The Generation Saying No: Is Anyone Listening?

There's a clear signal that is being misread as noise from a generation that was expected to be the early adopters of AI. The market calls it resistance. I think it's something much more valuable.

Jul 23, 2026

This is Part 7 of The AI Reckoning: A Future of Trust Series

The most digitally fluent generation in history is quietly declining the most powerful technology ever handed to them. Almost everyone is misreading why.

She said it with one word.

My niece was in town, and I had taken her and two of her friends to lunch. They were curious about what I was working on, so I told them a little about the new business, about the AI coach my co-founder and I were building, designed around empathy, built to support people through change. I was still shaping how I talked about it then. This was before the TEDx talk, before the language had hardened into anything polished. I was just a person at lunch, describing the thing she believed in.

One of my niece’s friends looked at me and said, “Creepy.”

Not hostile. Not even particularly interested in debating it. Just a verdict, delivered with the casual confidence of someone who had settled the question long before she sat down at that table. The conversation moved on. I didn’t.

Because here is what I knew about that young woman that made the word impossible to dismiss. She was not afraid of technology. Nobody in that generation is. She has never known a world without it, never had to learn it the way the rest of us did, never experienced it as new. Her “creepy” wasn’t coming from someone who didn’t understand AI or was evaluating the technology. It came from someone who was evaluating the relationship.

I didn’t know it yet, but that lunch was the beginning of a question I would eventually be unable to put down: whether the loudest misread in this entire industry might be generational. The story we keep telling ourselves is that young people will lead AI adoption the way they led every technology wave before it, and that skepticism is something age does to you. But that is not what the evidence is showing us. The evidence is showing something stranger, and I think far more important.

The Misread

Inside most organizations, there is a standing assumption about who will struggle with AI. The older workers, the story goes, will resist. The young ones will lead. It’s a reasonable assumption, because it has been true for every technology wave in living memory. Teenagers drove the adoption of personal computers, video games, social media, and smartphones, and skeptical parents were dragged along behind them.

With AI, for the first time, the pattern has inverted.

The survey data emerging over the past year tells a story almost nobody predicted. Gallup’s 2026 study of more than fifteen hundred Americans between fourteen and twenty-nine found that excitement about AI among Gen Z has dropped fourteen points in a single year, to just 22 percent, while anger toward the technology rose nine points, to 31 percent.[i] A separate consumer study found that among Gen Z non-users, a majority say they are simply not open to adopting it, a higher refusal rate than their grandparents’ generation.[ii] Read that again. Older Americans are now more open to AI than young ones. The generation that was supposed to lead this adoption is the one most visibly declining it.

But there is a contradiction that breaks the easy explanation: their usage hasn’t collapsed. Roughly half still use these tools weekly. They haven’t fled the technology. They use it, fluently, while trusting it less and less. Their skepticism is not rising because they don’t understand AI. It appears to be rising in the places where they understand it best. Employed Gen Z workers were three times as likely to say the workplace risks of AI outweigh its benefits than to say the reverse. Only three percent said they would fully trust work generated entirely by AI. Given the choice, nearly seven in ten said they would rather have the fully human version.

The industry reads this as an adoption lag. Something training will fix. Better onboarding. More time. I want to suggest a different reading, and it’s the reason this piece sits where it does in the series. In Part 5 of this series, The Human Adoption Gap, I wrote about the difference between whether people can adopt a technology and whether they will. This generation is the purest expression of that distinction we have. Their can is total. They are the most digitally capable cohort ever to enter the workforce. It’s their will that is saying no. And when the people most able to use something are the most reluctant to engage, that is not a lag. That is a signal.

They’re asking whether it’s worthy of their trust.

What the No Is Protecting

If you listen to what our younger generation is actually saying about AI, rather than what gets said about them, the refusal starts to organize around three things and none of them are fear of the technology.

The first is creativity, and more precisely, the fear of losing the struggle that produces it. In the Gallup research, Gen Z consistently declined to believe that AI enhances creativity or critical thinking, and a striking eight in ten students said that using AI tools now would likely make learning harder for them later. One college student put it in terms that stopped me: AI removes the friction from learning, and the friction was the point.[iii] I understand that instinct in my bones. I learned to water ski in the ocean and to snow ski in a blizzard, and what those experiences taught me had nothing to do with technique. They taught me that we learn by pushing against something. Friction is not the obstacle to growth. It is the mechanism. A generation raised to believe that is now watching a technology whose entire promise is the removal of friction, and they are asking the question their elders keep skipping: what happens to the muscle when nothing pushes back?

The second is authenticity. This generation came of age inside a culture that prizes the genuine above almost everything, and they are watching a flood of synthetic content wash through every feed they grew up on. They can usually spot it. They increasingly resent it. And they have started to treat “made by a person” as a marker of value in itself, the way an earlier generation might have treated handmade or original. When seven in ten prefer the fully human version of a piece of work, that is not nostalgia. It is a statement about what they believe work is for.

When the people most able to use something are the most reluctant to engage, that is not a lag. That is a signal.

I relate to this as a creator, not just an observer. I wrote my book waking at five every morning for a year, each word, each phrase, each thought mine. I used an editor at the end to fine tune, but the writing was mine, and the difference between those two things was never confusing to me. As a sculptor and painter I know the process of adding and subtracting and adjusting is not preparation for the work. It is the work. In business, as a creative director I went through version after version, but the vision came from somewhere within me, and no round of revisions ever changed whose it was.

And I will tell you something in the spirit of this piece: I write with AI now. I start with my own drafts, my own arguments, my own stories, and I use it the way I once used that editor, to pressure test and refine. The vision is still mine. The boundary I hold is the same one I hear this generation describing: I know exactly what it can do, and that is why I am careful about what I let it do for me. If that boundary sounds familiar, it should. It turns out the question they are asking is the right question for all of us.

The third thing the no is protecting is the ladder itself. Every previous generation entered the workforce at the bottom, doing the routine tasks through which a craft is actually learned, the first drafts, the research grunt work, the entry-level analysis. Those tasks are precisely what AI automates first. This generation is being asked to climb a ladder whose bottom rungs are being removed while they are standing on them, and then being told their hesitation is a mindset problem. The numbers behind that feeling are real: unemployment among recent college graduates is running well above the rate for workers overall, and competition for entry-level postings has climbed sharply year over year.[iv] One recent graduate put it plainly in a local news interview: the hard part isn’t accepting that AI exists. It’s accepting that it’s taking the opportunities they trained for. Their skepticism about whether this technology serves them is not paranoia. It is a reasonable reading of their own position.

The Receipts

There is a reason this generation’s “no” arrives faster and more confidently than anyone expected.

They have seen this movie before. They are the only generation that lived the entire lifecycle of the social media promise from inside their own childhoods: the launch, the euphoria, the connection that curdled into performance, the engagement that turned out to be extraction, the apology tours. They were the product the last time a world-changing technology promised to empower them. The lesson they took from the smartphone era, that moving fast and breaking things includes breaking people, is documented in their behavior, not just their sentiment. A recent Deloitte survey found nearly a third of Gen Z had deleted a social media app in the past year.[v] The market for deliberately limited phones is growing fastest among buyers under thirty, and they describe the downgrade not as nostalgia but as boundary setting.

So when the next transformative technology arrived promising to empower them, they did something no generation before them had the experience to do.

They priced the promise against the last one.

This generation is being asked to climb a ladder whose bottom rungs are being removed while they are standing on them, and then being told their hesitation is a mindset problem.

The reframe I keep arriving at, that connects directly to the last piece of this series, Part 6, Signal vs Noise is this: the industry is filing this generation’s refusal under noise, sentiment to be managed, an adoption lag, or a training gap. But I believe their refusal is closer to signal than almost anything else in the market. They are the users with the most fluency and the least sunk cost, and they are the ones asking the eighteen-month questions the rest of the market keeps skipping. What does this do to me over time? What does it cost that isn’t on the invoice? Who benefits from my adoption? Those are the questions I spent the last piece urging builders, investors and enterprises to ask. An entire generation got there first and we are missing it because we’ve been calling it resistance.

They may be the only constituency in this story practicing foresight, and they are the ones being told they don’t understand.

The No My Algorithm Hides

Here is a confession that took me longer to arrive at than it should have. I live inside the world of AI. My feeds are full of builders and investors, people for whom this technology is genuinely thrilling, and the algorithms that shape what I see have learned to give me more of what I already give my attention to. The generational refusal this piece describes was invisible from where I stood, not because it was hidden, but because I was never shown it.

The first time someone put it in front of me directly, I pushed back. One of the women on my team shared the insight with me. She sent me an article making the case that this generation was turning away from AI, and my first reaction was the industry’s reaction, almost word for word. They’ll come around. It’s an adoption curve. They don’t fully understand it yet. I reached for every available explanation except the one on the page. It took me longer than I would like to admit to notice what I was doing: I was reading a signal and filing it under noise, which is the exact failure I had just spent an entire piece describing in other people. Even the lunch I opened this piece with had been sitting in my memory as an anecdote, one word from one young woman, until someone I trusted connected it to a pattern and made me look again.

Then the evidence stopped being quiet, siloed and easy to miss. At the University of Central Florida this Spring of 2026 a commencement speaker told graduates that AI was the next industrial revolution. The arena booed. At Middle Tennessee State, a record executive told the class that AI was rewriting their industry as they sat there; when they booed, he told them to deal with it, and they booed louder. At the University of Arizona, one of the most powerful figures in the history of the technology industry was booed repeatedly for saying AI would touch every profession and every relationship they would ever have.[vi] These were not activists who bought tickets to protest. They were graduates, at their own ceremonies. And this class matters more than any other: they started college the same Fall ChatGPT launched. They are the first graduating class whose entire education happened inside this technology. They know it better than the people at the podium. And their answer, delivered in the most public setting their lives have offered so far, was “no.”

They may be the only constituency in this story practicing foresight, and they are the ones being told they don’t understand.

If you are a builder or an investor and none of this has reached your feed, that is worth sitting with. I know exactly how the reflex feels from the inside. The signal was there. I filed it under noise myself, until someone made me look twice.

What I Don’t Know

This is the point in the piece where I would normally consolidate the argument. Instead I want to be direct about the limits of what the data can currently support, because this topic deserves that care.

We are still in the early days of AI, and the research on this topic is also early and thinner than the confident takes on all sides suggest. I don’t know whether this is a durable values position or partly a life-stage effect that softens when this generation has mortgages and deadlines and less room for principle. And I don’t know how evenly the refusal is distributed; it may be concentrated among students and creative workers and much weaker elsewhere.

I also know the boundary of this refusal is not a clean generational line, because I live with the evidence. Someone close to me, a generation older than the people this piece is about, has been telling me for years that AI is “just an algorithm.” He works with the special needs community, and his whole professional life is built on the conviction that nothing replaces human presence. He is also unfailingly supportive of me and of what I’m building, which means his skepticism arrives gently, and I suspect he softens it more than he feels it. And yet, the handful of times I’ve used AI to help him with something real, he has been genuinely glad for the result. He holds both positions at once, the principled rejection and the practical appreciation, and he is not confused. He is conflicted, which is different, and I have come to think it may be the most common relationship anyone has with this technology right now. The surveys capture it as a contradiction. Up close, it looks more like a person trying to protect something while still living in the world.

What I am also discovering as of late is that the standard explanation, that they’ll come around once they understand it better, has the evidence exactly backwards. Understanding is not what they lack. Understanding appears to be where the skepticism comes from.

The Seat, Not the Pitch

So rather than resolve the question, I want to open it up to discussion. If you are part of this generation, I would genuinely like to hear how you decide what AI is allowed to touch and what it isn’t. If you manage people from this generation, I’d like to hear what their selective refusal actually looks like inside your organization. The comments are open, and this is the one piece in this series where the conversation may matter more than the argument.

And if you are building or deploying this technology, the way forward is not a better message. It is a seat. This generation is not asking to be persuaded. They are asking to be included in the decisions being made about the work, the tools, and the future they will inhabit longer than anyone else in the room. The organizations that bring them into the planning, and visibly change course based on what they hear, will earn something no adoption campaign can buy. The ones that keep trying to convert them will keep manufacturing the resistance they are trying to cure.

Understanding is not what they lack. Understanding appears to be where the skepticism comes from.

I have thought about that lunch, a couple of years ago, more than almost any conversation this year. And I no longer hear “creepy” as a door closing. I hear it as the price of admission being named. My niece’s friend was not telling me the thing I am building should not exist. She was telling me what it would take for her to trust it: that it listen without harvesting, that it support without replacing, that it never pretend the relationship is something it is not. Those are not unreasonable demands. They are the most precise product requirements I have ever been handed, and they came from a young woman over lunch, for free. The question is whether anyone building this technology is willing to treat the generation that said “no” as the standard to build toward, rather than the audience to win over.

Every technology wave has had its skeptics. What it has never had, until now, is a skeptic class made up of its most capable users.

They aren’t afraid of the future. They’ve already lived in one version of it.

Their “no” isn’t the absence of an answer. It’s an answer.

The question now is whether the rest of us are listening.

The next piece turns from the people moving slower than the market wants to the market moving faster than its own safeguards can follow. Because while human trust struggles to keep pace with AI, something else is falling even further behind: security. And the gap between those two speeds is where the next reckoning is already forming.

Sheryl Anjanette

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