Use Case Discovery Workshop

# Champions

# Driving Adoption

Learn how to run a team brainstorm to identify AI use cases

September 17, 2025 · Last updated on April 20, 2026

Use Case Discovery Workshop Playbook

A Use Case Discovery Workshop is a live, role-aligned session where teammates with similar goals reflect on current workflows, surface pain points, and identify where AI could create visible, repeatable value.

The workshop creates protected time to map day-to-day work, identify recurring friction, and decide which AI opportunities are worth testing first. Participants do not need to be active ChatGPT users already. The goal is not to generate the longest list of ideas or build a complete solution in the room. The goal is to identify a short list of workflows that are valuable enough to matter, practical enough to test, and clear enough to assign owners and next steps.

This session works well quarterly, as part of a larger team offsite, or any time a team needs to move from scattered AI experimentation to a more structured set of priority use cases.

Workshop objectives

Align on common pain points as a team

Map day-to-day departmental workflows and identify recurring inefficiencies, bottlenecks, manual steps, repeated handoffs, or places where work depends too heavily on individual memory or judgment.

Identify AI opportunities tied to real workflows

Spot where AI could improve an existing workflow by reducing manual effort, improving clarity, increasing consistency, accelerating drafting or synthesis, supporting better review, or making an output easier to reuse.

Prioritize what is worth testing first

Evaluate discovered ideas using a shared lens: impact / value, complexity / effort, frequency, and readiness. This helps the team distinguish quick wins from more complex ideas that may need more support before they are ready.

Leave with owners and next steps

Select one to three priority use cases to explore or pilot, assign owners, and define the first milestone for the next two to four weeks.

How to prepare

Define scope and participants

Select the department, function, or role group for the session. The best discovery workshops are specific enough that participants share similar workflows, goals, or pain points.

Identify one to three ChatGPT power users, Champions, or high adopters to serve as table leads or co-facilitators. Their role is to share examples, help participants get concrete, unblock discovery, and support follow-up after the session.

Choose the right scope

Keep the session focused on workflows the team actually performs. Avoid framing the workshop around broad AI capabilities or abstract themes like “how can we use AI?” Instead, frame it around real work:

What recurring work takes the most time?

What outputs are created repeatedly?

What work is inconsistent across people or teams?

What handoffs create friction?

What tasks are important but hard to complete reliably?

Share pre-work

Ask participants to reflect on tasks or workflows they repeat often, find time-consuming, or believe could be more consistent. Encourage them to bring real examples, such as notes, drafts, reports, templates, customer communications, internal updates, SOPs, or review checklists.

Suggested categories:

Research and summarization

Drafting and editing

Data analysis or reporting

Knowledge search and SOP retrieval

Meeting prep and follow-ups

Customer or internal communications

Planning and project management

QA, review, or checklists

Handoffs between teams or systems

Ask participants to come prepared with at least one repeated task and one pain point.

Use ChatGPT to create a message to participants

Set up the workspace

Reserve space, either in person or virtual, and choose a workshop workspace such as a virtual whiteboard, shared doc, or physical wall with sticky notes.

Pre-create columns or swimlanes that guide participants from raw ideas to prioritized next steps:

Workflow → Pain point → Frequency → Impact / value → Complexity / effort → Readiness → AI opportunity → Owner / next step

You can also color-code by team, priority, or readiness stage.

Assign facilitator roles

Assign a facilitator, note-taker, and timekeeper.

If you have table leads, ask them to help participants move from vague ideas to concrete workflows. For example, “AI for reporting” should become “drafting the weekly leadership update from team notes and project updates.”

Sample agenda: 90 minutes

Time	Activity	Description
0:00–0:10	Welcome and framing	Introduce objectives, agenda, and ground rules. Reinforce that the goal is to identify useful workflows, not replace people or solve everything in one session.
0:10–0:20	Shared prioritization lens	Explain the evaluation criteria: impact / value, complexity / effort, frequency, and readiness. Emphasize that the best starting points are both valuable and winnable.
0:20–0:35	Workflow discovery	Participants identify recurring workflows, pain points, handoffs, and outputs. Push for specificity: who does the work, how often, what input starts it, and what output is needed.
0:35–0:55	Use case discovery	Small groups map workflows to potential AI opportunities. Facilitators prompt participants to describe where AI could help: drafting, summarizing, structuring, reviewing, comparing, synthesizing, or creating a reusable output.
0:55–1:10	Prioritization	Groups evaluate candidate use cases using the shared lens. Identify likely quick wins, strategic initiatives, nice-to-haves, and ideas to avoid for now.
1:10–1:20	Optional live test	Try one or two high-potential workflows with real inputs. Capture what changed, what worked, and what still needs clarification.
1:20–1:27	Commitments and owners	Select one to three priority use cases. Assign owners, define the first milestone, and agree on what repeatable use should look like.
1:27–1:30	Close	Recap decisions, next steps, and follow-up timing. Reinforce that the goal is to turn the strongest workflows into tested, reusable use cases.

Facilitation guide

Start with a shared frame

Use this framing at the beginning of the session:

“Today is not about finding every possible way to use AI. It’s about identifying the workflows where AI has the best chance to create visible value without overwhelming the team. We’ll look for use cases that happen often, matter to the business, have clear inputs and outputs, and are realistic to test.”

Push participants from tasks to workflows

A repeated task can be a useful starting point, but it may not show the full workflow. Ask participants to zoom out enough to understand what happens before and after the task.

Useful prompts:

Who performs this task?

Who depends on the output?

What happens immediately before this task?

What happens immediately after?

What tools or systems are involved?

Where does information change hands?

Where do people manually clean up, rewrite, check, or clarify the work?

Where does the process break down or slow down?

What does “good” look like for the final output?

This helps the team avoid underestimating complexity or choosing a use case that looks simple but depends on hidden handoffs, unclear inputs, or unresolved ownership.

Use a prioritization lens

After discovery, evaluate each candidate use case using four criteria.

Impact / Value How much would this improve outcomes that matter? Would it save time, improve quality, increase consistency, reduce friction, improve customer experience, or make important work happen more reliably?

Complexity / Effort How much coordination, process change, governance, clarification, or support would be required to make this workflow reliable?

Frequency How often does the workflow happen? Frequent workflows create more opportunities for habit formation, repeated value, and visible momentum.

Readiness Are the inputs, outputs, owners, and success criteria clear enough to test? Or does the team need more discovery before AI can help reliably?

Categorize the ideas

Use these four categories to help the team make tradeoffs:

Quick Wins: High impact / low effort Start here. These workflows create fast proof, build trust, and generate internal pull.

Strategic Initiatives: High impact / high effort Capture and plan for these later. They may matter a lot, but they likely need sponsorship, operating rhythm, governance, integrations, or cross-functional support.

Nice-to-Haves: Low impact / low effort These can be useful, but they should not anchor the team’s adoption plan.

Thankless Tasks: Low impact / high effort Avoid these. They consume energy without creating meaningful credibility or momentum.

Force tradeoffs

A good workshop does not end with twenty exciting ideas. It ends with one to three clear priorities and a few ideas to revisit later.

Ask:

Which use case is most likely to create visible value quickly?

Which workflow happens often enough for the value to compound?

Which idea has the clearest inputs and outputs?

Which idea requires the least coordination to test?

Which idea sounds valuable but is not ready yet?

Which idea would need leadership, governance, or systems support before it can move forward?

Minimum details to capture

For each promising use case, capture:

Workflow or step improved

Role or team using it

Pain point

Impact / value

Complexity / effort

Frequency

Readiness

Owner

Reusable assets needed

First milestone

Outcomes and follow-ups

A strong discovery workshop should produce a concise recap that clearly separates ideas from decisions.

Include:

The top workflows discussed

The strongest pain points or bottlenecks identified

The one to three use cases selected for follow-up

Why those use cases were prioritized

Ideas captured for later

Owners and timelines

First milestone for each selected use case

What success or repeatable use should look like

Select one to three high-potential use cases to pilot within the next two to four weeks. Start with workflows that are high-frequency, low-friction, and easy to show before-and-after value.

Instrument success from day one. Depending on the workflow, useful signals might include:

Time saved

Steps reduced

Revision cycles reduced

Output quality improved

Consistency increased

Reuse across teammates

Fewer dropped handoffs

More reliable completion of a recurring output

Convert wins into reusable assets such as prompt packs, team GPTs, how-to guides, workflow templates, or documented SOPs.

Upload an image of the discovery workshop session to ChatGPT and document action items.

Thoughtful follow-up turns discovery into real outcomes. The goal is to move from raw ideas to validated workflows, and from validated workflows to reusable assets that build confidence and momentum across the team.

Tips for success

Keep it grounded

Encourage creativity, but keep ideas tied to real workflows and realistic starting points. You can always add complexity, automation, integrations, or governance later. Early momentum comes from use cases that are valuable and winnable.

Do not confuse interesting ideas with good starting points

Some ideas will sound impressive but require too much coordination, unclear ownership, new integrations, or policy review to test quickly. Capture them as strategic initiatives, but do not let them crowd out simpler workflows that can create proof now.

Test all tools before the session

Prepare backup methods such as physical sticky notes or a shared doc in case people have trouble accessing ChatGPT, virtual boards, or shared files. Avoid losing momentum to tech checks.

Bring real work into the room

The best discovery workshops use actual examples. Encourage participants to bring drafts, notes, reports, templates, messages, SOPs, or recurring outputs they already work with.

Include every voice

Make sure the loudest voices are not the only ones shaping the priority list. Use silent brainstorming, virtual whiteboards, or small-group discussion to create space for quieter participants. Facilitators should ask probing questions that encourage participation and specificity.

Assign owners before closing

Every selected use case needs an owner, a first milestone in the next two to four weeks, and a definition of what repeatable use should look like. Without ownership, workshops often create energy but not progress.

Useful facilitator prompts

Use these prompts to help participants get specific:

“What is one task you repeat often?”

“What is one workflow that takes longer than it should?”

“What output do you create again and again?”

“What work depends on someone remembering what ‘good’ looks like?”

“What is one task you wish you did less manually?”

“Walk me from trigger to finished output. Where does it slow down?”

“Who touches this work before and after you?”

“Where do handoffs, reviews, or clarification loops happen?”

“What inputs are already available?”

“What would a useful first draft or first pass look like?”

“How could we make this smaller or safer to test in a week?”

“What would need to be true for someone else to repeat this workflow?”

“Is this a quick win, or does it need more support before we start?”

Suggested participant pre-work message

Hi team,

We’ll be running a Use Case Discovery Workshop to identify where AI could help improve real workflows across our team. The goal is not to come up with every possible AI idea or build a complete solution in the session. The goal is to identify a short list of workflows that are worth testing because they happen often, create meaningful friction, and have clear potential value.

Before the session, please bring one to two examples of recurring work you do today. These could be tasks that are time-consuming, repetitive, inconsistent, manual, or difficult to complete reliably.

For each example, jot down:

What the workflow or task is

How often it happens

What makes it slow, difficult, or inconsistent

What input starts the work

What output needs to be created

Who uses or depends on the output

Examples might include drafting updates, summarizing notes, preparing reports, reviewing materials, finding information, creating customer communications, or managing follow-ups.

We’ll use these examples to identify which use cases are most valuable, practical, and ready to test.

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Use Case Discovery Workshop

Learn how to run a team brainstorm to identify AI use cases

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