How do I use AI in project management?

How to do it

1. 1

   Start with the meeting record

   Let the AI transcribe the call and write the minutes, the decisions and the open questions. This is the highest-volume, lowest-risk work in any project.

2. 2

   Extract the work items

   From the same transcript, produce numbered requirements and actions with owners and dates, each linked back to the sentence that produced it.

3. 3

   Let it flag conflicts

   Ask the AI to compare new statements with earlier ones and surface contradictions and scope changes. Finding them is a machine task; resolving them is not.

4. 4

   Draft the plan, then correct it

   Generate phases, dependencies and a Gantt from the requirements, then adjust the estimates with what you know about the team.

5. 5

   Keep a human approval step

   Every generated item stays a proposal until a person accepts it, and the earlier version stays in the history.

Good to know

• AI is most accurate on extraction (what was said) and least accurate on prediction (what will happen).
• Traceability to the source sentence is what makes an AI-written requirement auditable.
• The EU AI Act forbids inferring emotions of people at work, so meeting AI must not score attitude or engagement.
• Segua.ai labels every generated document as AI output and keeps a revision history per item.

Related questions

Does AI replace my project tool?

No. It produces the content (requirements, decisions, plan) that your tracker then executes.

How much time does it actually save?

The saving is in writing and chasing: minutes, requirement lists, status documents and follow-ups, not in the decisions themselves.

What about confidential meetings?

Check that audio is not stored, that names are pseudonymised before any AI call and that each project is isolated from the others.

Other answers