Can you use ChatGPT to answer security questionnaires? What works and what goes wrong

When a 150-row questionnaire lands, pasting it into ChatGPT or another AI chatbot is tempting. Sometimes it helps. But a security questionnaire is a set of factual statements about your company that may end up in a contract, and a general chatbot doesn’t know your company.

The short answer

Yes for wording, no for facts. A chatbot is good at turning your notes into clear sentences. It is not a source of truth about your controls. If you give it no information, it fills the gap with what companies usually do, and that is exactly the kind of answer a security reviewer is trained to spot (see 10 answers that invite follow-up questions).

Where it helps

• Rewording: you paste a rough note (“MFA on everything, Google Workspace, AWS console, GitHub”) and get a clean sentence back.
• Summarising a policy you paste in, so you can find the relevant part quickly.
• Checking a set of your answers for contradictions or vague wording.
• Starting a first draft of a policy document that you then rewrite to match what you really do.

Where it goes wrong

• Invented answers. Ask “Do you encrypt backups?” without context and you will often get a confident “Yes, all backups are encrypted with AES-256.” Maybe true, maybe not. The model has no way to know.
• No sources. Reviewers ask where an answer is documented. A chatbot answer has no link back to your policy, so you have to check every one by hand.
• Inconsistency. Ask the same question twice, in different sessions or different wordings, and you can get different answers. Questionnaires repeat themselves on purpose to catch exactly that.
• The file. You still copy each answer back into the customer’s spreadsheet, respect their dropdowns, and keep the formatting.
• Confidential data. Questionnaires and your internal policies are often covered by an NDA. Before pasting them into any AI service, check your plan’s data settings (whether conversations are kept or used for training) and what you have agreed with the customer.

If you use a chatbot, set rules

1. Paste the relevant source (the policy section, your notes) along with each question.
2. Tell it to answer only from what you pasted, and to say “not enough information” otherwise.
3. Check every answer against the source before it goes into the file.
4. Keep your approved answers somewhere you can reuse, so the next questionnaire starts from checked answers instead of a new chat.

This works, but it is slow for a long questionnaire. Most of the time goes into finding the right source for each question and checking the result.

What a dedicated tool does differently

A tool built for questionnaires does the source-finding for you. Rendro searches your own documents and approved past answers for each question, drafts the answer only from what it finds, shows the source for every answer, and marks the question “needs review” when your documents don’t support an answer, instead of guessing. Then it writes the answers back into the customer’s original file and saves the approved ones for next time.

Rendro doesn’t use your documents or questionnaires to train AI models. You can try it free for 14 days, no card needed.