RetrospectiveAn AX Training Assistant’s Retrospective on Using AI After Training
I took part in corporate AX training as an assistant instructor, helping with hands-on exercises and answering questions. AX refers to bringing AI into the workplace and changing how people work. While supporting the training, I kept wondering what would happen after the participants went back to work. Would they be able to use what they had learned here in their own jobs?
While helping with an exercise, I heard someone say, “I think I’ll forget all of this later.” During training, participants are given a sequence to follow and something to make. Once they return to work, though, they first have to decide for themselves what to use AI for.
During training
A sequence to follow and something to make are given.
Back at work
You first have to decide for yourself what to use AI for.
Hearing that made me think about the steps that still lie between finishing an exercise and actually putting it to use.
Starting from Your Own Work
The participants were working professionals with experience in their own fields. I wished we could have spent more time connecting their knowledge of their work with AI.
Still, even work you know well is hard to put into words. To explain a judgment you usually make without thinking, you have to retrace which conditions you looked at and what mattered to you. Asking AI for something is similar. Having the result you want in your head is not the same as being able to describe it concretely.
So I felt it would help to support the process of drawing out people’s thinking, alongside giving example prompts. That could mean working through questions about what they do, where they get stuck, and what they want to change. Instead of writing a finished request from the start, they could sharpen it through back-and-forth.
People using AI do not need to know every answer in advance. They can ask about what they don’t know, compare the answers with their own experience, and decide what to do next. That was the kind of approach I wanted to share more of.
Where Good Content Falls Short
The training content was good. What I found limiting was how hard it was to follow individual questions far enough in a group setting. Everyone heard the same explanation, but their work and their questions differed. Even while supporting the exercises, it was not easy to answer those differences in depth.
AI is a tool you can give your own context to and get help from. Yet in the very setting where people were learning AI, there was little room for that individual context. Beyond time spent learning the same material together, I felt participants also needed time to think through their own work.
I wondered what training within one department or a small team might look like. People could talk through recurring procedures or time-consuming tasks in work they all know, then try applying AI. If someone who knows the work and someone who helps with AI shaped those ideas together, finding something to carry on after the training seemed easier.
Reusing It in the Next Task
This experience made my idea of the goal of AX training a little more concrete. What participants have made by the end matters, but so does whether they can think of where to try AI in their next task. Even if they forget some of the mechanics, they can carry their learning forward as long as they can ask again for what they need and give it a try.
If I help with this kind of training again, I would like to start by having people describe work they already know well, and help them all the way to trying it themselves.
01
Describe the work
Put work they already know into words and organize it together
02
Find what to hand off
Find parts of that description to try with AI
03
Try it yourself
Participants try it in their own work
What this experience made me want to do more of was not introducing a long list of new features, but helping someone return to AI in their own work.