Your Meetings Are Data. Let LLMs Unlock Everyone’s Potential.

This isn’t a new idea, but it’s one I want to emphasize because I see teams still getting it wrong: with Zoom and Teams, we have the ability to record meetings — and I’ve made it a basic practice to do `exactly that. Unless it’s a one-on-one or a personal, ad hoc conversation, the recording is on.

I know how that can sound. Everything we say is being recorded? But surveillance isn’t the point. The point is that no one in the room should have to be the scribe.

The hidden cost of the note taker

Think about what we ask of the person taking notes. They’re capturing what everyone says, building the to-do list, creating the meeting artifacts — all while the actual conversation moves on without them. If you’re trying to lead a meeting and write down what everyone’s saying and track action items, it’s nearly impossible to participate in a meaningful, creative way.

And here’s the irony: the person we assign to take notes is usually the most organized, most focused person in the room. In other words, exactly the person who should be engaged from a leadership perspective — not tied down to minutiae.

This is where AI genuinely helps. It takes the toil of transcription off our plates so its power can be used to aggregate information, surface decisions, and draft the task list. That organized, focused person? Their energy gets redirected to reviewing the notes and driving the action plan — the work that actually requires their judgment.

A real example: 15 hours of planning, captured

Every quarter, we run product iteration planning sessions — roughly three hours a day, five days straight. That’s a 15-hour meeting marathon. No human note taker is going to capture 100% of what’s said over that stretch. Details get missed. Estimates get lost. Context evaporates.

Once the sessions wrap, I ask the AI to go back through the transcripts and write up the notes for each initiative and epic — then put that information directly into Jira for us. It does a great job: discussion points, estimates, the small decisions that would otherwise slip through the cracks.

The result is that everyone in the room gets to focus on creativity and decision-making — not just the people who happened to escape scribe duty.

A necessary caveat: review before you send

These AI-generated notes can’t go out as-is. Names get transcribed wrong. When six people are sharing a conference room mic, you don’t always know who said what. There are things a human needs to verify before the notes are distributed.

But that review takes minutes, not the entire meeting. It’s a huge jump start.

The bigger picture

The transcript isn’t just meeting notes — it’s an asset. Once you have it, it can feed other AI tasks downstream: status summaries, follow-up drafts, planning documents, Jira updates. One recording, many outputs.

So my advice is simple: hit record. Let AI handle the toil. And let your people actually meet in your meetings.

How is your team using meeting transcription? I’d love to hear what’s working — and what isn’t.