Turning a meeting
into actions with AI.

Why the summary from a recording is not enough

A transcript holds what was said in the meeting. An action needs more than that: a person who owns it, a date, and enough context for that person to do it without asking again. When someone says “let’s get the revised quote to them”, the transcript does not say who usually sends quotes, which version of the quote was discussed or what the customer was told last time. The AI fills those gaps with a plausible guess or leaves them open, so the list that arrives after the meeting reads well and still needs someone to work out who does what.

Earlier decisions are the other gap. A meeting often comes back to a subject that was settled a month before, and a transcript read on its own treats the discussion as new. Without the earlier decisions, the AI can list an action that contradicts one of them, and the person checking the list has to remember what was agreed in order to catch it.

Give the AI what the transcript does not contain

The first piece of work is to write down, once, what someone who sat in every meeting would know: who is responsible for which kind of work, the customers and projects in progress, the decisions already taken, and where your team keeps track of its work. This fits on a short page in plain words, kept up to date by the people it describes. When someone changes role or a project closes, the page is edited, and the next meeting is read against the new version.

Each meeting then adds to it. The transcript is kept with the project it concerns, alongside the important emails on the same subject, and the decisions taken in the meeting are recorded apart from the discussion, so the next meeting starts from what was settled. That material gives the AI its context for the work that follows, and it is what saves you explaining the same decisions and background again at every meeting.

This is one part of a wider structure: your business knowledge written down once and read at the start of each task, which we describe in what an AI adoption consultant does.

From the recording to the actions

The meeting is recorded with the agreement of everyone in it, and the transcript is filed with the project it concerns. The AI reads it alongside the earlier decisions and the list of who does what, then proposes each action with an owner, a date and the sentence of the meeting it comes from, so the person checking the list can see straight away why each item is there.

When the meeting did not settle something, such as an action with nobody named or a date that was never agreed, the AI does not choose for you. It lists the point as a question for the person who ran the meeting, who answers it in a line, and the answer goes back into the record. Once the list is confirmed, the tasks are created where your team already works, each with the sentence it came from.

What the AI may do after a meeting

What the AI is allowed to do with a meeting is settled before it starts, like any other access. The transcript gives it working context and no authority to act on what was discussed. It files the record, proposes the actions and drafts the recap, and three things stay with a person: sending anything to someone outside the business, agreeing a date or a price with a customer, and giving work to someone who did not agree to it in the meeting.

A recap sent to a customer is a commitment in writing, so it is prepared as a draft and a person reads it before it leaves. Recording has its own rule: everyone in the meeting knows it is recorded and agrees to it, and a meeting where that agreement is not given is not recorded. We explain how access and approvals are set for the rest of the business in adopting AI securely and on our security page.

Which meetings to start with

Start with a meeting that happens every week with the same people and the same subjects, such as your operations or team meeting. The list of who does what is short to write down, the actions are easy to check at the next meeting, and each correction shows where the written context is incomplete.

Calls with customers come next, once the lists from internal meetings prove reliable, because a recap to a customer carries more weight and its context includes what was agreed with them. Some meetings are better left out of recording altogether, such as a conversation about one person’s performance or pay. Deciding which meetings are recorded and which stay manual is part of the setup, and the list can change as your team gets used to it.

Your team also needs to know how to check a list of actions critically and correct it, which we cover in AI adoption training for your team.

How we start

The first step with us is a free AI pre-audit: 45 minutes on a call where we look at how you and your team use AI today and which work is worth handing over first. Bring the notes from a recent meeting and what came out of it. You leave with a clear next step, with or without us.

If you decide to go further, we set this up as part of the Sprint, alongside the rest of your business knowledge and the access for each role. See how we help and what we have built for other businesses, including the meeting knowledge capture described here. The same approach to context applies to answering your customers’ emails, and if your first question is where the recordings would be stored, we cover that in AI tools and your business data in Australia.