Training your teams on AI: the first 30 days

The standard corporate answer to AI is a training day: slides, a demo of a chatbot, a quiz. Three months later, nothing has changed in how anyone works. The problem is not the trainers — it is the theory-first format. People adopt tools they use on their own work, not tools they saw on a screen. Here is the 30-day sequence we see actually stick.

Days 1–10: acculturation, by profile

Not everyone needs the same knowledge. Executives need to understand what agents change in the cost structure and where the risks sit. Managers need to learn how to specify a task precisely enough for an agent to take it. Operational teams need hands-on practice with the tools that touch their daily work. One generic session for everyone serves no one — run three short, targeted ones instead.

Days 11–30: learn by working with a real agent

The turning point is the day a team works alongside an agent on its own tasks — validating its email drafts, correcting its classifications, adjusting its rules. Within two weeks, the questions change from « will it replace us? » to « can it also handle this? ». That shift is adoption, and no slide deck produces it. Pick one process, put one supervised agent on it, and make the team its trainer.

• →Week 3: the team reviews everything the agent produces, and logs each correction — corrections are the curriculum.
• →Week 4: validation narrows to exceptions only, and the team writes the rules for the next process to automate.
• →Structured courses and workshops still have a role — we run them ourselves — but as accelerators alongside real work, never as a substitute for it.

If you plan a training budget this year, invert the usual ratio: spend one part on formal sessions and three parts on supervised practice with a real agent on a real process. The certificate is optional; the changed daily habit is the deliverable.