Curriculum

What current AI tools can and can't do

Where they hold up: drafting, summarizing, pulling facts out of documents, rewriting for a different reader. Where they fail: making things up, getting figures wrong, sounding sure when they are wrong. You learn how to check output before anyone relies on it.

Live demonstrations on realistic business material

We run the tools on the kind of material an office handles every week: a bid or proposal, a long email thread, a policy document, a messy spreadsheet. You see the real output, mistakes included.

Building your data map

You sort what your business handles into cloud-safe, keep local and undecided. Customer records, contracts, financials, staff files, and anything under a regulation or client agreement each get a column and a reason. We also go through how to read what a tool's terms say about your data.

You leave with: Your data map. It decides what you build with on day two.

Building three workflows on your own work

Pick three recurring tasks from your business and build an AI workflow for each, using only material your data map allows. Each one is tested on a real example before the session ends.

You leave with: Three working workflows.

Writing your staff AI use policy

One page your staff will read: approved tools, data that never goes in, when output gets checked, and who answers questions. It comes from your data map, so it fits your business.

You leave with: A one-page AI use policy.

Building your 30-day rollout plan

Each workflow gets a named owner, a start date and a check-in. The plan is sized for a company that still has its day job.

You leave with: A 30-day plan with an owner for every workflow.