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AI Team Skills Map

AI Team Skills Map is a kickoff exercise in which a project team holds a guided conversation with an AI chat assistant that asks about the project, each member's skills and how the work could be divided, and ends with a table of names, skills and possible tasks. It is based on the team structure prompt in the 'AI as teammate' section of Ethan and Lilach Mollick's 2023 paper 'Assigning AI: Seven Approaches for Students, with Prompts'. The assistant structures the conversation; the team supplies the knowledge about its members and decides the allocation.

Duration
20m–40m
Group size
3–8 people
Materials
An AI chat assistant, A prepared role prompt, Shared screen…

Facilitation script

  1. 1

    Explain the purpose and the ground rule: the assistant asks the questions, the team provides the answers and makes the decisions. Enter the role prompt.

    3 min
  2. 2

    Describe the project to the assistant: goal, deliverables, deadline, constraints.

    5 min
  3. 3

    Go round the team. Each person states their own skills, experience and interests, and one person types them in.

    8 min
  4. 4

    Discuss how tasks could be organised. Ask the assistant for a suggested allocation and for gaps it sees.

    6 min
  5. 5

    Generate the table of names, skills and possible tasks. Review it line by line, correct it and check each person agrees with their row.

    6 min
  6. 6

    Save the table, note open gaps and agree when the allocation will be revisited.

    2 min

Tips

  • The main benefit is the conversation in step three, when team members find out what their colleagues can do, so give it time and let people speak for themselves.

  • Ask for interests and things people want to learn as well as existing skills, otherwise the table assigns everyone the work they have always done.

  • Treat the assistant's allocation as a draft; it knows nothing about workload, availability or who works well together.

  • Use first names or roles only and leave out anything that reads like a performance judgement.

Common pitfalls

  • Accepting the assistant's allocation as it comes. Tasks end up with people who lack the time or the interest, because the model knows neither

  • One person describing everyone else's skills. The table repeats existing assumptions and the team learns nothing about each other

  • Listing only formal qualifications. Useful experience and things people want to learn stay hidden, and the same people get the same work as always

  • Entering sensitive personal details or performance assessments into the tool, which damages trust and may breach policy

  • Never looking at the table again. Allocations made at kickoff stop fitting once the project changes

Variations

For remote teams, one person shares the chat on screen while the others answer by voice. To give quieter members more room, everyone writes their own skills and interests on notes before the chat and reads them out when their turn comes. In larger programmes, each sub-team runs its own map and the tables are compared to find skills that are missing everywhere. The name AI Team Skills Map is a descriptive label; the paper calls the exercise the team structure prompt, presents it for student teams and gives no timing or group size.

Where it fits

Project kickoffTask allocation by strengthsNew teams learning each other's expertiseSpotting skill gaps before work startsStudent or cross-functional project teams

When to use it

  • A newly formed project team is about to divide the work and members do not know each other's backgrounds

  • Tasks tend to be assigned by job title or by who speaks first

  • A cross-functional or temporary team has no manager to do the allocation for it

  • The project has a clear scope and deliverables, so tasks can be named

  • You want a quick first draft of who does what as input to a fuller kickoff

When not to use it

  • Roles are contested or there is a conflict about who decides. Use a facilitated Roles and Responsibilities session or a RACI Matrix

  • The project scope is still unclear. The assistant can only match skills to tasks that have been named

  • The team has worked together for years and knows each other's strengths. A direct planning conversation is faster

  • Sharing personal skill profiles with an AI tool conflicts with company policy or with what team members are comfortable with. Use a paper-based Personal Strengths Matrix

  • The aim is individual development planning, which belongs in a coaching conversation

Related methods

Frequently asked questions

What is AI Team Skills Map?▾

AI Team Skills Map is a short kickoff exercise in which an AI chat assistant guides a team through questions about its project, its members' skills and how to divide the tasks. The result is a table listing each person, their skills and possible tasks. The team checks and corrects the table before using it.

Where does the method come from?▾

It is based on the team structure prompt in the 'AI as teammate' section of 'Assigning AI: Seven Approaches for Students, with Prompts' by Ethan Mollick and Lilach Mollick (2023). The paper presents it for student project teams. The name AI Team Skills Map and the timings given here are not from the paper.

Why use an AI assistant for this at all?▾

The assistant acts as a patient interviewer that asks every member the same questions and keeps the answers in one place. That gives structure to a conversation teams often skip. It does not know the people, so its suggestions on who should do what are only a starting point.

How long does it take?▾

Plan 20 to 40 minutes for a team of three to eight. Most of the time goes into the round in which members describe their skills. The source gives no timing, so this is an estimate from practice.

What should we keep out of the chat?▾

Leave out personal data beyond first names or roles, anything confidential about the project that your AI tool is not approved for, and any judgement of colleagues' performance. Describe skills and interests in the words people use about themselves. If in doubt, run the conversation without the tool and build the table by hand.

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Method descriptions on Workshop Weaver are original content written by our team, based on established facilitation practices. This method was inspired by work from Ethan Mollick and Lilach Mollick, 'Assigning AI: Seven Approaches for Students, with Prompts' (2023).