The most common mistake leaders make when young people push back is assuming the push is against the thing, not against the terms of the thing. That mistake is shaping much of the response to Gen Z’s skepticism about artificial intelligence.
The recent boos that greeted AI-themed commencement remarks at several universities were easy to dismiss as youthful resistance to change. But these graduates grew up inside digital life. They use AI, experiment with it, and in many cases understand its usefulness more intuitively than the executives urging them to embrace it. Their objection is not to the existence of the technology. It is to the bargain being presented around it.
The message young people keep hearing is familiar. AI is inevitable. AI will transform work. AI will create opportunities. You should be excited. Each statement may contain some truth. But the sales pitch often arrives stripped of the details that weigh most heavily on people entering the labor market now. What happens to the first job? Who bears the environmental cost? Who consented to the use of creative work that trained systems now competing with creators? These are not isolated concerns. They are signs of a deeper problem. The social contract around AI is being written while many of the people who will live with its consequences feel they have no meaningful voice in the terms.
The first break concerns apprenticeship. Entry-level work has never been only about low-cost labor. It is where people begin learning professional judgment. Junior employees draft, research, revise, coordinate, observe, make mistakes, and absorb the habits of a field. Much of that work is routine. Some of it is tedious. But it is also formative.
AI is especially good at many of the tasks traditionally assigned to beginners. That creates an obvious efficiency gain. It also creates a less obvious institutional risk. As employers automate routine work or shift it to more experienced employees using AI, they may weaken the training layer that once converted beginners into capable professionals. A decision that looks rational on a quarterly spreadsheet may prove less rational if it hollows out the future talent pipeline. For graduates who did what they were told to do, earn the degree, build the resume, and seek the first serious job, the bargain can feel unilaterally revised. They are being asked to celebrate a future in which the first rung of the ladder may be pulled up just as they arrive.
The second break concerns environmental honesty. Many young adults were educated to think in systems. They learned to ask who benefits, who bears the cost, and what sits outside the official accounting. They are unlikely to accept an AI narrative that celebrates scale while treating energy use, water demand, and data-center expansion as footnotes. That does not mean every environmental objection is decisive, or that AI’s costs cannot be justified by important benefits. It means the ledger has to be visible. A generation trained to value transparency will hear selective disclosure as evasion.
The third break concerns creative consent. Artists, writers, designers, musicians, coders, and other creators have watched systems trained on human work become commercial products that can imitate, compress, and compete with the labor that made them possible. The legal and ethical debates remain unsettled. But the source of resentment is not difficult to understand. A business model was built before the social contract was negotiated.
That is why Gen Z’s apparent contradiction is not a contradiction at all. Young people can use AI and still distrust how it was built. They can recognize its utility and still question who captured the value. Adoption is not consent. Use is not endorsement. Convenience does not erase grievance.
Leaders will misread these concerns if they treat them as messaging failures. A warmer commencement speech, a better metaphor, or a more empathetic slide deck will not close the gap. The problem is not tone. It is credibility.
The better institutional question is not whether students and workers will use AI. They already do. The question is whether employers and educators will introduce it in ways that preserve pathways into professional competence, account honestly for material costs, and respect the human contribution on which these systems depend.
Higher education has a particular responsibility. It cannot answer student anxiety with vague enthusiasm about the future. It has to show that it is redesigning learning around judgment, verification, ethical decision-making, adaptability, and disciplined use of powerful tools. It also has to help students understand what human capability means when machines can produce first drafts, summaries, code, images, and analysis at scale.
The boos were not the story. They were the audible part of a larger trust problem. The institutions that take the signal seriously will not merely defend AI or denounce it. They will recognize that adoption without legitimacy is fragile.
The work now is not persuasion. It is proof.
About Rick Inatome
Rick Inatome is a business leader who played a pivotal role in the early development of the personal computer industry. Working with other technology pioneers, he helped bring personal computers into the consumer market and later into corporate environments. He currently serves as Managing Director of Collegio Partners and Chairman of the Board at Léman Manhattan Preparatory School. Over his career, he has founded and managed private equity funds, served on multiple boards, and continues to work as a consultant, mentor, and speaker.
