Use Case Showcase Playbook
A use case showcase is a team-focused session where employees share how they apply AI in their own work.
Instead of presenting broad AI capabilities, contributors walk through a specific workflow, show what changed, and explain what others can learn or try.
The goal is to make tested workflows visible, credible, and easier for others to learn from and repeat.
This playbook is primarily for Activators organizing the session. Leaders can support by connecting the showcase to team priorities, creating visibility, and helping remove barriers when teams want to test a featured workflow.
Showcase Objectives
A strong showcase should:
- Make AI value visible through examples that show how real work changed.
- Support peer learning by featuring workflows from trusted colleagues and relevant roles.
- Encourage continued adoption by giving the audience clear resources and next steps.
How to Prepare
Choose the Format and Audience
Decide whether the showcase will be a live session, a segment within an existing meeting cadence, a company-wide event, or a recorded demo. A focused team or role-based showcase may be more relevant than a broad company-wide session.
Select Two or Three Use Cases
Choose examples that:
- Address a recognizable work problem
- Have been tested and successful in real work
- Show a credible improvement
- Can be explained clearly in a few minutes
- Include a practical next step for the audience
Recruit and Prepare Presenters
Invite Activators or other users who can explain:
- What the work looked like before
- Where AI fits into the process
- What evidence suggests the workflow is useful
- What they still review, edit, approve, or decide
- How another person could try the approach
Use a consistent presentation structure: Task → Before → AI-Supported Approach → After → Value → Human Review → How to Try It
Sample Agenda: 30 Minutes
| | |
|---|
| | Introduce the purpose, agenda, and what the audience should listen for. |
Showcase Two or Three Use Cases | | Contributors walk through concise examples using the shared structure. |
| | Clarify how the workflows work, where they may apply, and what limitations remain. |
Next Steps and Call to Action | | Share supporting resources and explain how participants can try or submit a use case. |
How to Run the Showcase
Open With the Purpose
Set expectations at the beginning:
Today’s goal is to learn from tested examples of AI in real work. As you listen, focus on the workflow, what changed, what evidence supports the result, and whether there is something your team could try or adapt.
Keep Demos Short and Consistent
Keep each presenter to the shared structure and agreed time. Avoid long product walkthroughs or detailed histories of every prompt iteration.
Build in Interaction
Use the discussion to help the audience understand:
- When the workflow is useful
- What inputs or access it requires
- What still requires human judgment
- Whether the workflow could be adapted for another role or team
You can also use a quick poll, chat question, or invitation for volunteers to test an example.
After the Showcase
Share a Short Recap
Send the audience:
- The workflows featured with short summaries of what each one helps with, and the clearest value signal
- Links to prompts, Skills, Workspace Agents, templates, guides, or recordings
- The owner or point of contact
- The next step for someone who wants to try the workflow
Do not share a prompt or recording without enough context to explain when to use it, what to provide, and what to review.
Capture Follow-Up Interest
Look for:
- Teams that want to test or adapt an example
- Questions about access, setup, or support
- Requests for role-specific adaptations
- Barriers that require support from a Leader, Workspace Admin, functional owner, or technical partner
- Employees with tested workflows, adaptations, or lessons to share in a future showcase
Provide one simple form or submission path for follow-up requests and future contributors.
Look beyond attendance when assessing whether the showcase was useful. Stronger signals include questions, resource use, requests to test an example, adaptations by another team, and future use-case submissions.
