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AI Workshops
A workshop should change
how people work the next day.
We run practical AI workshops built around your team, your workflows, and the decisions you actually need to make.
Plan a workshop
A working session: the team maps its own work, and each person leaves with one task to do differently on Monday. The problem
Most AI workshops fail for one reason: they are interesting, but not useful.
People leave knowing more about AI, and still do their job exactly the same way on Monday. We focus on application.
Interesting
- Transformers → attention?
- 17 tools to try
- Agents = the future
- Cool demo!!
- Ask IT about access…
Useful on Monday morning
Monday, 9:00
- Run intake emails through the triage prompt
- Check each draft against the policy source
- Send anything over the limit to the team lead
- Note what the prompt got wrong
What participants do
Hands on the work,
not on slides.
Every exercise uses the team’s own tasks.
First
Look at the work
- Map repetitive work
- Test AI against real tasks
Then
Change it
- Redesign a workflow
- Identify useful vs risky use cases
- Build reusable prompts
- Score opportunities
Before you leave
Decide
- Define human / AI boundaries
- Leave with next actions
Custom to your business
We do not teach from a generic deck and swap your logo onto it.
AI 101 · slide 1 of 64
The Future
of Work
Your logo Before the session, we learn
- Who is in the room
- What work they do
- What tools they already use
- What leadership wants to achieve
- What is off-limits
- Where the real friction is
That becomes the workshop.
Workshop output
Prioritized AI use cases
- 1 · Intake triage · start here
- 2 · Draft replies from approved sources
- 3 · Month-end summary · later
Workshop output
Workflow maps
- Request
- Check
- Draft
- Approve
Workshop output
Team prompt library
- Summarize this request for the owner. Quote the source.
- List what is missing before this can move on.
- Draft a reply using only the attached policy.
Workshop output
Risk / governance questions
- Which data can this tool see?
- Who approves anything sent to a customer?
- What happens when the answer is wrong?
Workshop output
Pilot recommendations
- One queue, one team, four weeks
- A person approves every send
- Measure time per request and error rate
Workshop output
Action plan
- Set up the triage prompt · team lead
- Collect ten real examples · each person
- Review what went wrong · Friday
Workshop output
Executive summary
- Where AI helps this team now
- What needs a decision from leadership
- What we recommend testing first