AI Vendor Assessment ToolUse this guide to answer a customer’s AI and security questions accurately for a named product, plan, and configuration. Treat each answer as a claim that needs an owner and evidence. These response structures are examples, not pre-approved statements about this site or any real vendor. This page does not provide a downloadable questionnaire or trust-center file.
Understand the customer’s request
An AI security questionnaire response template should begin by clarifying the product, feature, plan, deployment, data, and intended use in scope. Customer questions commonly cover:
- What the AI feature does, which model or downstream providers it uses, and who may change it.
- What prompts, files, outputs, telemetry, or support data are processed, where they go, and how long they are retained.
- Whether customer data is used to train or improve models, including differences by plan, setting, or subprocessor.
- Human review, output limitations, access controls, security testing, incident handling, and customer configuration duties.
- Subprocessors, data locations, export and deletion, service changes, and available documentation or assurance materials.
Separate a statement about an organization from a statement about a specific service. If evidence covers only one product, region, or plan, say so. A response to an AI in SaaS products customer questionnaire should make the SaaS feature and configuration boundaries explicit.
Build an answer library with evidence
Store approved answer patterns with required fields rather than reusing unqualified “yes” answers. For each question, capture product and plan, configuration, answer owner, evidence reference and date, exceptions, approval status, and next review trigger. Use clear statuses such as confirmed for this scope, partial, unknown, or legal review needed.
| Topic | Response structure | Status until verified |
|---|---|---|
| Training or improvement use | “For [product/plan/configuration], [verified statement about each data type and downstream provider]. Source: [contract or setting], reviewed [date]. Exceptions: [list].” | Unknown if account, data type, or subprocessor scope is not confirmed |
| Retention and deletion | “[Data types] are handled under [service-specific term], with [verified period or trigger] and [known backup or legal-hold exception].” | Partial if a term covers production data but not logs or backups |
| Human review | “For [feature and use], [verified review, correction, escalation, or override process] is owned by [role].” | Unknown if review depends on customer settings not yet checked |
| Assurance evidence | “[Report or certification] covers [entity/service/systems] for [period], with [relevant exceptions and customer responsibilities].” | Partial if the product or period is outside the evidence boundary |
Do not convert a missing answer into a favorable claim. Avoid blanket phrases such as “fully compliant,” “never trains,” or “all data is deleted” unless approved evidence supports that exact scope and wording.
Collect and share evidence carefully
Choose documents that answer the customer’s question and cover the product in scope. Possible materials include a service-specific data-flow summary, current subprocessor list, contractual data terms, security architecture overview, incident process, vulnerability-management summary, or assurance report. Confirm each item’s owner, version, review date, product boundary, and permitted audience.
Send documents only through an approved channel under applicable confidentiality terms. Remove secrets, customer data, credentials, and unrelated findings. If a report is available only under a separate agreement or to a restricted audience, state that limitation instead of implying it was supplied. The AICPA & CIMA SOC suite page is a resource index, not a substitute for reviewing an actual vendor report and its scope. This guide does not provide SOC 2 or ISO control mapping.
Maintain an AI trust center responsibly
An AI trust center can organize public information and controlled access to approved materials. For each published statement or document, keep an internal record of the product and plan covered, owner, source evidence, approval date, audience, expiration or review trigger, and change history. Provide an access-controlled route for restricted reports; publish only content approved for public use.
Check that public statements agree with contracts, product settings, and the answer library. FTC guidance on AI data practices emphasizes honoring privacy and confidentiality commitments made to customers and users. See the FTC discussion of AI companies’ commitments. It is guidance about commitments and FTC-enforced laws, not a prescribed trust-center format.
Different diligence situations
For AI due diligence, assemble evidence around the decision being made and the audience receiving it. A customer security review, procurement assessment, and investment diligence request may need different levels of detail and different confidentiality controls. An AI due diligence M&A process may also require product, contract, data, security, and dependency evidence to be reviewed by the parties’ authorized legal and technical teams. Do not treat a response pack as a warranty or substitute for transaction-specific advice.
An AI startup due diligence checklist investors can use should distinguish statements supported by current records from management representations, assumptions, and open questions. For a startup, name the owner of each material claim and identify what evidence could be shared under the applicable confidentiality terms. Avoid implying that a short questionnaire establishes technical assurance, future performance, or regulatory status.
Response workflow
- Clarify the customer’s product, feature, plan, deployment, data, and intended use.
- Assign each question to an evidence owner in security, privacy, product, engineering, legal, or customer operations.
- Check exact evidence scope and current settings; mark gaps and contradictions instead of guessing.
- Route legal or assurance claims to qualified reviewers and factual claims to the product owner.
- Send only approved wording and documents with relevant scope, dates, and exceptions.
- Record what was sent, to whom, under what terms, and what must be reviewed before reuse.
Worked hypothetical example: A customer asks a small AI software vendor whether prompts are used for model training. The public FAQ says customer prompts are not used to train models but does not identify the customer’s plan or a downstream model provider. The responder marks the claim unknown for this account, asks the product owner to verify the contract and configuration, and tells the customer the answer is being confirmed. The responder sends an approved answer only after the scope is checked. This example is fictional and does not describe this site’s data practices or any real vendor’s answer.
Answering with care
When asked how to answer a customer AI security questionnaire, state the verified scope, evidence date, owner, and exception in plain language. If evidence is incomplete, say what is known and what remains under review. A concise, scoped answer is more useful than broad language that cannot be supported.
An AI trust and safety assessment vendor response should describe the particular product, workflow, safeguards, limits, and escalation route supported by evidence. Do not imply that trust or safety is guaranteed by a policy statement, model card, or assurance report alone. Keep the response aligned with the actual configuration and the customer’s use.
Frequently asked questions
Can we reuse a previous questionnaire answer?
Only after checking that product, plan, configuration, evidence scope, and wording remain current. Record the approval and any exceptions before reuse.
What if the answer is not yet verified?
Mark it unknown or under review, identify the owner, and give the customer a clear next step. Do not substitute a general marketing statement.
Should every trust-center document be public?
No. Publish only approved materials. Use the appropriate confidentiality and access process for restricted reports or detailed evidence.
Does a questionnaire response establish compliance or certification?
No. A response documents scoped statements and evidence. Legal status, assurance, or certification depends on separate requirements and review.
Organize a due diligence pack
- Service overview: product, plan, purpose, system boundary, and current model or provider list.
- AI and data practices: data flows, retention and training statements, human review, limitations, and change process.
- Security evidence: scoped assurance material, access and incident summaries, and customer responsibilities.
- Privacy and contract: applicable data-processing terms, subprocessors, locations, and deletion information.
- Response record: questionnaire version, answer owners, evidence references, approval dates, exceptions, and unresolved items.
Keep the pack versioned and audience-appropriate. For questions you ask suppliers, use the AI Vendor Assessment Questionnaire and AI Vendor Security Review Checklist. For EU role and documentation prompts, see the EU AI Act Vendor Due Diligence guide.
Updated 2026-10-07. Sources are linked on this page.
Customer AI security questionnaire: how to answer
Begin by identifying the product, configuration, question owner and evidence reviewed. Keep a documented fact separate from a planned control or unresolved question. An AI due diligence checklist can help a responder identify gaps before answering, but it cannot supply evidence or approve a claim. Ask the appropriate reviewer to confirm the answer and its scope before sending the packet.