# AI Governance Consulting & Assurance Services: evaluation worksheet

Source: https://dutygraph.com/directory/ai-governance/categories/services/
Editorial date: 2026-09-07

## Scope

- Organization / team:
- Task and expected output:
- Human owner:
- Product and version:
- Evaluation date / environment:
- Reviewer:

## Questions

### 1. What concrete deliverables and acceptance criteria are included, and what is out of scope?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 2. Which claims rely on interviews, documents, technical testing or independent assessment?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 3. Who performs the work, and how are relevant experience and independence demonstrated?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

### 4. What training, update process and reusable records remain with the client?

- Observation (demonstrated / described / unknown):
- Evidence reference:
- Limitation or follow-up:

## Evidence checklist

- [ ] A scoped statement of work and sample deliverable
- [ ] A methodology with evidence requirements
- [ ] A client handoff plan with named responsibilities

## Boundary to check

An advisory engagement is not automatically an audit or certification. Verify any claimed accreditation and its exact scope directly with the relevant body. A software license and a human-delivered engagement should be compared as different offerings.

## Decision

- Fit for the scoped task:
- Unresolved gaps:
- Next action, owner and date:

This is a planning worksheet, not an endorsement, access approval or compliance certification. Keep confidential evaluation notes in your organization's approved storage.