Every meeting produces decisions, actions and context — then most businesses lose all three within a day. The fix is now genuinely cheap; the craft is in the details.
The pipeline
Capture — a notetaker joins calls automatically, or recordings are pulled from your meeting platform. Transcription — modern speech models handle accents and crosstalk far better than two years ago. Understanding — a language model produces the useful artefacts: a summary someone would actually read, decisions made, actions with owners. Filing — the output lands where the client or project lives: the CRM record, the project file, the deal room. This last step is where most tools stop and most value lives — a summary in the meeting tool's own archive is barely better than nothing.
The details that decide success
- Consent, stated plainly. UK law and basic decency: people in the meeting should know it's captured. A standing line in invites does it.
- Client-facing calls need judgement. Some clients won't want a bot in the room. The system needs a no-notetaker path — a quick voice memo afterwards, transcribed the same way.
- Actions must land somewhere real. Extracted actions that live in a summary nobody opens are theatre. They belong in the task system, assigned, with the meeting linked.
- Retention policy. Recordings and transcripts are personal data; decide what's kept and for how long. See GDPR and AI.
What it's worth
Count it: (people in meetings × minutes per week writing up) plus everything currently lost because nobody wrote it up — the action agreed and forgotten, the context that left with the account manager. For a 20-person business, the write-up time alone is commonly £15,000–£25,000 a year. This is usually one of the first automations we recommend because adoption is easy: nobody has to change how they work — the meetings simply start filing themselves. It's also a natural first feed for a Company Brain.
Want this looked at in your business? M22 is a London-based AI consultancy. A thirty-minute call gets you an honest read on where automation would pay, and where it wouldn't.
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