Can I trust AI meeting notes enough to stop taking my own?

Why do AI summaries invent commitments?

The reasonable hope is that recording the whole meeting should give you a better record than hurried typing. It gives you more material. Turning that material into a short list of next steps still requires choices about meaning.

Consider this invented exchange, with illustrative timestamps:

Now suppose the summary says: “Maya will send finance the revised estimate by Friday.” It contains familiar words from the conversation, but it creates a promise. Maya offered conditional checking, Jo suggested a different task, and neither set Friday as a deadline.

There are several places for this to go wrong:

• Compression drops conditions. A rewritten sentence can lose “if finance sends the costs” while keeping “Maya” and “check the numbers.” The shorter version changes what was agreed.
• Speaker attribution moves a promise. Speech recognition produces words; speaker diarization labels who spoke when. These are distinct jobs, even when a product combines them. A correct sentence attached to the wrong person becomes a wrong assignment.3
• Task extraction turns suggestions into obligations. A request to find next steps invites the system to interpret “someone should check” as work to assign. In the example, treating Jo's suggestion as Maya's acceptance would create a task without agreement.
• A later correction gets lost. “Friday” might occur early in a longer discussion, then be withdrawn. A summary that keeps the first date and omits the withdrawal can look perfectly sensible on its own.

These examples explain possible failures; they aren't findings from tests of the named apps. The FRANK paper distinguishes errors in what happened from errors in who was involved; it also covers wrong times and unsupported additions. It studies summaries of news articles, so its error categories help explain the problem without establishing an error rate for today's meeting products.4

Think of a restaurant order slip. “Could we get the fish if you can leave out the nuts?” needs an answer before the kitchen has an order. A neat slip saying “fish” has saved space by throwing away the part that determined whether to cook it. Meeting summaries can make the same mistake with a dependency. (The condition may be the most important word in the sentence.)

What should I keep writing down myself?

Keep the details you would struggle to reconstruct if capture failed: decisions and unresolved objections, plus the exact limits on your own commitments. Write short lines beside the meeting agenda. You don't need a second transcript.

For example: “Estimate still blocked on costs. I agreed to check numbers only. Delivery date open.” These are personal notes to compare against the generated summary, not a substitute for confirming the shared record.

Before the meeting ends, read back commitments that matter: “Maya, are you agreeing to check the estimate once the costs arrive? Are we leaving the date open?” Record the answer. This changes the input the summarizer receives and gives the people involved a chance to correct it immediately. Silence after the meeting is not confirmation; keep an unanswered item marked unconfirmed.

I'd keep this habit even with a product whose summaries usually look right. A readable paragraph is hard to audit when nobody has said what counts as agreement.

How do I review AI meeting notes in five minutes?

Use this as a time budget for a routine meeting with a short action list. Its speed and missed-error rate have not been measured. If there are too many commitments to verify, keep the remainder marked unreviewed and spend longer before assigning them.

1. Spend one minute checking capture and decisions. Open the transcript and your brief notes. Check that capture covers the discussion you need, including the end of the meeting. Compare the summary's decisions with your notes. Flag anything described as agreed when you remember an open question.

2. Spend two minutes tracing commitments to their source. Open the source passage for each action item. Check the task, who accepted it, the due date and any dependency. Read the turns before and after the cited line, then look later in the transcript for a changed decision. Replay the relevant audio if a name or a negative such as “don't” seems wrong. When a field wasn't agreed, write “Owner unconfirmed” or “No deadline agreed” instead of accepting a guess.

3. Spend one minute checking what the summary left out. Compare it with your decision notes and the meeting agenda. Check that rejected options remain rejected and blocked work remains blocked. Look for commitments missing from the action list. Reviewing only the generated list cannot catch a task the list omitted.

4. Spend one minute correcting the shared record. Edit the summary and action list, then ask the relevant people to confirm unresolved items. Add a review note with the reviewer and date. If time runs out, state which items remain unchecked. Review before copying tasks into another system. Check the destination task or email too if an earlier version has already been sent there.

For the invented exchange above, a defensible record would read: “Maya offered to check the numbers if finance supplies the costs. Sending the estimate and a deadline remain unconfirmed.” That wording keeps the useful part of the discussion without assigning extra work.

Keep the evidence beside each proposed task. Here is an example record, filled only from that invented exchange:

Keep suggestions in a separate list until someone accepts them. A missing deadline is an honest field value; filling the box with a guess creates an agreement the meeting never made.

You can also ask an assistant to help locate evidence:

For each proposed action item, show the exact supporting words and the surrounding exchange, with a timestamp if available. Separate explicit commitments from suggestions. Leave the owner or deadline unconfirmed when nobody agreed to it. Include any later correction or withdrawal.

Treat the returned quotes as pointers to check in the original transcript. Asking the same system to explain its answer doesn't create independent evidence. A faithful summary can also repeat a bad transcript; compare disputed wording with audio or ask the speaker. (Two outputs agreeing is little comfort when both use the same mistaken words.)

Which products show source quotes or timestamps?

Granola and Otter document direct routes from generated notes or tasks to transcript evidence. Fireflies documents timestamped exports. Fathom and Circleback describe citations for assistant answers. Circleback also documents links to selected transcript passages. Those are different kinds of support, so check the route you will actually use.

These come from each maker's own documentation, not tested results. “Not verified” means the reviewed documentation didn't establish that particular capability.

For reviewing individual generated commitments, I'd start by inspecting Granola's note sources or Otter's action-item links. That is a recommendation about the documented review controls. This page has no matched accuracy results establishing which product makes fewer mistakes.

A timestamp answers “where should I look?” You still have to decide whether the passage supports the claim. A link to Jo's suggestion in our example would locate relevant text while failing to prove Maya agreed.

When should I spend longer on review?

Spend longer when a wrong assignment would start expensive work or communicate an approval outside the meeting. Recheck the full relevant exchange and get explicit confirmation from the person concerned. A five-minute timer shouldn't decide whether an uncertain commitment becomes official.

Also check that correcting the transcript corrected the version people will read. Otter's conversation guide specifically says its existing summary cannot be regenerated with newly tagged speakers; it suggests using Otter Chat to generate a summary incorporating edits.2 For the other products, this page doesn't establish how corrections flow through to every shared copy or integration. (An exported task deserves its own check.) If a wrong commitment has already been shared, send a correction to the same recipients rather than relying on an edit they may never see.

If your approved capture settings don't save audio, use the transcript and ask participants to resolve uncertainty. Keeping a recording has its own privacy and retention costs; agree on an appropriate capture method before the meeting. Our guide to checking what leaves your Mac covers a separate part of that choice.

About this page

Candor is being built as personal voice intelligence for everyone. You can join the Candor waitlist at candor.inc. Candor's own documentation is at candor.inc/docs.

Candor's docs on this page's topic: Open a citation.

Last checked: 4 November 2026. Product claims come from first-party documentation, and facts about Candor come from Candor's documentation [12] and homepage [11]; no product accuracy tests have been run for this page. The five-minute routine is an editorial recommendation awaiting testing. Report an error to support@candor.inc.