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Before enabling an AI meeting assistant, find out what it records, where each artifact goes and who can retrieve it later. A promise not to train models on your data does not answer every question about retention, sharing or participant expectations.

This is an operational purchasing checklist, not legal advice or a hands-on vendor comparison. Use your organization's rules and relevant requirements for recording consent.

Map the artifacts separately#

A meeting can produce audio, video, a transcript, a summary, extracted tasks and searchable history. Those objects may have different retention rules and access controls.

For example, deleting a recording does not necessarily delete a summary copied into a team chat. Ask the provider which objects are removed together and which require separate deletion.

Zoom describes its approach in its AI Companion privacy lifecycle document. Read the documentation for the exact feature and account configuration you plan to use; do not extend one provider's policy to another service.

Ask the vendor questions that lead to a decision#

Request clear answers to these questions:

  • Which meeting content is processed, and by which services?
  • Can content be used for model training, and under what setting or agreement?
  • How long are recordings, transcripts and summaries retained?
  • Can administrators enforce retention and sharing settings?
  • Can external guests receive summaries automatically?
  • What happens when a participant or employee loses access?
  • Can you export useful records and remove unwanted ones?

If the answer is “enterprise only,” determine whether your actual plan includes the control. Do not purchase a personal subscription expecting an enterprise policy boundary.

Decide who may enable recording#

For a small team, assign an owner rather than letting bots join every calendar event by default. Decide which meeting types are suitable and how participants can request an alternative.

Use a simple announcement before enabling the tool: what will be captured, who receives the notes and where the records will be stored. Give people a workable way to decline, such as a human-written recap.

Do not treat a visible bot name as sufficient explanation. Participants may not know whether the assistant retains audio, shares a transcript or only produces a summary.

Run a low-risk pilot#

Use a fictional project discussion with consenting participants. Avoid customer records, credentials and sensitive personnel matters.

During the pilot:

  1. Check who can start and stop the assistant.
  2. Inspect every generated artifact.
  3. Confirm which participants receive a link automatically.
  4. Try access from an account that should not have permission.
  5. Remove the pilot artifacts using the supported controls.
  6. Check the documented deletion scope and any retained copies.

Record actual results. A successful pilot establishes behavior for the tested setup; it does not prove that every future meeting configuration behaves the same way.

Review accuracy before distributing notes#

An assistant can assign a task to the wrong person or turn a tentative suggestion into a decision. Ask a meeting owner to review names, dates, responsibilities and disagreements before distributing a summary.

Keep the transcript or agreed source record available when appropriate, so disputed notes can be corrected. Use our AI answer verification workflow for factual claims added to the recap.

Choose the lightest tool that meets the need#

If you only need a short list of decisions, shared human notes may be enough. If search across many meetings is valuable, evaluate the additional retention and access requirements deliberately.

The right purchase is the one whose controls fit your team, not the one with the longest feature list. For records you need to preserve independently, understand cloud sync versus backup before relying on synchronization alone.