How to answer a customer's AI questionnaire

It usually arrives attached to a renewal, a procurement review or the biggest pitch of your year: a spreadsheet or portal login titled "AI due diligence" or "vendor AI assessment," asking how your company uses artificial intelligence. Every guide on the internet is written for the people sending these questionnaires. This one is for the people who have to answer them — because on the seller side, the questionnaire is rarely a compliance exercise. It's a sales moment: the customer is deciding whether your AI practices are a reason to sign, or a reason to stall. Firms that answer quickly, specifically and with evidence keep the deal moving. Firms that answer with adjectives don't.

Quick answer

• Expect five areas of questions: what AI you use and where; what happens to data (including whether it trains models); who is responsible and who reviews outputs; how you disclose AI use; and what happens when something goes wrong.

• Answer the question asked, with a fact and a pointer — the policy section, the contract clause, the registry entry. "We take AI seriously" is not an answer to any of them.

• Name your tiers. "Our provider doesn't train on our data" is only true for specific plans. Say which products and which plans you use, and cite the provider's terms.

• Distinguish aligned from assessed. Buyers are trained to spot the difference between "we follow framework X" and "an independent body checked us against standard Y." Claim only the second if you can link to it.

• Build the answer pack once. Every questionnaire after the first should be an afternoon of tailoring, not a week of archaeology.

The standard question set — and what satisfies it

Buyers vary the wording, but the underlying questions converge. These are the ones that recur across enterprise AI and privacy reviews, grouped the way buyers group them.

1. "Which AI systems do you use, and for what?"

They want an inventory, not a vibe. A list of the AI tools and AI features in your stack, what each is used for, and which of them touch the customer's work or data. This is the question vendors fail most often — not by lying, but by genuinely not knowing, because nobody maintains the list. If you have an AI inventory, this answer is a copy-paste. If you don't, the questionnaire just told you to build one.

What satisfies it: the list itself, with purposes in plain language. Bonus credibility: noting the AI features inside software they already know you use (your CRM, your meeting tool), which signals the answer is complete rather than curated.

2. "Is our data used to train AI models?"

The single most consequential question in the set, and the one with the least room for a fuzzy answer. The honest answer is built from your providers' terms, and it depends on tier: major providers' API and business products generally commit to not training on customer data by default, while consumer plans carry different terms. So the answer names your tools, your plans, and the commitment — "customer data processed through [tool, business plan] is not used to train models, per [provider]'s data processing terms" — and states your own rule: whether staff may put customer data into any tool outside that list (they may not, if your policy says so).

What satisfies it: the provider terms or DPA clause you can point to, plus your internal data rule. What doesn't: "we never share data with third parties," which answers a question nobody asked.

3. "What data goes in, how long is it kept, and who else processes it?"

Retention, subprocessors and locations. Buyers ask how long your AI providers retain prompts and outputs, who your subprocessors are, and what happens to their data when the contract ends. Assemble this once from your providers' published subprocessor lists and DPAs and keep it current; it's the same table every time.

What satisfies it: the subprocessor list with purposes, retention periods as published by each provider, and the deletion/exit commitment in your own terms.

4. "Who is accountable for AI use, and who reviews what it produces?"

The governance question. Buyers want a named role (not "the team"), a description of where a human reviews AI output before it affects the customer, and how someone can contest an outcome and reach a person. "Human in the loop" as a bare phrase scores poorly; "a named reviewer checks every AI-assisted deliverable before it is sent, and can reject or redo it" is an answer.

What satisfies it: the role title, the checkpoints described concretely, and the policy document behind them.

5. "Do you disclose AI use to your customers?"

They are, in part, checking whether they'll be surprised. Where do you tell customers AI is involved — chatbot notices, statements in proposals or deliverables, labels on AI-generated content? If your practice is disclosure, this question is easy and quietly differentiating: many of your competitors will be writing something evasive here.

What satisfies it: the actual disclosure wording or the places it appears. A sample is worth more than a description of a sample.

6. "What happens when the AI gets it wrong?"

Incident process: how errors or misuse are spotted, who is told and how fast, what gets paused, what the customer hears about it. Buyers are not expecting perfection; they're checking that a process exists before they need it.

What satisfies it: a short incident outline — detection, internal owner, customer notification commitment, corrective step — consistent with whatever your security answers already promise.

7. "What standards or certifications back any of this up?"

The evidence question, and the one where wording matters most. Buyers and their advisors are explicitly warned to separate "aligned to," "built around" and "in line with" (self-declared, unverified) from independent assessment (checked by someone else). List what you actually hold: a SOC 2 report is an attestation your customers can request under NDA; a framework you follow internally is context, not proof. An entry in a public registry — where the customer can verify your status themselves, without asking you — is the strongest form of answer because it removes you as the middleman of your own claim.

How to answer well, mechanically

• Acknowledge fast, answer once. Reply within a couple of business days naming your owner for the questionnaire and your expected completion date. A named human and a date defuse most escalation.

• Answer in their format. If it's a spreadsheet, answer in the spreadsheet, cell by cell. Don't substitute a marketing PDF and make the reviewer transcribe it.

• One answer per question, reusable forever. Write each response as a standalone statement of fact that will still be true in six months. Store the set — the answer pack — with the evidence links beside each item.

• Flag the gaps honestly, with a date. "We don't currently publish a subprocessor page; here is the list as of today, and the page launches in March" beats a polished evasion. Reviewers score candour; they remember being misled.

• Never let sales write a control into existence. If the answer pack says a review step happens, it has to happen. Questionnaires increasingly become contract exhibits — your answers can be held against you, literally.

Build the pack before the next one arrives

The firms that answer in hours have a standing pack: the AI inventory; the data-flow and subprocessor table; the one-page AI use policy; the disclosure wording; the incident outline; and the proof links — certifications, registry entries, report availability. That pack is, not coincidentally, most of what an independent certification review examines. The Ethicality AI Use Standard (EAUS) assesses the same ground buyers ask about — disclosed AI use, a human responsible for important decisions, confidential information protected — across 15 plain-language requirements, and certification puts your answers in a public registry the customer can check directly. When the questionnaire's hardest question is "says who?", a registry link is the shortest answer there is. The mirror image of this post — what buyers should ask — is on our procurement page, and pricing and the certification cost guide cover what the certification route costs if the questionnaire has you considering it.

Frequently asked questions

How long should an AI questionnaire take to answer?

The first one, done properly, takes days — most of that is assembling the inventory and the subprocessor facts, not writing. Once the answer pack exists, a new questionnaire is mostly mapping their questions to your standing answers: hours, plus whatever is genuinely new. If your third questionnaire still takes a week, the pack is the problem, not the questionnaire.

What if we use AI but hold no certifications at all?

Answer with facts and documents: the inventory, the policy, the provider terms, the review checkpoints. Plenty of vendors pass reviews on documented practice alone, especially for lower-risk uses. Be precise about what you don't hold — "we do not currently hold SOC 2; our AI use is governed by [policy], and customer data is processed only through [providers] under these terms" — rather than letting the reviewer discover the gap. Then decide, calmly and outside a live deal, whether independent certification would pay for itself; it's much cheaper bought before a deadline than during one.

Can we push back on unreasonable questions?

Yes, on scope, not on substance. It's reasonable to ask which of your services a question covers, to offer your standard answer pack in place of a bespoke format, and to route deep technical items to a call. It's not reasonable to refuse to say which AI tools touch the customer's data or whether that data trains models — those are now baseline questions, and declining them reads as an answer.

Should we share our SOC 2 report for an AI questionnaire?

If you hold one, naming it (type, period, auditor) in the answer and offering the report under NDA through your usual channel is standard practice. Remember what it does and doesn't cover: SOC 2 attests to security and related controls; it doesn't describe how your people disclose or review AI-assisted work, so the AI-specific questions still need their own answers alongside it.

What's the difference between our answer pack and a trust centre?

Nothing in substance — a trust centre is the answer pack published as web pages instead of kept in a folder. Publishing it (with the sensitive documents behind a request form or NDA) shortens every future review and quietly helps sales, because some buyers check before they ever send the questionnaire. Start with the folder; publish when the same questions have arrived three times.

Does certification actually change the outcome of a review?

It changes the verification burden. Reviewers still ask their questions, but each answer that ends in an independently checkable reference — a registry entry, a certificate number, a named standard — is an answer they don't have to take on trust or chase evidence for. In a competitive bid where two vendors' self-descriptions read the same, the one whose claims a third party has checked is easier to approve. That's the entire mechanism.

Make the next questionnaire boring

An AI questionnaire is a request for evidence you either have or have to invent under deadline. The inventory, the data rules, the named human, the disclosure wording, the proof link — build them once, keep them current, and the biggest customer review of your year becomes an afternoon of copying from your own pack. If you want the pack's claims independently checked rather than self-declared, get certified — the application takes about ten minutes, the assessment is free, and decisions land within five business days.