A workshop should produce decisions, not enthusiasm
The failure mode of an AI workshop is easy to spot. Everyone leaves inspired, but three weeks later no workflow was chosen, no owner was named, and the company has a more expensive version of the confusion it started with.
A useful session is judged by what survives the meeting: a ranked workflow inventory, a risk model for the top candidate, and a first prototype scope with an owner and success metric attached. Everything in the agenda should bend toward those artifacts.
Exercise 1: build shared vocabulary
Mixed rooms stall because agent, workflow, eval, retrieval, and tool use mean different things to different people. Spend the first block getting everyone to the same definitions. The goal is not AI education for its own sake. It is so the prioritization discussion does not dissolve into people talking past each other.
The useful distinction is simple: a single model call answers or drafts; a workflow follows a predefined path; an agent can decide steps and tool use dynamically. That vocabulary changes how leaders judge risk and complexity.
Exercise 2: inventory the work
Ask each team to list repeated work, not departments. Do not write customer support. Write triaging inbound tickets and drafting first responses. Do not write finance operations. Write matching invoices to purchase orders and routing exceptions.
For each candidate, capture volume, systems touched, owner, rough human time per instance, common exceptions, and whether the output has a clear quality bar. Specificity is what makes prioritization possible. The inventory is only as good as who is in the room. Without the people who actually own the work, and someone who knows the underlying data and systems, the list and the later risk map are guesses dressed up as a plan.
Exercise 3: score and rank
Score each candidate 1 to 5 on value, feasibility, safety, and provability. Value is volume times time per instance. Feasibility is whether the systems and data are bounded. Safety is whether failures are reversible and reviewable. Provability is whether success can be measured without a meeting.
Do this in the room, out loud. Score value and feasibility 1 to 5, but treat safety and provability as gates rather than points: a workflow whose failures are not reversible and reviewable, or whose success cannot be measured without a meeting, is out no matter how much value it carries. Rank what survives by value times feasibility. The winner is often not the workflow leadership expected, and watching the scores fall out changes minds faster than a slide deck.
- Value: how many hours or dollars are actually at stake.
- Feasibility: how bounded the systems, data, and actions are.
- Safety gate: are the failure modes reversible and reviewable?
- Provability gate: can the team define pass/fail outcomes without a meeting?
Exercise 4: map risk on the top candidate
Once the top workflow is chosen, answer the operational questions while the room is together. Where do humans review? Which actions can the agent take alone? Which require approval? What data is sensitive? What has to be logged? What happens if the agent is wrong?
This is where workshops become real. Executive adoption fails when permissions, data boundaries, review requirements, and accountability stay vague.
Exercise 5: scope the prototype and the 90 days
End on commitment. Define the narrowest version of the workflow worth testing, name the owner, name the success metric, and write the first test cases. Keep the prototype honest by constraining it: one workflow, one or two record or request types, and proposal-only output that a human approves before any action is taken. Widening the scope is a later decision, not a starting condition. Then sketch the first 30, 60, and 90 days: prototype, evals, hardening, supervised rollout.
If a single workflow is already chosen, skip the workshop and start implementation. If the goal is general awareness with no workflow decision, that is training. A workshop is for the messy middle: leadership agrees AI matters but needs a method for choosing where to start.