There’s a version of the AI-at-work story we tell often, and it’s a good one. AI handles the repetitive stuff like data entry, the first draft of an email, a weekly progress report, and we are thrilled we get our time back for the work that actually needs a human: strategy, creativity, the messy and important business of connecting with customers and teammates. In that story, AI doesn’t just make us more productive. It makes us more interesting. We become the resourceful, high-judgment people we always wanted time to be.
That story is true. It’s just not the whole story.
Here’s where I worry and it’s the part we don’t talk about enough: some of the “routine” work AI is taking off our plates isn’t routine to the person doing it. It’s the work they’re good at. The work they find meaningful. The work that took years to get good at. The work that makes them proud, that other people notice and compliment, and that tells them everyone paying attention (like their boss), and “I am excellent at my job!”.
The Baker And The Piecrust
Imagine a baker who has spent a decade learning to ‘read’ dough. They know by feel and by instinct, when humidity is going to make a crust tough, when the butter is too warm, when to stop working the flour before it turns from flaky to leathery. That knowledge lives in their hands. Customers taste it, love it, and tell everyone. It’s part of how the baker feels pride and accomplishment in their work.
Now imagine an oven that monitors humidity and temperature automatically and adjusts the process so the crust comes out perfect, every time, without human support.
The pie is still excellent. Maybe it’s more consistently excellent than before. But something has changed for the baker. The skill that used to separate a good pie from a great one — their skill — is no longer the thing standing between the dough and the plate. The machine is.
This isn’t a hypothetical about bakers. It’s a hypothetical about anyone whose work is quietly being absorbed by a tool that’s more accurate, faster, or simply always-on in a way no person can be. The analyst who took pride in spotting the pattern no one else saw. The support rep who could de-escalate any angry customer. The engineer who could debug anything by instinct. AI doesn’t have to take someone’s job to take something that mattered to them. It can just take the part they were proud of.
Why This Is A Real Problem
I know it’s easy… and it’s tempting to respond to this with the logic: “But now you have more time for higher-value work!” That’s true, and it’s also not the point. I know from all of my work teaching difficult conversations training that pride and meaning aren’t always rational calculations. They’re built from repetition, visible skill, and other people noticing what you do well. When the visible, admired part of a job gets automated, you might be losing the ‘thread’ that connects your effort to your identity. It’s often the same empty feeling that people often get when they retire… except now with AI we are all retiring one little bit at a time.
There’s also a quieter risk: skill atrophy. The baker who stops reading dough because the oven does it all on its own will eventually lose their expertise — not because they got lazy, but because their skills got rusty. And here is the problem, if the machine ever needs a human to step in, that human may no longer be as capable as they once were. Organizations that automate away practiced judgment without a plan can end up with employees who technically have more time, but less capability and less connection to work they find meaningful.
None of this means AI adoption is a mistake. It means the emotional and identity costs of automation are real, uneven across employees, and worth designing for — not something to wave away with a slide about “freeing people up for strategic work.”
What can leaders actually do to continue inspiring and supporting their team?
- Name it before employees have to bring it up. Most people won’t tell their boss, “I feel less proud of my work since we started using this tool.” This can come across like the employee is resisting progress which isn’t good either. This is where transparency will help. A leader who says, “some of you are going to lose parts of the job you loved, and that’s worth talking about” will be giving their team permission to have a real reaction you can talk about. It also shows they are a leader who cares and wants to listen.
- Don’t assume the “freed up” time is automatically fulfilling. Handing someone five extra hours a week doesn’t automatically hand them meaning. If the baker’s five extra hours go to spreadsheet work instead of new recipe development or mentoring a junior baker like they would enjoy, they haven’t traded busywork for purpose, they’ve just traded one kind of busywork for another. Leaders need to actively help people find where their freed-up capacity should go, not assume it will find its own way there.
- Protect some craft, on purpose. Not every task that AI can do should be handed to AI. Some tasks are worth keeping human-led even at a cost to speed or consistency because the doing of them is where someone’s pride, skill, and connection to the work live. Maybe the baker has a signature tart that they developed that is a customer favourite and you ask them to continue making those by hand. This is a real trade-off leaders have to make deliberately, not by default but by deciding with the team, which parts of the craft stay in human hands.
- Redefine what “good at this job” looks like by asking the people doing it. When AI absorbs the skill that used to define expertise, the definition of expertise has to move. That shift shouldn’t be announced top-down; it should be built with the employees whose sense of competence is most at stake. Ask the baker where her judgment is still irreplaceable like recipe development and teaching / mentoring and build the new version of “great baker” around that.
- Watch for disengagement and take it seriously when it shows up. If someone who used to love their work starts seeming checked out, the instinctive read is often “they need a new challenge” or “they’re not adapting well.” Sometimes the real story is quieter: they lost the part of the job that made it theirs, and no one ever acknowledged that loss out loud. Checking in with genuine curiosity — not a performance review — matters here.
The Honest Answer
AI is going to keep getting better at work people like you and I take pride in doing ourselves. That’s not a reason to run away from AI. The leaders and organizations that get this right won’t be the ones with the flashiest AI rollout. They’ll be the ones who treat “will this take away something someone loves?” as a real question to ask before every deployment, and they’ll have an honest strategy idea and answer ready if and when the answer is yes.