Enterprise decision framework
AI implementation partner scorecard: evidence before selection
Evaluate an enterprise AI delivery partner through entry gates, observed capability, handover and commercial accountability.
By QualifiedPOC.ai Research. Research methodology and evidence limits
Executive answer
Choose an AI implementation partner only after business fit, data readiness, delivery ownership, evaluation and exit gates pass. Score demonstrated evidence, not presentation quality or unsupported case-study claims.
Key takeaways
Apply mandatory gates before weighted scoring.
Meet the people who will deliver the work.
Test handover and exit before expanding the contract.
1. Apply five entry gates
A named business owner accepts the problem, baseline and intended outcome.
The buyer can lawfully and technically provide representative test data.
A named delivery team and production operator are accountable.
An agreed evaluation can distinguish success from failure.
Data export, documentation, intellectual-property terms and exit responsibilities are explicit.
2. Score delivery evidence consistently
Rate 0 for missing evidence, 1 for a claim, 2 for inspected artifacts and 3 for observed or independently verified delivery. This is our proposed rubric, not an industry certification.
| Dimension | Evidence to inspect |
|---|---|
| Business delivery | Comparable scope, baseline, actual result and permission to verify the reference |
| Technical capability | Working session with the proposed team on your architecture and failure cases |
| Risk and operations | Access model, test results, incident ownership and change controls |
| Handover | Runbook, maintainable artifacts, training and successful buyer-operated recovery |
| Commercial fit | Milestone acceptance, exclusions, ongoing costs and exit obligations |
3. Run a working-session canary
Give each shortlisted team the same approved problem and constraints. Ask them to identify missing evidence, propose a thin implementation and explain how the buyer could stop or recover it. Do not share another supplier’s confidential design.
4. Make the award decision
Document gate results, scoring rationale, unresolved assumptions and acceptance conditions. A strong total score does not offset a failed access, safety or ownership gate.
5. How to use this framework
This is a QualifiedPOC.ai editorial decision framework, informed by the linked primary sources. Its gates and test designs are proposals to adapt to your workload.
They are not legal advice, a certification or a claim of measured customer results. Sources checked 3 November 2026; this is a review date, not their publication date.
NIST: AI RMF Core (version 1.0, 2023)Source date: not recorded · Checked 2026-11-03
Request POC for this use casePractical questions
What is the strongest evidence of an AI partner’s capability?
Observed work by the proposed delivery team, inspectable artifacts and a verifiable reference with comparable constraints are stronger than an unsupported claim. Obtain permission before contacting a reference.
Does a certification replace a POC?
No. A relevant certification can support supplier assurance, but it does not prove that the proposed team can deliver your workflow, controls or business result.
How should buyers compare partner prices?
Compare identical scope, acceptance conditions, exclusions, operating costs and handover obligations. A lower day rate is not proof of lower total delivery cost.
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