Training your team for AI without a training budget

Businesses assume AI adoption needs technical training. In practice, the skill that separates teams who get value from teams who get burned is critical evaluation: the habit of asking whether an output is actually right.

Three sessions that cover most of it

• Session one — what these tools are and are not. Focus on confident wrongness, not the technology.
• Session two — safe use. What data can never be pasted in, what must be checked, who to tell when something looks off.
• Session three — applied practice on your own real tasks, with someone experienced reviewing the outputs alongside them.

Each session is an hour. Run them with the people who do the work, not with managers describing the work.

Make champions, not mandates

Pick one person per team who is genuinely curious and give them protected time — an hour a week is enough. Adoption spreads sideways through peers far faster than it flows down through policy.

If nobody in the business is allowed to spend an hour a week experimenting, you do not have an AI strategy — you have an AI subscription.

Measure confidence, not attendance

Ask staff quarterly how confident they are spotting an incorrect AI output. Rising confidence, backed by fewer escalations, is the signal that training worked.