Your Team Isn’t Bad at AI. They’re Grieving.

Most teams treat AI adoption as a training problem, but underneath the technical roadblocks, people are going through complex emotions. If they aren’t given the space and time to work through them, they won’t be ready to adopt.

“I’ve got a great idea,” I told my manager. “I’m going to build our design system, turn it into a plugin, push it to our org repo, and train everyone to run it themselves.” I paused. “I guess then I won’t have a job.”

I said it as a joke, but I was worried. Not that I was replaceable, but that I wasn’t as smart or as creative as I’d thought and AI was about to prove it. And, I realized, that if that was how I felt, my teammates had to be feeling it too.

Where teams stop

Every team hits roadblocks adopting AI, and the technical ones are the easiest to see. Mine was leaning into my husband’s office to ask “what a grep was, and why you push and commit to a repo, aren’t those the same thing?” Those are yield signs; they slow you down but they don’t stop you.

What stops a team is the emotion part. People can’t learn while they’re working out whether the thing they were good at (the thing their identity is tied to) still matters. AI is making people redefine what they believe about their own abilities, and if where that redefining lands is “then I was never as good as I thought,” then no amount of training can get through it. You have a team of people grieving, trying to learn from a tool that’s the cause of it.

What would have helped me

Being told I wouldn’t lose my job didn’t help, because it wasn’t true. Anyone can lose their job.

What would have helped me was evidence: the headlines on our homepage that AI couldn’t have written, the campaign idea that was all mine, the product logo I’d drawn by hand. Give a person proof of their own indelible ideas and you can redraw the definition of their work together: what are the things only you are good at, what can you alone do for your team and your role and the company?

Three people on my team

My team got there on our own. We’re capable and we landed on our feet, but that is a circumstance, not a system, and the next team might not be so lucky.

Our growth marketer knows which campaign is worth building and which one to kill. AI can write the report for her but it can’t make that call, because the call requires walking a tightrope of market, personas, data, internal politics, budget and instinct. She’s making her bet, and owning the results.

Our producer will get all-in on an argument with the CEO over a single word, because he knows it’s the wrong one and he’s right. He isn’t being stubborn (well, maybe a little). He won’t ship something that’s only approximately true, and he spends social capital to pay for that.

Our webinar series was framed on paper as a teacher in a classroom, and I changed it to a conversation between a leader, a researcher, and a teacher, because our audience doesn’t want to watch someone teach. They want to see research become a shift in a classroom. I’m sitting in the audience’s seat, looking through their eyes and following what I find there.

Each of those decisions took a combination of experience, intuition, and care that AI can’t replicate. When a team has firm footing in what makes their work excellent, alone and together, AI gets closer to what it promised to be: something that saves time and amplifies effect.

Make room for the grief

What would make this easier for any team is a ritual of grief. (I don’t mean a funeral for my design briefs.) I mean that as the work speeds up, you stop and mark what is changing and what is being lost, and you let it be said out loud that this is hard and disorienting and a little frightening.

That’s the leader’s job, and it starts with the leader going first. Someone has to say “I don’t know where this is headed or what’s going to be valuable, and that’s hard” before anyone else will. It doesn’t change the plan. You still ship, you still plan and build and create. It just means the fear gets said out loud and everyone gets to feel together in the hard stuff for a little while.

I get why teams don’t do this. It asks a lot to stop and say you’re afraid when work is piling up, and capable people would rather just push through. But pushing through is the expensive version.

You can’t solve the grief, but once it’s out in the open it becomes less oppressive, and then there’s room for the technical work everyone wanted to start with. You can establish team-wide ownership, so you know who holds the standard for which skill. You’re ready to automate anything that makes you go “ugh, not this hour of my week again.” Most of all, the team stops fighting the change, because you’re not asking them to pretend it costs nothing.

The invitation

I was afraid AI would prove I wasn’t as good as I thought. And it did, in a way. It’s very competent at the parts of my job I’d tacked a good part of my worth to. I’m efficient, I’m organized, I’m excellent at pattern recognition. What it can’t do is the part I had a hard time putting words to, which turns out to be the part that’s mine.

Every time the AI gets better, it presses you to answer that question again: what’s only yours, what’s unique about you, what constellation of experiences and feelings and expertise belongs only to you?

You can hear that question two ways.

One is a threat, evidence that the ground keeps shrinking until one day nothing is left that’s yours. The other is an invitation, because there is always something left to discover, about the work and about yourself, and a better tool is only what sends you looking for it. Which way you hear it comes down to how you see the future.

I hear it as an invitation. I believe in the unending creativity and invention of people, and I believe there is always more to find, in the work and in who’s doing it. To lead in the age of AI is to choose that path, and to help your team choose it with you.