What is an AI meeting agent?

Start with a task grounded in a meeting

The word “agent” is used for many products. For meeting work, a practical definition is software that can use the discussion as context and help produce the next useful result. That result might be an agenda, a brief, minutes, or a draft presentation.

Consider a customer call. The customer explains a problem, your team discusses possible approaches, and both sides agree on a next step. A meeting agent can help turn that record into a proposal draft. You can ask it to preserve the agreed scope, flag missing information, and write for the person who will approve the project.

The important link is between the output and the evidence. A polished document that invents a requirement is not useful. Ask for the draft to reflect the conversation, then check the statements that affect cost, timing, or responsibility.

How recording, notes, and agent work connect

Recording captures the sound. Transcription turns speech into text. Notes organize the discussion. Agent tasks use that context to answer questions or create work. Each stage relies on the quality of the earlier record.

Meeting.ai accepts in-person recordings from the mobile app or browser, bot recordings from Zoom, Google Meet, and Microsoft Teams, and uploaded audio or video. Its transcription supports speaker identification in 30+ languages. Review unclear names and technical terms before using them in a client document.

After the notes are reviewed, the agent can draft editable PowerPoint presentations, spreadsheets with live formulas, documents, and PDFs. A Visual Note can show the discussion on one page. An audio brief gives someone another way to catch up when reading a long record is inconvenient.

Why meeting history changes the request

A single meeting rarely contains every fact a team needs. People refer to last week's agreement, a customer's earlier concern, or a file shared before the call. Meeting.ai's Memo memory keeps context across meetings, including priorities, tradeoffs, decisions, people, and files.

That supports questions such as “Why did we postpone the launch?” or “What did the customer ask us to change?” Meeting.ai can answer across meeting history with the source. Use the source to check whether a past decision still applies. Later meetings may have changed it.

Give the agent a brief you can evaluate

You do not need a technical instruction. State what to use, what to make, and who it is for. A request like this gives the draft a clear boundary:

Use today's planning meeting to draft a project update for the sponsor. Include agreed milestones, current risks, and questions that still need an owner. Keep proposed dates separate from confirmed dates.

Read the result against that request. Did it include the right meeting? Does it distinguish a risk from a decision? Are the open questions still open? Clear instructions make these checks easier.

Skills extend what Meeting.ai can help with, including research, writing, presentations, analysis, spreadsheets, images, and audio. People can install skills or create Private Skills for their own workflows. Choose a capability because the meeting calls for that work, rather than adding steps without a purpose.

Keep responsibility with the people involved

An agent can help reduce the work between a conversation and a draft. It cannot know that a commitment was misunderstood unless the record or your instruction makes that clear. Check figures, dates, scope, and recipients before sharing.

Start with a bounded task from a real meeting. Review the result, correct the context, and use that experience to decide where the agent fits into your routine. The useful measure is whether the meeting produces a clearer, more usable piece of work.