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As of 13 August 2026, AI can answer customer proposal questionnaires.
Most people should hand this to a purpose-built tool.
Can you do it?
15 minutesto a draft.
30 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ita colleague
What the alternative costsThe supplied tool data does not price a human proposal-writing service.
If this goes wrong: you submit an unsupported claim or an unintended service commitment and damage the bid, customer relationship or delivery margin.
What to actually do
Use a tool built for this
The route this page recommends
Do it yourself
Second choiceA chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.
How to actually do it
- Open the customer questionnaire and copy its complete text, including instructions, scoring criteria, question numbers and response limits.
- Gather the current approved product descriptions, service specifications, pricing, implementation information, security material, accreditations, case studies and relevant company policies.
- Ask the owners of sales, delivery, security, finance and legal content for any current limits, exclusions or commitments that the source documents do not state clearly.
- Paste the questionnaire, source material and proposal context into a chatbot with the supplied prompt, then ask it to produce the answers and the evidence table.
- Compare every drafted factual claim, figure, date, accreditation and service promise with the current source document named in the evidence table.
- Send answers marked [NEEDS INPUT] or requiring commercial, technical, security or legal approval to the relevant colleague, and replace the placeholders with their approved wording.
- Paste the final answers into the customer's template, check its word limits and submission instructions, then have the proposal owner approve and send it.
Prompt
Answer the customer proposal questionnaire below using only the supplied source material. Do not invent capabilities, accreditations, customers, figures, delivery dates, security controls or contractual commitments. For every answer, identify the source document or section that supports it. If the material does not support an answer, write [NEEDS INPUT] and state exactly what information is missing. Preserve the customer's question numbering and answer every question in plain, specific UK English. Keep answers concise but complete, use the customer's terminology where appropriate, and do not make claims stronger than the evidence. Separate factual answers from suggested wording for any point that needs commercial or legal approval. At the end, provide a table with the question number, drafted answer, supporting source, confidence level, missing information and the internal owner who should approve it. Questionnaire: [PASTE QUESTIONNAIRE HERE] Source material: [PASTE APPROVED COMPANY, PRODUCT, SECURITY, SERVICE, PRICING AND POLICY INFORMATION HERE] Intended customer and proposal context: [PASTE CONTEXT HERE]
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
Hand it to a person
The distant thirdA person who owns the outcome does this end to end, worth it when the failure is dear.
What it gets wrong
- AI cannot know which capability your business is prepared to commit to when the source material is incomplete or ambiguous.
- AI cannot validate that a security, technical or operational claim remains current without an authoritative internal owner.
- AI cannot decide whether a commercially attractive promise would create an unacceptable delivery cost or contractual obligation.
- AI cannot replace approval from the people accountable for pricing, compliance, delivery and legal commitments.
- AI can make a plausible answer sound more certain than the evidence supports, especially when the questionnaire uses vague wording.
Even on a YES, the friction has a name: judgement under ambiguity, stakes of error and context depth.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 2 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 8 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT fill in a proposal questionnaire?
- Yes. Give it the questionnaire and approved company information, and it can draft answers, preserve the question structure and flag unsupported claims. You still need a colleague to check commitments, figures and specialist answers before submission.
- Can AI answer a security questionnaire?
- It can draft answers from your current security policies, certifications and control descriptions. It cannot confirm that a control exists or is operating today, so your security or compliance owner must verify and approve each answer.
- Will AI make up answers in a customer questionnaire?
- It can invent plausible capabilities, figures or commitments when the supplied material is missing or unclear. Tell it to mark unsupported questions as [NEEDS INPUT], require a source for every answer and check the result against current internal documents.
- Is it safe to use AI for a customer proposal?
- It is suitable for drafting when you use approved information and follow your organisation's rules for confidential customer and commercial data. Do not let it make unapproved promises, and have the relevant business owners approve the final questionnaire.
Nearby answers
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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