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AI Security and Ethics Checklist for Engineering Teams

A practical pre-release checklist for AI features covering security, misuse risk, transparency, and governance.

AI security and ethics checklist cover

Shipping AI features without security and ethics checks creates hidden operational risk.

Use this checklist before each release.

1) Data and privacy

  • Confirm data minimisation in prompts and context.
  • Remove secrets and personal data from logs.
  • Enforce retention windows for model inputs and outputs.
  • Validate third-party processor boundaries.

2) Security controls

  • Restrict tool permissions by role and environment.
  • Validate all tool outputs against strict schemas.
  • Add prompt-injection defences for external content.
  • Require approval gates for high-impact actions.

3) Safety and misuse

  • Define clear disallowed use cases.
  • Add risk prompts for potentially harmful requests.
  • Add user-visible warnings for uncertain outputs.
  • Add abuse monitoring and escalation paths.

4) Transparency and trust

  • Disclose where AI assistance is used.
  • Explain known limitations and confidence boundaries.
  • Track and review user-reported failures.
  • Document rollback and kill-switch procedures.

5) Governance and compliance

  • Maintain model and prompt version history.
  • Document risk assessment per release.
  • Map obligations for regulated use cases.
  • Train internal teams on AI literacy responsibilities.

Release gate rule

If any critical checklist item is unresolved, release as limited preview only.

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