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AI SECURITY QUESTIONNAIRE / CHECKLIST

Answer the buyer once. Reuse the evidence on the next deal.

Enterprise AI questionnaires mix product architecture, model risk, privacy, security operations, governance, and contract claims. This checklist helps an AI SaaS vendor turn the incoming spreadsheet into an owned evidence system instead of a one-off writing project.

Reviewed 24 July 20268 minute readIndependent practitioner guide
1named AI system in scope
3evidence states: proven, partial, missing
5workflow approval stages
0unsupported claims permitted
01

INTAKE

Normalize the buyer's questions before drafting.

Keep the original wording and buyer identifier, but classify each question by system, topic, required evidence, risk, and owner. Mark duplicates and dependencies. This preserves the buyer's intent while exposing which answers can be reused.

Confirm the deadline, submission format, confidentiality terms, and whether the buyer wants current facts, roadmap commitments, or contract language. Those are different approval paths.

  • Original buyer question and due date
  • Named system and deployment boundary
  • Topic, risk, owner, and required reviewer
  • Requested attachment, link, or attestation type
02

SYSTEM / MODEL / DATA

Build a buyer-readable AI system record.

Describe the service, its intended use, customer-facing AI functions, models and providers, data sources, outputs, storage, regions, retention, subprocessors, and human checkpoints. Distinguish your controls from controls operated by upstream providers.

Capture versions and dates. A model or provider inventory without change history becomes stale the moment engineering changes the stack.

  • Architecture and data-flow record
  • Model, API, infrastructure, and subprocessor inventory
  • Customer data-use and retention statement
  • Intended use, prohibited use, and limitation record
03

TEST / PROTECT / MONITOR

Link security answers to operational records.

Buyer questions increasingly ask for testable AI controls. OWASP's AISVS 1.0 describes an open catalogue of testable requirements spanning the AI lifecycle and explicitly identifies procurement as a use case. Use a recognized source to challenge your coverage, but answer only with controls actually implemented in the named system.

Evidence may include access reviews, threat models, adversarial test plans, evaluation results, release thresholds, logging configurations, incident exercises, recovery tests, and change approvals.

  • Identity, privilege, and production access review
  • Model and prompt attack testing with dated results
  • Evaluation thresholds, failed cases, and accepted exceptions
  • Monitoring, escalation, incident response, and recovery records
04

OWNER / APPROVAL / LIMIT

Make governance claims traceable to decisions.

A committee name is not the same as evidence of governance. Link material claims to a charter, decision record, risk acceptance, review cadence, or approval history. Name the role that can approve the representation and the role that can fix a gap.

Record limitations beside the claim. If an evaluation covers only English prompts or one model version, the answer should not imply broader coverage.

  • Policy or standard with effective date and owner
  • Risk register entry and acceptance authority
  • Release or model-change approval record
  • Known limitation, exception, and target remediation date
05

FINAL REVIEW

Ship a frozen, reviewable response set.

Before submission, confirm that every link resolves for the intended reviewer, confidential attachments have the right access, answer language matches the evidence, and open gaps are not presented as completed controls.

Freeze the submitted version and keep the buyer's follow-up questions. They are inputs to the reusable answer library for the next deal.

  • Security, product, privacy, and legal review where applicable
  • Approved response version and evidence index
  • Visible partial and missing states
  • Buyer follow-up log and library update owner

FREE / NO EMAIL GATE

AI Procurement Evidence Inventory

A no-gate CSV with fields for the buyer question, framework reference, system scope, owner, approved answer, evidence URI, review date, gap, and target date.

Download CSV

PRIMARY SOURCES

Verify the framework at the source.

CSA AI-CAIQ v1.1Official structured AI self-assessment and third-party evaluation resource.OWASP AISVS 1.0Official testable AI security requirements and procurement use case.NIST AI Risk Management FrameworkOfficial voluntary framework and Generative AI Profile links.

ONE LIVE QUESTIONNAIRE / 15 BUSINESS DAYS

Turn the deadline into a reusable evidence room.

The Evidence Factory Sprint covers one defined AI system and one accountable client team. We organize source material, draft bounded answers, expose gaps, route approvals, and hand off the response library and evidence index. The client approves every external representation.

$25,000 fixedFixed scope. No payment is taken on this site.

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