How to choose an AI meeting assistant

Pilot only with informed participants and non-sensitive meetings. Measure corrected transcript and action accuracy, then prove access, retention, export, and deletion before wider use.

Decision criteria

CriterionWhat to verifyDecision signal

Notice and controlDefine who can invite the assistant, how participants are informed, when recording starts, and how anyone can object or pause capture.Required for the shortlist

AccuracyMeasure names, numbers, decisions, speakers, uncertainty, and action items after human correction across accents and audio conditions.Required for the shortlist

Data lifecycleVerify audio, transcript, summary, embeddings, training use, retention, access, export, deletion, and subprocessor behavior.Verify before purchase

Action safetyRequire an owner to approve tasks and external messages; prevent an inferred statement from becoming an automatic commitment.Verify before purchase

Total-cost model

Seats or meeting hours + review and correction + storage + integrations + governance + incident and deletion handling.

Skip this if

Skip meetings involving restricted data or participants who cannot meaningfully understand and control the capture process.

Proof-of-fit checklist

Publish a participant notice
Test pause and opt-out
Score transcript and action accuracy
Review workspace permissions
Export and delete a meeting
Disable automatic external actions

What changes the answer?

Team size, workflow volume, regulated data, integration depth, support expectations, and switching cost can change the shortlist. Re-run the decision after any of those constraints changes.

Reference standard

NIST AI Risk Management Framework

Last methodology review: 11 August 2026. No vendor claim or affiliate offer is active on this page.