A claimable invoice and a full room are not the same thing as a more capable team. Most AI training delivers the first two and quietly skips the third.
HRDC funding has made AI training easy to approve and easy to waste. Too many programmes are a day of slides, a certificate, and no measurable change in how anyone works the following week. The funding is real, so the bar should be higher.
Why most AI training fails
The usual programme teaches concepts in the abstract. People leave able to define a large language model but unable to use one on their own work. Within days the momentum is gone. Knowledge that is never applied decays fast.
What effective training looks like
The programmes that change behaviour share a few traits. They are built around the participant's real tasks, not generic examples. People bring their own work into the room and leave having already automated part of it.
- Hands on from the first hour, using the team's actual tools and data.
- Role specific tracks, because finance and marketing need different things.
- A concrete deliverable per participant, not just a certificate.
- A follow up checkpoint weeks later to lock in the habit.
"If your team cannot point to something they now do faster, the training did not work, no matter how good the slides were."
Measure the outcome, not the attendance
Track the things that prove value: hours saved per week, tasks now handled with AI assistance, and the number of people still using what they learned a month later. Those numbers turn a claimable expense into a genuine capability, and they make the next round of investment easy to justify.
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