AI Vendor Assessment Tool

AI vendor risk scoring model and spreadsheet export

The AI vendor risk scoring model turns reported answers and evidence dates into follow-up priorities; it does not estimate breach likelihood or determine whether a supplier is safe. Unknowns and expired evidence remain visible so a reviewer can assign the next action.

For an AI SaaS vendor risk review, scope one service, plan, configuration, data path, and intended use before comparing responses. The scorecard can export the completed record as CSV or JSON for a controlled register. If you need an AI vendor assessment spreadsheet, use the CSV export as a starting record; it reflects current answers and is not a pre-filled template. The tool does not verify evidence or upload the result.

Updated 2026-10-08. For voluntary risk-management context, see the NIST AI Risk Management Framework; this scorecard does not implement or certify that framework.

What the scorecard does

This browser-local worksheet records a named vendor, service and intended use, then makes review gaps easier to assign. It asks about the most sensitive expected data, model training or improvement, model and subprocessor disclosures, access, consequential actions, human review, retention, incidents and exit terms. It also records short evidence references, review dates and expiry dates across seven areas. Enter references such as a contract section or report name; do not upload or paste the evidence itself.

How to use it

1. Scope one service, plan, configuration and business use.
2. Answer from evidence for that scope. Keep unknown and partial answers explicit.
3. Add a short evidence reference plus review and expiry dates. Missing or expired items remain follow-up flags.
4. Create the scorecard, review each flag, and record a named human decision, rationale, conditions and date.
5. Export CSV or JSON locally only if you need a record; protect that file under your own access and retention rules.

Worked example with the loaded synthetic inputs

The example is labeled Northstar Demo AI (synthetic): a support assistant that searches tickets and drafts replies while a person sends every reply. It selects personal data, unknown training terms, partial model disclosure, undisclosed subprocessors, write access, consequential influence with human review, unknown retention and exit, and a defined incident term. On an assessment dated 7 October 2026, its deliberately incomplete evidence references and one expired model-provider item yield 57 follow-up points and the displayed “High-priority review” band. That is a reproducible triage example from the current inputs and engine; it is not an observed vendor result, probability of harm, approval or compliance score.

Limits and source context

The worksheet does not verify claims, inspect a vendor, fetch evidence, determine legal applicability or make procurement decisions. The rules are explicit local weights, not a NIST method or calibrated measurement. A human reviewer decides whether to proceed, add conditions or decline. Review the NIST AI Risk Management Framework as voluntary risk-management context; it does not certify this scorecard or its result.

Frequently asked questions

Does the scorecard verify a vendor’s answers?

No. It records answers and evidence references you provide. A reviewer must inspect the referenced material and confirm that it covers the product, plan and use in scope.

Does a high-priority band mean the vendor is unsafe?

No. The points prioritize follow-up from unknown answers, reported conditions and evidence gaps. They are not a vendor rating, likelihood estimate, compliance finding or automatic decision.

Are my entries sent to a server?

The current tool processes its entries in this browser. It does not upload them. If you export CSV or JSON, the file is created locally; handle it under your organization’s security and retention rules.

What does evidence freshness mean?

You record the evidence reference and its review and expiry dates. Missing references, missing dates and expired evidence create follow-up flags; the tool does not authenticate a document or decide whether it is sufficient.

Related guidance

AI Vendor Assessment Questionnaire · How to Evaluate AI Vendors · Vendor Monitoring and Tiering

Interpret the review points before comparing vendors

This AI vendor assessment tool records one defined service and your current evidence. Its AI vendor risk scoring model uses explicit local weights to highlight missing answers and follow-up conditions. AI vendor risk scoring does not measure the probability of an incident, establish regulatory compliance or produce a procurement approval. Compare records only when scope, assumptions and review dates are comparable; a lower total can still hide an important unresolved issue.

Use an AI vendor assessment spreadsheet as a working record by downloading CSV and reviewing its rows in your approved spreadsheet application. The separate JSON export retains structured answers for your own records. Neither export is uploaded or synchronized by this site. AI vendor assessment automation here means applying the displayed rules when you create a scorecard; it does not collect reports, authenticate evidence, email a supplier or schedule future checks.

Connect this worksheet to your review process

Third party AI risk management needs an accountable reviewer, a named use and evidence that covers the actual product and configuration. For an AI SaaS vendor risk review, record the subscription scope, model dependencies, data handling and consequential actions instead of assuming every service edition behaves alike. Keep unknown terms visible and assign a person to request the missing material.

If you compare AI third party risk management software or an AI TPRM platform, examine access control, approval history, evidence permissions, change detection and retention separately. This free local worksheet does not supply those hosted capabilities. AI vendor management software should be evaluated against documented requirements and verified product behavior, rather than this worksheet's score alone.

An AI vendor risk register can link each unresolved question to its evidence reference, reviewer, condition and next decision. Use exported records under your organization's access and retention rules; track later changes in your approved system. For AI vendor risk assessment cost, plan the work involved in scoping, evidence inspection, security and legal review, and follow-up. The worksheet does not invent an hourly rate, service fee or savings estimate. Record actual effort and separate recurring review from initial onboarding before budgeting.