Earlier this year I attended a college graduation ceremony of my teenage nephew. A clip from that spread quickly online.
An executive from an AI-focused company was delivering the commencement address to a class of arts and humanities graduates. Midway through, she began speaking with real enthusiasm about artificial intelligence as the next industrial revolution.
The students booed. Loudly.
What made the clip go viral wasn’t just the reaction — it was her response to it. She looked genuinely thrown, as if it hadn’t occurred to her that a room full of newly minted graduates might not share her excitement at the mention of AI.
In that moment, two very different visions of the future ran headlong into each other. One voice was talking about acceleration and innovation. The audience was quietly wondering whether they’d have a place in the future she was describing.
Much of the commentary that followed chalked it up to tech-phobia or resistance to change. That explanation doesn’t hold up well.
Most young professionals already lean on AI every day — to brainstorm, to turn a bloated email thread into three usable bullet points, and to figure out if hot sauce packets, a can of corn, and a brick of ramen can pass for dinner. (Usually, they can.)
So the unease isn’t really about the tools. It runs deeper than that.
The Fear Isn’t About Technology — It’s About Relevance
What people are actually reacting to is a growing sense that conversations about the future of work are dominated by efficiency, automation, and margins — and increasingly disconnected from what it actually feels like to live through that shift.
AI’s upside is real. It’s already accelerating medical research, widening accessibility, cutting down repetitive work, and unlocking creative possibilities that used to require far more resources than most people had access to. None of that should be dismissed.
But a lot of the loudest AI conversation right now isn’t really about enriching human life or making work more meaningful. It’s about output. Scale. Cutting cost. Moving faster. Doing more with fewer hands.
People feel that.
This lands hardest on younger professionals — people entering fields where entry-level roles are already being reshaped, where creative work can feel newly disposable, and where the old on-ramps for building experience and confidence are getting harder to find.
In some industries, the exact tasks that used to go to interns and junior staff — the ones that let them struggle a little, ask questions, and slowly get better — are being automated away before those employees ever get a shot at them.
So what happens to growth when the work people once used to build judgment starts vanishing or changing shape? What happens to a sense of creative identity when years of hard-won skill can be reproduced in seconds? What happens when the things people worked hardest to develop in themselves start to feel harder to prove and easier to replace?
None of that is irrational. Those are legitimate human questions.
Leadership Still Shapes What Comes Next
Sociologist Ruha Benjamin has spent a lot of time pushing back on the idea that technology is neutral or unstoppable. In her view, the future gets built through human choices — priorities, values, whose voice counts in the room while it’s being designed.
That framing matters right now, because so much of the AI conversation focuses on what the technology can do while sidestepping a much harder question:
Who still feels seen inside the future being described?
The leaders people actually trust are the ones who stay in that question rather than rushing past it — who can hold the fact that people are curious and unsettled at once. Excited and worn out. Hopeful and wary, all at the same time.
People notice when AI discussions begin and end with cutting labor and boosting output. They also notice — and remember — when leaders talk instead about easing burnout, widening access, protecting room to learn, and making space for work that actually feels worthwhile.
Growth Was Never Built to Be Efficient
This shift puts a different kind of responsibility on leaders.
As AI reshapes or eliminates traditional entry-level work, leadership now has to think much more deliberately about how people actually develop in the first place.
Judgment isn’t built quickly. It comes from trying, getting it wrong, sitting through hard conversations, asking the awkward question, and occasionally being handed something before you feel ready for it.
It also comes from sitting with not knowing — long enough to form your own take before you ever ask AI for one.
Mentorship doesn’t move fast. Creativity is often messy by nature. Confidence is built through repetition, conversation, discomfort, and support — and some of the most important professional growth happens in moments that are hard to measure and even harder to automate.
Younger professionals are trying to figure out, in real time, where that boundary sits. When does AI actually support growth — and when does it quietly take the place of the struggle and repetition that build confident, independent thinking?
There’s no settled answer yet. That uncertainty is a big part of why this moment feels so unsettling.
The Question AI Can’t Answer
Work will keep changing — that much is certain. The real question isn’t whether AI belongs in the workplace. It’s what room leaders choose to make for learning, mentorship, creativity, and human development alongside it.
Because people are still working out how to grow inside systems that are evolving faster than the pathways that used to guide that growth.
And they’re watching closely to see what leaders keep valuing while everything else shifts around them.
Adapted from Lara Dollens’ thought process and writing.
Best wishes
yogesh