Give the workshop a specific job
An AI workshop is useful when your team leaves able to tackle a real task more effectively. A series of impressive demonstrations does not establish which application fits your information, approval process or available capacity. Agree an outcome beforehand, such as defining a reviewed workflow for the monthly customer newsletter.
A specific assignment gives the session a workable boundary. Participants can examine actual inputs, handovers and decisions rather than discussing every possible use of AI. For an initial workshop, we recommend one connected process. Other ideas can be recorded for later without displacing the agreed objective.
Bring working material and decision-makers
Ask participants for typical task descriptions, approved examples and the corrections they repeatedly make. Use suitable sample information in exercises when the original contains confidential data. Include someone who performs the work and someone who can make decisions about ownership and approval.
A rough baseline is also valuable. Record how the current task is completed and where time goes. This does not require a large measurement project. A clear starting point helps reveal whether a proposed process saves work or simply transfers effort to another colleague. List the tools already in use and any access needed for a pilot.
Expect four tangible outputs
A productive session should leave you with prioritised use cases, a reproducible working example, written quality criteria and a pilot plan with a named owner. For a newsletter, the example could include a brief, a draft, a review checklist and an approval step.
Write the quality criteria explicitly. Are factual statements supported? Does the language fit the brand? Can the intended reader understand the message? Is the next step clear? A repeatable way of assessing output is more valuable than agreeing that a single demonstration “looks pretty good”. The team should also know which defects require revision and which require expert input.
Example: Turning an interview into a newsletter
In an illustrative exercise, a company supplies an approved interview with a subject specialist. Participants first identify the customer questions it answers. They then develop an outline and a draft. A second person checks substantive statements against the original material and flags additions that need evidence.
Anthropic describes fixed sequences of tasks as one way to build AI workflows. That provides a technical foundation for this kind of bounded exercise, without making the workshop dependent on a particular software interface. Workflow background
Make the pilot easy to assess
Choose a review period, representative tasks and a joint evaluation. Define acceptable output and who handles problems. Compare the complete process, including preparation and corrections. If generation becomes faster but approval becomes slower, the evaluation should show that clearly.
NIST offers a general framework for managing AI risks. A practical question for workshop follow-up is therefore who will continue to observe quality and effects once the training is over. Attendance at a session does not itself establish that ownership. NIST framework
Leave with a next step
Everyone should know what happens next, where the working materials live and when results will be reviewed. Turn unresolved technical questions into explicit tasks. If a system integration is necessary, describe it separately so that its effort and dependencies are visible.
Our AI workshops combine practical exercises with a defined route into everyday work. If the initial use case is still unclear, AI consulting helps select it. The choice of tools follows the agreed business task.
