Juliette's Learning Tribe
How to introduce AI to your team when some of them do not want it
Some of your team will not want AI. Ask them why, sort fair objections from fixable ones, change the plan where they are right, and measure the work.
I have been going through our own Level 5 in Future Fluency. It is the level for people who lead a team through AI, rather than only changing their own work.
The AI turns out to be the easy bit. The hard bit is the people. Especially the ones who do not want it.
If you lead a team, assume somebody on it has typed “can an employee refuse to use AI?” into Google this month. Start there.
Write down who changes, and how
Before any training. Before any tool.
Take each person in your team. Write what changes for them. Then write who depends on their work, because those people change too.
Look hardest at whoever is best at the job the old way. They have spent years getting good at it. Now the thing they are known for is the thing the tool does. They have the most to lose, and their worry is fair.
Ask them, and write down what they say
Decide how you will ask. One to one, as a team, or in writing. Some people will never say it in a room.
Then ask, and record what each person raises. All of it.
I learned why this matters the hard way this summer. Somebody told me their work was missing from a tool we had built. They were right. For six days they had used it with none of their work in it, and drawn the only conclusion available. Nobody had listened.
A wrong number you can fix on a Tuesday. You cannot fix that one with code.
And think about the people who did not answer. Silence is not agreement. Go and find them.
Sort the objections into two piles
This is the most useful thing I have taken from the unit.
Pile one is about the change itself. “I do not think AI should write to our clients.” “This takes away the part of the job I am good at.”
Pile two is about the way it is being done. “Nobody showed us how.” “We got two days’ notice.” “Which tool are we even allowed to use?”
Pile two you can usually fix this week. Pile one deserves a proper answer, with your reasons. And some of pile one will be right.
Change the plan where they are right, and say so
Go back to people. Tell them what changed because of what they said.
If nothing changed, tell them that too, and why.
This is what makes anyone bother to answer you next time.
Tell each person what is expected of them
Each person, not the team. Say what is changing for them, and when. Say what you expect them to do, what help they will get, and how long they have.
A slide at a team meeting does not do this. A conversation does.
The person who still says no
There will usually be one. Have the conversation anyway. Write down what you agreed, and what you did not.
Can an employee refuse to use AI? That depends on their contract, your organisation’s procedures, and any duty you have to consult. Talk to HR before you treat a no as a disciplinary matter.
But check their reasons first. Sometimes the person saying no has spotted the flaw. This summer Claude told me I was wrong about a fix, and it was the most useful thing that happened all week. The people who disagree with you can do the same.
Decide what your team will not learn
Not every new skill belongs in your team. Some you can buy in. Some you can share with another team. Some work you can move. Some you should drop.
Pick at least one thing your team will not try to become good at, and say why. It stops the change becoming everything at once.
Measure the work, not the training
This is the bit I care about most.
In twenty years I have watched most training get counted by who finished it. That tells you who turned up. It does not tell you whether anything changed.
So decide at the start what the change should look like in the work your team produces. Faster turnaround. Fewer errors. A report nobody has to rebuild by hand. Then measure that, using figures from your own systems.
And look for where it did not take. That is where the next conversation is.
Where we come in
The Level 5 Diploma in Future Fluency is built for people leading this change in their own department. It is still a draft qualification. You work on your own team, your own processes and your own figures, not a case study about somebody else.
You find out what your team can do now and what it will need. You talk to the people whose jobs change, including the ones who do not want it. You change the plan, lead it, and measure what it did to the work.
If your team is earlier on than that, start with how each person learns AI on their own work. I wrote a tip sheet on talking to AI at work that you can hand round.
Your first Future Fluency module is free. After that, learning is paid.