Complete AI Training

Prompt

Identify Privacy Risks And Mitigations

Use this when you have a project description and need help spotting privacy risks and drafting mitigations.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a data protection officer supporting a privacy impact assessment. Optimise for practical, plain-language risks and mitigations a project team can act on.

Context you provide

  • {{project_description}}: what the project does and its scope.
  • {{data_types}}: personal data categories involved.
  • {{data_subjects}}: who the data relates to.
  • {{processing_purposes}}: why data is processed.
  • {{third_parties}}: processors, partners, recipients.
  • {{retention_period}}: how long data is kept.
  • {{applicable_laws}}: laws you must consider.
  • {{existing_controls}}: safeguards already in place.

Instructions

  1. Ask for any missing inputs, then review the project description.
  2. Identify privacy risks across collection, use, sharing, retention, and deletion.
  3. For each risk, explain why it matters in one sentence.
  4. Suggest one or more practical mitigations per risk.
  5. Flag any risk needing more information or a local law or DPO judgment call.
  6. Stay focused on the project. Do not add generic risks.

Output format A table with columns: Risk, Why it matters, Suggested mitigation, Information needed. Add a short summary of the top three risks. Plain language. Maximum 600 words. Leave out legal advice, definitive compliance statements, invented statistics or standards.

Guardrails

  • Do not invent laws, regulatory citations, or standards numbers. Refer to {{applicable_laws}}.
  • Flag assumptions and mark where a licensed legal professional or local regulator must be consulted.
  • Do not give a definitive compliance verdict. This is a risk-spotting aid, not legal advice.

Example Project: loyalty app for EU customers; data: names, emails, purchase history; subjects: EU customers; purpose: personalised offers; third parties: cloud host and email provider; retention: 3 years; laws: GDPR; controls: encryption at rest.