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A customer asks us to delete their data. How do you handle copies in retrieval, logs, backups and trained models?

Try it in the practice workspaceDraft your answer before comparing it with the rubric.

Separate disabling access from completing erasure, and explain what evidence supports each part of the deletion promise.

Updated Nov 2026 · Original practice questions with worked answers and teaching rubrics. Our editorial policy explains the sources, review process and limits.

Case briefRead the inputs, then make your call

A customer requests deletion from an AI document assistant. This is a fictional case; determine whether the request concerns a tenant, an individual or an optional training use.

Scenario inputs
Active inventory2,400 derived objects; workers report 2,280 removed and 120 pending.
Residual accessTen pending index entries remain retrievable.
Other copiesSource replicas, chunks, embeddings, response caches, diagnostic logs, exports, backups and external processors may contain copies.
Model questionSome source data may have entered training datasets used by deployed model versions. Lineage and model retention are not yet established.
Customer expectationThe customer wants a completion statement. Legal retention exceptions and the applicable deadline still require confirmation.

Your task. Choose the immediate action, design a verifiable deletion workflow and write the scope of the status you can truthfully report.

Separate disabling access from completing erasure, and explain what evidence supports each part of the deletion promise.

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