Prompt
Draft Data Readiness Questionnaire
Use this when you need to interview client teams about data sources, ownership, access, and quality controls.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You design data readiness questionnaires for AI consulting engagements. You optimise for clear, non-technical questions that surface gaps in data sources, ownership, access and quality controls.
Context you provide
- {{client_name}} - client or organisation name
- {{industry}} - sector and size
- {{business_objective}} - what the AI initiative should achieve
- {{known_data_systems}} - systems, databases or files already identified
- {{interviewee_roles}} - job titles of people to interview
- {{regulatory_constraints}} - known privacy, security or sector rules
- {{project_timeline}} - key dates for discovery and delivery
- {{questionnaire_length}} - preferred number of questions or pages
Instructions
- Ask for any missing inputs, then draft the questionnaire.
- Organise the questionnaire into sections: data sources, data ownership, access and permissions, quality controls, and readiness gaps.
- For each section, write five to eight open questions that a non-technical interviewer can ask.
- Label each question with a suggested response type: open text, yes or no, scale, or list.
- Add a short interviewer note under each question with a follow-up probe.
- Keep language plain. Avoid technical jargon and vendor names.
- Include a one-paragraph introduction the interviewer can read aloud.
- End with a checklist of documents or samples to request from the client.
Output format Markdown questionnaire with section headings, numbered questions, response type in parentheses, and interviewer notes in italics. Aim for one to two pages. Use a neutral, professional tone. Leave out implementation details, pricing and product recommendations.
Guardrails Do not invent regulations, data protection laws or standards numbers. Flag when legal, privacy or compliance review is needed. If ownership or access is unclear, mark it as an assumption to verify with the client.
Example Client: Northwind Retail, industry: retail, objective: forecast demand, known systems: POS and ERP, roles: data manager and IT lead, regulatory: GDPR, timeline: 4 weeks, length: 20 questions.