The short answer
Paloren provides an AI governance checklist that turns policy into observable controls for real workflows.
Use an AI governance checklist that covers use-case inventory, access rules, approvals, quality checks, monitoring, incident response and audit evidence. Assign each control a named owner and review date.
What this can change for your team
- Practical controls
- Named owners
- Audit evidence
01 / 02AI governance checklist
What should an AI governance checklist include?
Use cases, access, approvals, quality and audit.
How we make this work
A practical checklist starts with a use-case inventory. It then defines access boundaries, approval routes, quality checks, monitoring, incident response and audit evidence. Each control needs a named owner and a review date. This prevents governance from becoming a document nobody can follow.
- Use-case inventory
- Access and approvals
- Quality and audit
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How often should governance be reviewed?
Quarterly or after major changes.
How we make this work
Review governance at a set cadence and whenever systems, data or workflows change materially. If a control adds friction without reducing risk, redesign it. Paloren recommends quarterly reviews for active systems and event-triggered reviews after source changes or incidents.
- Quarterly review
- Event-triggered review
- Control redesign
Make the next decision
What to do with this
Checklist
Control matrix
Owner register
Audit evidence
Review schedule
Incident route
- 01
Inventory use cases
List systems and decisions.
- 02
Set access rules
Limit by role and field.
- 03
Define approvals
Name owners for consequences.
- 04
Audit and review
Track evidence and changes.
| Stage | What it changes |
|---|---|
| Inventory use cases | List systems and decisions. |
| Set access rules | Limit by role and field. |
| Define approvals | Name owners for consequences. |
| Audit and review | Track evidence and changes. |
Which use cases need controls?
Tell Paloren the systems, data and approvers.
Reply from the team within one business day. No deck, no technical brief needed.
Before we begin
Questions we get asked, answered with numbers
Do we need governance for one tool?
If it accesses business data or affects decisions, yes.
What is the first control?
An inventory of AI use cases, data and decisions.
Who owns governance?
Name a business owner and a technical owner for each workflow.
How do we know controls work?
Test representative cases, monitor incidents and review audit evidence.
Which use cases need controls?