How to respond to an AI governance due-diligence questionnaire

Why you are getting these questionnaires

The organisation asking has its own accountability. Guardrail 8 of the Voluntary AI Safety Standard asks organisations to be transparent across the AI supply chain about the data, models and systems they rely on, which means your customer has to understand your AI to answer for their own. A questionnaire is how they do that at scale. The quality of your answer feeds their decision to proceed, and a vague answer reads as an absent control, not a busy respondent.

What the questions are really asking

Behind the wording, most AI governance questionnaires test the same small set of things. They ask whether you know what AI you run, whether each system has an owner, whether you assess and monitor risk, whether a person can intervene, whether you keep records and whether you can show any of it. Those map closely to the guardrails and to ISO/IEC 42001, so a respondent who has the governance in place is answering questions they already hold the evidence for. A respondent who does not has to write around what is missing, and a careful reader can tell.

Step 1: Answer from records, not intentions

The difference between a strong answer and a weak one is usually tense. “Each AI system has a named owner and a recorded risk decision” is a statement you can back. “We are putting owners in place across our AI systems” is a plan, and a due-diligence reader discounts plans. Answer from what is true and recorded today, and where something is genuinely in progress, say what is done and what is not rather than blurring the two. A reader trusts a precise partial answer more than a confident vague one.

Step 2: Map your answers to a recognised standard

An answer that measures your governance against your own preference asks the reader to accept your judgment of what is enough. An answer that maps to the Voluntary AI Safety Standard, ISO/IEC 42001 or the NIST AI Risk Management Framework measures it against a reference the reader already recognises. Naming the standard you align to, and answering in its terms, does two things. It shortens the reader’s assessment, because they can slot your answer into a framework they know, and it signals that your governance was built to an external bar rather than assembled for the questionnaire.

Step 3: Give evidence the reader can check

The strongest answer points to evidence rather than describing it. A reader weighing your response would rather see a sealed record of an impact assessment, dated and attributed, than a paragraph asserting that assessments happen. Where you can, attach or offer records the reader can confirm have not changed since they were captured, because evidence that a third party can verify without trusting the author is worth far more than a summary in the response document. This is the qualitative difference between passing due diligence and merely completing it.

Step 4: Be precise about what you do and do not do

A due-diligence reader is professionally alert to answers that claim more than the control delivers. If you monitor a system quarterly, say quarterly, not continuously. If a person approves high-consequence actions but not routine ones, describe the line rather than implying every action is reviewed. Overstating a control is the fastest way to lose a careful reader, because the moment one answer is caught reaching, every other answer is reread with suspicion. Precise scope is more persuasive than broad reassurance.

Step 5: Keep a reusable evidence set current

These questionnaires arrive repeatedly, from different customers, in different formats, asking the same underlying questions. Answering each from scratch is slow and drifts out of date, so keep a current set of answers and the evidence behind them, and update it when your governance changes rather than when the next questionnaire lands. A maintained evidence set turns a fortnight of scrambling into an afternoon of mapping, and it keeps every response consistent with the last one you sent.

Common mistakes

• Answering in the future tense about controls that are not yet in place.
• Describing evidence instead of pointing to it.
• Claiming continuous or complete coverage the control does not actually deliver.
• Rebuilding the whole response from scratch each time one arrives.
• Leaving the answers unmapped to any standard the reader recognises.

Frequently asked questions

How is an AI governance questionnaire different from a security questionnaire? A security questionnaire tests how you protect systems and data. An AI governance questionnaire tests how you govern the AI itself, including which systems you run, who owns them, how you assess and monitor risk and how a person can intervene. Many customers now send both.

Which standard should I map my answers to? Map to the reference your customer is most likely to recognise. In Australia that is usually the Voluntary AI Safety Standard, with ISO/IEC 42001 for a customer that expects a certifiable management-system answer and the NIST AI Risk Management Framework for a customer aligned to that.

What if we do not yet have a full answer to a question? Say what is done and what is not. A precise partial answer holds up in due diligence. A vague claim that papers over what is missing does not, and it puts your other answers under suspicion once the reader notices.

Can Aicura complete the questionnaire for us? No. Aicura surfaces the picture and holds the evidence you answer from. It does not write the response, decide what to disclose or attest to your controls on your behalf. The accountable owner answers and signs.

Where Aicura fits

Aicura is your AI Register. It holds the AI systems in use as the record, versions each one as it changes and prompts you when a review is due, so the answer to “what AI do you run” is current rather than assembled the week the questionnaire arrives. Impact Assessments hold the risk decisions and their owners, which is most of what these questionnaires ask about, and Incidents holds the record of what went wrong and what you did.

The Evidence Vault seals each record so it can be shown unchanged since capture, evidence you don’t have to trust us for, cryptographically anchored and verifiable without Aicura in the loop. The Trust Centre lets you share that evidence with the customer running due diligence directly, rather than pasting summaries into a spreadsheet, and Attestation lets an accountable owner sign a statement against the record. Aicura surfaces the picture and holds the evidence. It does not write your response, decide what to disclose or attest on your behalf. You answer and you sign.

For the related work, read how to prepare for an AI governance audit and how to keep AI governance records that stand up. If you are weighing tooling, the AI governance software overview sets out what Aicura supports.

Sources

• Voluntary AI Safety Standard, Department of Industry, Science and Resources, industry.gov.au/publications/voluntary-ai-safety-standard
• ISO/IEC 42001:2023, AI management system, International Organization for Standardization, iso.org
• AI Risk Management Framework (AI RMF 1.0), National Institute of Standards and Technology, nist.gov/itl/ai-risk-management-framework

A note on this page

This guide is general information on how to respond to an AI governance due-diligence questionnaire against current Australian and allied guidance. It is not legal advice and it does not tell you what a particular customer or contract requires you to disclose. For how the guidance applies to your organisation, read the primary sources above and take your own professional advice.