Core question
Why does our AI training not stick?
Short answer
Because most training is built for the trainer. If a session ends with applause but no change in behavior, you hosted a performance. Training has to be built around practice with real tasks, not presentation. The goal is habits, not enthusiasm.
I have sat through sessions on using AI in business that were essentially a stage act. Slick slides, simple prompts producing instant responses, entertaining stories, and a speaker who clearly enjoyed the sound of his own voice. The topic was important. The delivery taught nobody anything they could use on Monday.
We take a different approach, and the difference starts with explaining how the tool actually works. When people understand that a language model is not comprehending their text but predicting the next word based on pattern, the entire conversation changes. It turns a flashy moment into a useful one, because now they know how to engage the tool rather than being impressed by it.
The rest is practice. Prompting, interpreting, applying, with hands on real work. Until your team gets their hands dirty, nothing sticks. Stop investing in inspiration and start investing in internal capability.
Measure it accordingly, and be careful about what you measure. Counting prompts or documents produced tells you almost nothing, because activity is not value. What is worth tracking during a training rollout is narrower: how often people reach for the tool relative to the occasions where it would have helped, whether it gets built into a workflow rather than used once and abandoned, and whether the people using it say it was worth their time. Those are adoption signals, and adoption is the precondition for any business result later. They are not the business result itself, and they should not be reported as one.