What does the ai accountability matrix produce?
Assign accountable and responsible roles to one AI lifecycle activity, with a reviewer and escalation route.
Prepare and review the task-specific records in this browser. Inspect consistency findings and retain the complete backup before preparing the finalized pack. Accountable decisions require responsible review.
What do you need before you start?
- Define the named scope, accountable owner and your review basis.
- Retain the actual evidence separately. Recorded links and evidence references are declarations and are not fetched.
- Choose a valid review date. Resolve missing fields, contradictory declarations and date or status findings before relying on the review.
What information do you enter?
The browser workspace asks only for the structured fields listed below.
- AI system or use case (required). Use the name in the organization’s inventory.
- Lifecycle activity (required). Choose the activity covered by this assignment.
- Accountable owner (required). Name one role that owns the final internal decision.
- Responsible person or team (required). Name the role that performs the work.
- Reviewer or approver (optional). Name the independent or supervisory reviewer.
- Assigned duties (required). Describe the bounded task and expected evidence.
- Escalation route (required). Record where unresolved issues or conflicts go.
- Evidence reference (optional). Use an internal record or ticket reference.
- Next internal review date (required). Choose the organization’s own review date.
- Assignment status (required). Record whether the assignment is ready for use.
| Field | What to enter | Fictional example |
|---|---|---|
| AI system or use caseRequired | Use the name in the organization’s inventory. | Example recruitment assistant, fictional |
| Lifecycle activityRequired | Choose the activity covered by this assignment.Choose from Design, Procurement, Approval, Deployment, Monitoring, Incident response, Retirement. | Monitoring |
| Accountable ownerRequired | Name one role that owns the final internal decision. | Head of People |
| Responsible person or teamRequired | Name the role that performs the work. | People analytics team |
| Reviewer or approverOptional | Name the independent or supervisory reviewer. | Employment counsel |
| Assigned dutiesRequired | Describe the bounded task and expected evidence. | Review monthly outcome samples and record exceptions. |
| Escalation routeRequired | Record where unresolved issues or conflicts go. | Escalate material differences to the AI governance committee. |
| Evidence referenceOptional | Use an internal record or ticket reference. | EXAMPLE-RACI-004 |
| Next internal review dateRequired | Choose the organization’s own review date. | 2026-11-30 |
| Assignment statusRequired | Record whether the assignment is ready for use.Choose from Draft, Confirmed, Needs update, Retired. | Draft |
What you can download
Every result must identify its supplied facts, assumptions and unresolved items.
| Free result | Included downloads |
|---|---|
Enter your information, inspect the on-screen result and keep a browser backup. Editing and direct copies of your entered information stay free. |
These supported outputs are free. No checkout is required. |
How does the ai accountability matrix work?
- 1Prepare the named records
Use the task-specific fields above. Retain original evidence separately and record exact references and versions.
- 2Review internal consistency
Choose the review date. Inspect each scope identity, contradictory declaration, missing decision support and date or status finding.
- 3Keep recoverable work
Download a free backup before replacing or clearing work. Restore earlier record backups or the complete current snapshot, including unfinished drafts.
- 4Prepare the finalized pack
Prepare all nine files, then download them free. Review excerpts in PDF and DOCX against the complete Excel, CSV and JSON. Optional private cloud saving requires sign-in and separate consent.
Method and sources
Apply the steps above to the supported inputs. Use the listed source sections to review the rule basis, assumptions and limits.
- Artificial Intelligence Risk Management Framework 1.0A voluntary US baseline for AI risk records, responsibilities, evaluation and lifecycle decisions. Govern, Map, Measure and Manage.National Institute of Standards and Technology. Published 2023-01-26. Reviewed 2026-10-08.
- AI Risk Management Framework PlaybookImplementation ideas and documentation practices for the AI RMF. Suggested actions for Govern, Map, Measure and Manage.National Institute of Standards and Technology. Published 2023-03-30. Reviewed 2026-10-08.
Common questions
What information does the ai accountability matrix need?
Enter AI system or use case (required). Use the name in the organization’s inventory; lifecycle activity (required). Choose the activity covered by this assignment; accountable owner (required). Name one role that owns the final internal decision; responsible person or team (required). Name the role that performs the work; reviewer or approver (optional). Name the independent or supervisory reviewer. Define the named scope, accountable owner and your review basis.
What does the ai accountability matrix produce?
Complete all-field record review and task-specific scope rows. Every unresolved finding stays visible. Free restorable browser backup including the unfinished draft, editing reference and review date. Nine-file finalized pack. Formal PDF, editable DOCX, complete Excel register and review sheets, records CSV, findings CSV, scope review CSV, complete JSON, file hashes and instructions. Review unresolved findings and limitations before use.
Who makes the final decision?
A responsible person reviews the result. Checks review customer declarations, recorded dates and internal consistency. They do not authenticate evidence, approve an AI use, determine legal applicability or establish conformity, safety or risk acceptance.
Is this tool free?
Yes. The on-screen result and listed downloads are free. No checkout is required. Keep local backups and review the stated method and limits.
Can I use the ai accountability matrix for this task?
Assign ownership for design, procurement, deployment and monitoring. Checks review customer declarations, recorded dates and internal consistency. They do not authenticate evidence, approve an AI use, determine legal applicability or establish conformity, safety or risk acceptance.
What still needs review?
Checks review customer declarations, recorded dates and internal consistency. They do not authenticate evidence, approve an AI use, determine legal applicability or establish conformity, safety or risk acceptance.
Each workspace supports 1000 records, 20000 characters per field and a 30 MB complete workspace. Invalid and foreign backups preserve current browser work.
PDF and DOCX show the first 20 records, field excerpts through 2000 characters and the first 40 findings. Excel, CSV and JSON retain complete values and derived rows. Referenced files are not fetched or included.