AI Automation Partner Scorecard
Ten questions and an evidence rubric for comparing an AI automation partner before approving a project.
Use this scorecard to compare an agency, consultant, freelancer, or internal build team before you approve an automation project.
Score each question from 0 to 2:
- 0: no clear answer or evidence;
- 1: partial answer, but important details are missing;
- 2: specific answer with a named owner, example, or document.
The ten questions
| Question | Score 0–2 | Evidence to request |
|---|---|---|
| Can they define the operational outcome and current baseline? | A before-and-after metric and how it will be measured | |
| Do they map the workflow before selecting tools? | A workflow map showing inputs, decisions, handoffs, and exceptions | |
| Are human judgment and escalation explicit? | A list of decisions the system cannot make alone | |
| Can they explain data access, security, and failure modes? | Permissions, data flows, retention, and failure handling | |
| Are testing and acceptance cases defined? | Normal, incomplete, conflicting, and escalation test cases | |
| Who owns accounts, code, documentation, and credentials? | A written ownership and handover plan | |
| What support exists after launch? | Response expectations, maintenance boundaries, and change process | |
| Can they show relevant and verifiable proof? | A case study, system walkthrough, or approved reference | |
| Is the quote tied to scope and risk? | Deliverables, assumptions, exclusions, and change rules | |
| Will they tell you when automation is the wrong answer? | A clear example of work they would leave human or fix manually first |
How to read the score
- 0–7: pause. The project may be carrying too much delivery, ownership, or measurement risk.
- 8–14: continue discovery, but resolve the missing evidence before signing.
- 15–20: the partner has supplied a usable basis for comparison. Confirm references, scope, and ownership before approval.
A high score does not guarantee a successful project. It means the partner has made the important work visible enough to evaluate.
Questions to ask in the first call
Ask the partner to walk through one real workflow. Listen for the baseline, the exception path, the human review point, and who owns the system after launch. If the conversation stays at the level of tools and features, ask what the team will do differently on Monday morning.
Flowgrammer's approach is documented in How to Choose an AI Automation Agency and the AI Success Audit.
Continue with Flowgrammer
- Use the AI Success Audit when the project is not yet defined.
- Review the advertising lead intelligence engine.
- Compare implementation scope in AI Automation Systems.
- Book an AI Success Audit.