AI Meeting Note Taker: A Buyer's Guide From 224 Meetings
Quick Summary
How AI meeting note takers work, bot vs bot-free vs in-person capture, and what 224 recorded field sales meetings showed about notes, actions and coaching.
An AI meeting note taker records a conversation, transcribes it, and turns it into a summary, a list of action items with owners and, in the better tools, a searchable record you can query weeks later. Most tools either send a bot into Zoom, Google Meet or Teams, or capture audio on your own device without a bot. Very few handle a meeting in a customer's office well. For a team, picking the right one depends less on headline transcript accuracy than on three things: where your meetings happen, which languages they're in, and what happens to the notes afterwards.
We build an AI meeting recorder at Shiken, so we're not neutral. What we can offer is evidence most buyer's guides don't have. During a pilot, a European B2B field sales team (37 reps) recorded 224 real customer meetings, all of them face to face and in several languages. This guide uses what that pilot showed alongside what the tools themselves publish.
Editorial note: This article compares Shiken with Fathom, Granola, Otter, Fireflies, Gong and Google Meet, plus other meeting assistants, using each vendor's published product information and third-party sources available at the time of writing, last reviewed on 12 November 2026. Capabilities, packaging and pricing change; if you spot something out of date, email info@shiken.ai and we will review it.
How an AI meeting note taker works, and where each step breaks
Almost every product runs the same pipeline. The useful question is what fails at each stage.
- Capture. A bot joins the call, an app records your computer's audio, or a phone records the room. Breaks when: the bot is blocked by the customer's IT, the laptop isn't in the meeting, or the signal drops at a customer site.
- Transcription. Speech becomes text. Breaks when: several people talk at once, accents are strong, or the conversation switches language.
- Speaker separation. The transcript is split by speaker. Breaks when: everyone is around one phone on a table. Online calls give the software a separate audio track per person; a room does not.
- Summary and action items. A language model writes the notes and pulls out commitments. Breaks when: nobody said out loud who owns a task, or when the summary template assumes every meeting is a discovery call.
- Delivery. Notes go to email, Slack, a CRM or a shared workspace. Breaks when: the notes sit in an app nobody opens.
Most comparison articles grade steps 2 and 4. For a team, steps 1 and 5 decide whether the tool gets used.
Bot, bot-free or in-person: decide this first
| Capture mode | How it works | Best for | Watch out for |
|---|---|---|---|
| Calendar bot | A named participant joins Zoom, Meet or Teams | Internal and recurring online meetings | Some customers dislike bots or block them |
| Bot-free desktop | App records your computer's audio | Sensitive external calls, 1:1s | Only records what your laptop hears |
| Phone / in-person app | Phone or tablet records the room | Field visits, on-site workshops | Speaker separation, patchy signal |
| Built into the meeting platform | Zoom, Teams or Meet generate notes | Teams standardised on one platform | Plan eligibility and language limits; check in-person coverage |
Built-in options are worth checking first because you may already pay for them. Read the small print, though. Google's own help page says Meet's "Take notes for me" needs an eligible Google Workspace edition or Google AI plan and supports only one language at a time. That second limit matters more than it sounds, as the pilot below shows.
If more than a fifth of your team's important conversations happen in person, filter out every tool that can't record reliably on a phone without a connection. Most buyer's guides skip this. Check each tool's in-person capture yourself rather than relying on roundups.
What 224 field sales meetings taught us about AI meeting notes
The pilot team sold B2B products to business customers across several European countries. Reps recorded meetings on a phone or desktop app. Each recording was started by hand, with no calendar prompts. Here's what held up and what didn't.
1. People will record in-person meetings, but only if it's easy and they're reminded
37 of the 61 invited reps recorded at least one real customer meeting. Weekly volume grew from the first week to the peak, and a stable core of reps recorded every week.
The warning sign was the drop-off. Weekly active reps fell from 16 to 13 with no reminders in place. When you evaluate a tool, ask how it prompts people before a customer visit, such as a calendar nudge. A good recording button isn't enough.
2. Action items are the real product, and they die if they don't reach the CRM
The system pulled 1,447 action items with named owners. A summary and follow-up email was drafted for all 224 meetings. Reps never had to log in to receive them, which we think explains why adoption held up.
But at the end of the pilot, 0 of those meetings were linked to an account or deal in the CRM. The commitments existed, but the CRM couldn't see them. If your buying case depends on follow-through, test CRM write-back during the trial. Don't take it on trust from the feature page.
3. Assume your meetings aren't all in English
40% of the meetings weren't in English: Portuguese, Spanish and Italian. Reps got notes in the language of the meeting, and the manager got coaching reports in English.
Check language support on the vendor's own pricing page, not on a review site. As of 12 November 2026, Otter's pricing table lists AI transcription in six languages. Fireflies says English is its primary language, with Spanish, French, Portuguese and Italian supported and 100+ others in beta. Google Meet's note taker works in one language per meeting. For a pan-European team, these differences decide which tool you can use.
4. Most meetings aren't discovery calls
Summary templates often assume a first call: pain, budget, next step. The pilot's mix was different: 77 follow-ups, 44 quarterly business reviews, 39 discovery calls, 30 proposal meetings and 34 others. If the tool forces one template on every meeting, a QBR summary will look like a badly filled-in discovery form. Look for templates by meeting type, or at least editable ones.
5. Notes become coaching data, but only if someone coaches
Every meeting was scored against a four-stage rubric: opening and introduction, understanding the customer, identifying solutions, and close. The average was about 47/100 and stayed flat across the pilot. The weakest stage across the team was the opening. The strongest was identifying solutions.
There are two lessons here. First, a recorder that scores every meeting shows a team-wide gap that ride-alongs would never surface. A manager sees a handful of meetings, and the pilot scored all of them. Second, scoring alone changed nothing. Scores stayed flat because nobody had started coaching against them yet. If a vendor promises "AI coaching", ask what the manager is meant to do each week with the output.
6. The value grows when you can search across meetings
Across the 224 meetings, cross-call analysis found recurring themes, objections and customer questions, each tagged to the exact meeting and quote. The top objection was competitors undercutting on price and terms. The top theme was that customers judge total cost, not list price.
No one could have compiled that by hand. And it got used: the person running the rollout used the dashboard and the "ask the meetings" assistant regularly, asking many questions of the meeting library.
| Without a note taker | With one (observed in the pilot) | |
|---|---|---|
| Notes and follow-up | Written by the rep, often skipped | Summary and follow-up drafted for all 224 meetings |
| Commitments | In heads and inboxes | 1,447 action items with owners |
| Coaching coverage | A handful of ride-alongs | Every meeting scored on 4 stages, with quotes |
| Voice of customer | Anecdotes, rep by rep | Themes, objections and questions across 224 meetings |
| Languages | English-only tooling | 40% of meetings in Portuguese, Spanish and Italian |
How to evaluate an AI meeting note taker in one week
Skip the feature grid. Run this test on real meetings during a free trial.
| Test | How to run it | What a pass looks like |
|---|---|---|
| Your worst audio | Record a real meeting in a noisy room or on a phone | Names, numbers and product terms mostly correct |
| Speaker labels | Record a 3+ person in-person meeting | You can tell who committed to what |
| Your languages | Record one meeting in each language your team sells in | Notes in that language, usable without fixing |
| Action items | Compare extracted tasks to what was actually agreed | Every real commitment has an owner |
| CRM write-back | Link one meeting to a live deal | Summary and tasks appear on the record |
| Search | Ask "what did customers say about pricing this week?" | Answer cites the exact meeting moment |
| Offline capture | Record with flight mode on, then reconnect | Full meeting uploads, nothing lost |
| Consent and data | Check consent notice, retention and training opt-out | Admin can set all three org-wide |
Which kind of tool fits your team
Prices and plan details below come from each vendor's own pricing page, as checked on 12 November 2026. They change often.
| Tool | Capture | Free plan | Paid entry point | Pick it if |
|---|---|---|---|---|
| Fathom | Bot, or bot-free (beta) | Yes | Business from $25/user/mo billed annually (2-user min), adds CRM field sync and AI scorecards | You want a fast, free notetaker for online sales calls |
| Granola | Bot-free device audio; desktop and mobile apps | Yes, 30-day history | Business $14/user/mo; Salesforce on Enterprise ($35) | You want private, bot-free notes you can edit |
| Otter | Joins online meetings; iOS/Android apps | 300 min/month, 30 min per conversation | Pro, $8.49/user/mo billed monthly | You need live transcription and a mobile app |
| Fireflies | Joins online meetings; iOS/Android app | Yes | Paid plans per seat; the pricing page shows no dollar amounts | You want a wide integration library and searchable archive |
| Gong | Conversation analytics for customer calls and meetings | Listed on pricing page; limits not stated | Pricing on request: per-user licence plus platform fee | You're an enterprise revenue team buying forecasting too |
| Shiken | Bot, bot-free, desktop and phone, records offline | Unlimited recording and transcription, 30-day history, 5 AI summaries/month | Enterprise per seat, on request | In-person or multilingual meetings, and you want notes to feed coaching and roleplay practice |
Our honest read: if your meetings are online, in English and you mainly want clean notes, Fathom's or Granola's free tiers are hard to beat. Start there. Teams that need conversation intelligence plus forecasting at enterprise scale tend to look at Gong. Shiken is the better fit when meetings happen in person, in several languages, or when you want the recorder to score calls against your own framework and turn weak moments into AI roleplay practice. Our AI meeting recorder comparison goes deeper, and there are head-to-heads against Granola and Fathom.
Consent, privacy and data
Recording-consent rules differ by country and, in the US, by state, so get your legal team to sign off before rollout. Practically:
- Make consent visible and stored. In the pilot, every recording carried a consent state with the disclosure wording saved alongside it. If a customer later asks, you can show what they were told.
- Set retention deliberately. Decide how long audio, transcripts and summaries live, and whether that differs for customer meetings and internal ones.
- Check model-training terms. Ask whether your recordings are used to train the vendor's models, and whether an admin can opt out for the whole organisation, not just per user.
- Control who sees what. Coaching scores on individual reps are sensitive. Agree who can see them before the first meeting is scored.
What goes wrong in team rollouts
- Buying for transcript accuracy and ignoring capture. If half your meetings happen in person, a perfect bot is half a product.
- Treating summaries as final. AI notes are a first draft. Names, numbers and commitments need a human glance before they go to a customer.
- Scoring without a coaching rhythm. Our pilot's scores stayed flat until coaching was planned around them. Book the monthly 1:1s and team sessions before you turn on scoring.
- No CRM link. Without it, action items stay in a separate app and the pipeline never sees them.
If you're turning recorded calls into coaching, our step-by-step guide to coaching from call recordings covers the manager side.
FAQs
Can I use an AI note taker for in-person meetings?
Yes, but choose a tool built for it. You need a phone or desktop app that records the room, keeps recording without a signal and uploads later, and copes with several speakers on one microphone. Bot-based tools can't join a meeting that isn't on a video call. In our pilot, all 224 meetings were physical meetings captured this way; online meetings were out of scope.
Is Google Meet's AI note taker free?
Not on a standard personal account. Google says "Take notes for me" needs an eligible Google Workspace edition or Google AI plan, and it handles one language per meeting. If you already pay for an eligible plan, try it before buying a separate tool.
Which is the best AI meeting note taker?
It depends on your meetings. For free notes on online calls, Fathom and Granola are strong starting points. For live transcription on a budget, Otter. For in-person, multilingual sales meetings where notes should feed coaching, a recorder with offline phone capture and rubric scoring, such as Shiken, fits better. Run the one-week test above on two shortlisted tools before you decide.
