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Compliance & standards

Good AI governance follows the data.

Map personal information, sensitive business material, and derived copies before deciding how to protect them.

The system view A conceptual view to help connect the parts. It is an illustration, not a product architecture. Select the image to enlarge.

Draw the complete journey

Information can appear in an upload, prompt, retrieved passage, response, embedding store, evaluation set, and application log. A simple diagram often reveals more than a long policy. For each stage, identify the purpose, owner, access conditions, storage location where known, and retention rule. Include support and debugging workflows.

Ask whether the data is necessary

More context is not automatically better. Consider whether the task can work with fewer fields, synthetic examples, aggregated information, or an approved subset. Removing direct identifiers does not necessarily make a dataset anonymous. Review what people could infer from the remaining information and how outputs might reveal details.

Carry access permissions into retrieval

A document assistant should not become a new path around source-system restrictions. Check access when selecting material for the current user, not merely when displaying the final response. Test permission changes, document deletion, group membership changes, and cross-user queries. Consider derived indexes and cached results as well as the original files.

Treat retention and deletion as workflows

A policy saying “delete after thirty days” needs an implementation and evidence. Determine which stores it covers, how backups and derived copies are handled, and what the provider can actually delete. Set expectations for exported content and local copies. Assign someone to resolve discrepancies between the intended rule and the product’s behavior.

Keep legal analysis tied to context

Privacy requirements vary by jurisdiction and the organization’s role. Identify the applicable rules and seek the right review for the intended processing. A vendor promise about model training does not settle every question about lawful use, transparency, individual rights, or security. Explain the specific data practice rather than using “private AI” as a blanket assurance.

The whiteboard A visual recap of the questions, decisions, and evidence on this page. Select the image to enlarge.

PUT IT INTO PRACTICE

A useful next step

  1. Trace one sample record through the application.
  2. List every stored or derived copy.
  3. Test revocation and deletion in a lab.
  4. Record unresolved retention and processing questions.

Keep the result: record the decision, owner, supporting evidence, and the next review trigger.

Go to the source

These links support further learning. The worked example and practical exercise are SyruSec’s own educational interpretation.

KEEP THE THREAD GOING

Related reading.

Illustration