What a Corporate AI Workshop Actually Covers (and What It Shouldn't)

Where most training goes wrong: the tool tour

The usual session shows one product after another. It creates excitement, but few people keep using AI, because the hard part was never the screen. It is choosing which task to hand over, briefing AI for usable output, and checking it before a customer sees it.

Those three skills work with every tool and still apply after the next model comes out.

The agenda that works

1. 01Where AI pays off here, and where it doesn't. Thirty minutes comparing the team's own workflows with what generative AI does reliably well. The result is a shortlist, plus a clear list of what not to automate.
2. 02Briefing. The core skill. A thin prompt gets a bland answer. Add your positioning, the audience, the objection you are handling and two examples of your house style, and you get something usable. This is prompt engineering taught as a business skill.
3. 03Live work, in the room. People bring a live brief, account plan or reporting task and finish it. This takes most of the day and shows which work is not worth automating.
4. 04Checking. What the model is likely to get wrong, which claims need a source, and who approves output before a customer sees it.
5. 05Writing down the workflow. Each person leaves with a written, reusable workflow for the task they finished. Without it, the day is forgotten within two weeks.

What a good agenda leaves out

How to tell whether it worked

Attendance and feedback scores are easy to hit and say little about lasting use. Agree in advance which workflows should change, then check at sixty days what changed and what blocked the rest. That review should be in the price.

Background on the technology discussed here: generative AI and large language models.