policy repository / GRC workspace
- Dependency analysis showing what consumed the system before it was withdrawn · Document repository
First move
This control is evidenced by people and documents, not systems. Put the document under version control with an owner and review date, and log each review as a record with reviewer and date. Do not try to automate it.
Common gaps auditors find
- Procedure exists but retirements are executed as an infrastructure ticket outside it
- Model artefacts and training data deleted while a regulatory retention duty still applied
- Downstream consumers discovered the retirement from a failure rather than a notice
Do this for your whole sheet
Paste the rows you run your controls from and get this mapping for every control at once, with the periodic-review ones flagged and a first move per row. No account for the first run.
Build my evidence sheetGV-1.6 Mechanisms are in place to inventory AI systems and are resourced according to organizational risk priorities · GV-2.1 Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are documented and are clear to individuals and teams throughout the organization