The problem
A consulting firm's partners were spending significant time preparing for client meetings — researching the client's recent activity, reviewing previous meeting notes, compiling relevant project updates and preparing briefing materials. Each meeting required thirty to sixty minutes of preparation. With multiple meetings per day, the preparation time consumed hours that could have been spent on client work or business development.
The preparation was valuable — meetings were more productive when the partner arrived informed. But the process of gathering and structuring the information was mechanical work that did not require partner-level judgement.
What we built
We built an AI meeting preparation assistant that compiled briefing documents automatically. Before each meeting, the assistant:
- Gathered the client's recent activity from the CRM, project management tools and communication history
- Summarised the previous meeting's notes and outstanding action items
- Compiled relevant project updates from the consulting teams
- Surfaces any relevant news or developments about the client's business
- Produced a structured briefing document in the partner's preferred format
The partner reviewed the briefing document — usually taking five to ten minutes — rather than spending thirty to sixty minutes compiling it.
The results
Two months after deployment:
- Meeting preparation time reduced from thirty to sixty minutes to five to ten minutes per meeting
- Preparation quality improved because the assistant gathered information more comprehensively than manual preparation had allowed time for
- Meeting outcomes improved because participants arrived with better context
- Partners reclaimed several hours per week for client work and business development
How it worked
The assistant connected to the systems where client information lived — CRM, project management, email archives, document repositories. It knew what to gather for each client and each meeting type. It produced the briefing in a consistent format that the partners found immediately useful.
The assistant did not replace the partner's judgement about what mattered. It handled the gathering and structuring so the partner could focus on the thinking and the preparation that required their experience and insight.
What we learned
The most important lesson was that the assistant's value was not just in saving time. It was in improving preparation quality. When partners had thirty minutes to prepare, they gathered what they could in the time available. When the assistant gathered everything and the partner had ten minutes to review, the preparation was more comprehensive because the assistant had done the time-consuming gathering work.
We also learned that meeting preparation is an ideal automation candidate because the inputs are well-defined — which client, which meeting type, what format — and the value of better preparation is immediately visible in the meeting itself.
For a broader look at how AI supports executive workflows, see AI executive assistant. For a related case study on briefing preparation, see AI assistant for executive briefings.
This case study describes a composite of real implementations. Results vary based on the specific process, team and context.