AI & ML

Do you log AI interactions for audit purposes?

How to answer this security questionnaire question, with an expert response your security or GRC team can adapt.

Expert answer

Log AI requests and responses with the same rigor as other sensitive operations, capturing who initiated the call, what feature was used, and when. Retain these logs under your standard policy and make them available for audit and incident investigation.

What the security reviewer is checking

This question pulls in two directions at once, and reviewers know it: audit teams want enough logging to reconstruct what the AI did and who invoked it, while privacy teams do not want sensitive prompt content accumulating in yet another data store. The strong answer demonstrates a deliberate position: exactly which fields are captured (actor, timestamp, feature, model, decision/output disposition), whether full prompt and completion text is stored or excluded, where logs live, how long they are retained, who can access them, and whether customers get visibility into AI activity in their own tenant. "We log everything" and "we log nothing" are both red flags — the first for data minimization, the second for accountability.

Example response you can adapt

This is an illustrative template, not a real vendor's security posture. Replace every claim with what is actually true for your organization before submitting it.
Yes, with deliberate scope. Every AI interaction generates an audit record capturing the authenticated user, organization, timestamp, feature invoked, model and version used, request outcome, and whether the user accepted, edited, or rejected the output — sufficient to reconstruct who used AI, on what, and what happened as a result. Full prompt and completion text is handled separately under data minimization: content payloads are retained only transiently for abuse detection and quality monitoring with a short retention window, are encrypted, and are excluded from the long-lived audit trail. Audit records are stored in our append-only logging pipeline, retained for one year, and access-restricted to security and compliance personnel with all access itself logged. Customer administrators can view AI usage activity for their own organization in the audit log, and AI-generated content in the product is flagged as such, preserving provenance. Model providers process requests under zero-retention terms, so no additional interaction history accumulates outside our environment.

Evidence reviewers expect you to attach

  • Logging and monitoring policy covering AI interaction events
  • Audit log field schema for AI events (sanitized sample record)
  • Retention schedule entries for audit records and content payloads
  • Product documentation for the customer-facing audit log

Follow-up questions reviewers ask next

  • Is full prompt and response text retained, and for how long?
  • Can we export AI interaction logs for our own tenant?
  • Who on your side can read AI interaction content, and is that access logged?
  • How do the logs distinguish AI-generated content from human edits?
  • Do your model providers retain any interaction history on their side?

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