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AI Team Accelerator.

From shared team work to a concrete AI approach.

A practical team track in which colleagues apply AI to shared tasks and develop reusable ways of working together. When one application deserves further development, the track can be extended with a Build Lab in which a smaller team builds and tests the use case themselves with live coaching.

  • 1 team session
  • Optional Build Lab
  • Maximum 12 participants
Plan an intake → See both formats

Why this Team Accelerator

Everyone experiments. Nobody builds further.

In many teams, people each use AI in their own way. They write one-off prompts, individually find useful applications and sometimes get good results, but valuable knowledge is barely shared. What works for one colleague doesn't yet become an approach the whole team can build on.

The AI Team Accelerator brings colleagues together around the work they share. The team tries out relevant applications, compares results and develops practical AI ways of working that several colleagues can use and improve.

Scattered experiments shared AI ways of working optionally build one application

The structure

Two formats, one logical track.

The Team Accelerator always starts by applying AI to the team's shared work. Only when a promising use case emerges that deserves further development does an optional Build Lab follow.

  1. Explore team work
  2. Apply AI
  3. Develop ways of working
  4. Promising use case
  1. Build Lab
  2. Build it yourself
  3. Test
  4. Decide

Fixed team session

Applying AI to the work you share.

Colleagues work in the available AI tool with recognizable tasks, documents and processes from their daily work. They try different approaches, compare the results and jointly develop reusable prompts, templates and AI ways of working.

  1. 01

    Exploring shared work

    We map the team's recurring tasks, materials and work processes.

  2. 02

    Choosing relevant applications

    We select several applications that are recognizable and usable for different colleagues.

  3. 03

    Trying things out together

    Participants apply AI to real tasks and compare different ways of working.

  4. 04

    Assessing the output

    The team jointly determines what usable, reliable and responsible results have to meet.

  5. 05

    Developing ways of working

    Good approaches are turned into reusable prompts, templates, instructions and clear steps.

  6. 06

    Setting priorities

    The team establishes which ways of working are immediately usable and which application may deserve further development.

Result of session 1

  • Shared AI ways of working
  • Reusable prompts and templates
  • Joint quality and safety criteria
  • Concrete agreements on use and further improvement
  • A view of applications that deserve further development

Optional build session

Build one promising use case yourself with live coaching.

When one application is relevant and well-defined enough, a smaller build team takes it forward. Participants translate the use case into a first working solution, test it with representative examples and improve the result under live guidance.

  1. 01

    Scoping the use case

    We make the user, task, input, desired output and scope concrete.

  2. 02

    Defining success criteria

    The build team establishes up front what a usable result has to meet.

  3. 03

    Designing the way of working

    We determine which steps AI performs and where human oversight remains necessary.

  4. 04

    Building it yourself with live coaching

    Participants get the core of the application working in a suitable and permitted AI or prototyping tool.

  5. 05

    Testing and improving

    The team uses representative cases to surface errors, exceptions and points for improvement.

  6. 06

    Deciding on the follow-up

    We determine whether the application should be used further, adjusted, investigated, developed further or deliberately stopped.

Result of the optional session

  • One well-defined use case
  • A testable first solution or prototype
  • Established success and quality criteria
  • Test findings and points for improvement
  • Insight into risks, exceptions and preconditions
  • A well-founded next step

A prototype is not yet a production-ready, integrated or formally approved implementation. The value lies in making the key assumptions tangible and testing them.

The outcome

First an approach for the team. Optionally a working first solution.

After the fixed team session the team has tested AI ways of working for shared work, reusable prompts and templates, and joint criteria for quality and responsible use. It is also clear which applications are immediately usable and where further development can add value.

When the track is extended with a Build Lab, a smaller build team develops one selected use case into a testable first solution. The findings provide the evidence needed to decide on the follow-up with confidence.

After session 1

  • Shared AI ways of working
  • Reusable prompts and templates
  • Joint quality criteria
  • Agreements on use and improvement
  • Priorities for further application

After the optional Build Lab session

  • One well-defined use case
  • A testable first solution
  • Test findings from practice
  • Insight into risks and preconditions
  • A well-founded follow-up decision

Practical

Who it's for
One existing team whose colleagues share comparable tasks, processes or responsibilities.
Format
One practical team session · optionally extended with a separate Build Lab session. We tune the exact duration during the intake to the team, the selected activities and any prototype scope.
Participants
Session 1: maximum 12 participants. For the optional Build Lab we assemble a smaller build team with relevant users, subject-matter experts and, where needed, technical or organizational stakeholders.
Preparation
A focused intake covering the shared work, the available AI tools, relevant materials and possible applications. For a Build Lab we additionally scope one use case, the test criteria and the required access.
What participants need
Their own laptop and secure access to the AI tools, documents or test materials used during the workshop.
Possible tools
ChatGPT · Claude · Microsoft Copilot · Gemini · available and permitted prototyping tools
Location
In-company or at Rollo · in person, online or hybrid depending on the chosen set-up

Ready to make AI concrete for your team?

Start with the work you share.

In a focused intake we map the team's tasks, processes and AI experience. On that basis we build the first session around recognizable applications and determine whether an optional Build Lab is relevant.

Plan an intake → See all workshops