Everyone, it seems, has discovered artificial intelligence.
Or at least everyone has discovered that saying “AI” is now a requirement for staying relevant in the conversation. I find myself using those two letters almost on the hour, every hour.
AI is everywhere.
On billboards. In conference session titles. In product demos. In casual conversations. In strategic plans. In the sudden confidence of companies that, until fifteen minutes ago, were not especially known for technological imagination.
And I get it.
Markets move. Institutions panic. Companies adapt. Nobody wants to be seen as yesterday’s solution in tomorrow’s world. But after a while, the noise becomes hard to separate from the signal. Some of what I see and hear is serious. Some of it is thoughtful. Some of it reflects real attempts to help solve real problems.
But much of it is just lipstick on a chatbot.
A familiar product with an AI sticker.
An old workflow with a new acronym.
A service model that has not fundamentally changed, now marketed as innovation because a machine can draft the email faster.
This is where we have to be honest.
AI is not a magic wand. It is not a strategy. It is not a moral position. It is not, by itself, a vision for the future. It is a tool, a force, an accelerant, and increasingly, an infrastructure layer beneath almost every form of work. But when people who have not done the hard thinking start using AI language to sound profound (have you been on LinkedIn lately?), the whole conversation gets cheapened.
And that cheapening worries me because outside conference conversations and boardroom meetings, students are not experiencing AI as a clever product feature. They are experiencing it as a threat to the bargain they were sold.
Across the country, graduates have been booing commencement speakers who bring up artificial intelligence. Some people have treated this as immaturity. Others have treated it as righteous resistance. I think both readings are naive.
Imagine being a student today.
You were told to study hard, earn the credential, build the résumé, follow the rules, and trust the system. You were warned not to use AI in your classes because it might be cheating. Then you arrive at graduation, carrying debt, uncertainty, and a degree whose value already feels less secure than promised, only to hear someone wealthy enough to experience disruption as opportunity tell you that AI is the future.
Of course students are angry.
They are not wrong to feel that something is off.
They are not wrong to distrust the sales pitch.
They are not wrong to notice the hypocrisy of institutions that spent the last few years policing AI in classrooms and now want to celebrate it from the stage.
But anger is not preparation and booing is not a career strategy. And refusal, however emotionally satisfying, does not slow down the future.
This is the truth students deserve to hear, even if they do not want to hear it. The future is not waiting for every graduate to feel ready. It is not pausing while universities rewrite curriculum. It is not asking permission from faculty committees. It is not checking whether the student body has achieved emotional consensus.
The future is not taking attendance. It is moving. Fast.
The real question is whether education will move with it, or keep producing graduates who are shocked that the world did not preserve the rules they were trained to obey.
AI did not create the crisis in education. It exposed the fact that too many students and universities were already unprepared for the future.
It exposed how much of education still depends on performance rather than proof. It exposed how many assignments reward completion more than thinking. It exposed how many curricula are organized around information scarcity in a world of information abundance. It exposed how many institutions confuse content delivery with education. It exposed how fragile the entry-level job market becomes when basic cognitive tasks can be automated, accelerated, or outsourced to machines.
Most painfully, it exposed the gap between what students are promised and what they are actually prepared to do.
That is where the protest should be aimed.
Not at the existence of AI.
But at the failure to prepare students for a world in which AI exists.
Universities should not be asking only, “How do we stop students from using AI dishonestly?”
They should be asking, “What if the assignments became dishonest first?”
What if the old measures of learning were already too shallow, too procedural, too easy to simulate? What if the essay, the problem set, the discussion post, the résumé, the cover letter, the polished application, and the generic group project were already losing their power as evidence of real ability?
AI did not ruin those signals. It revealed their weakness.
That should terrify universities far more than plagiarism because the deeper crisis is educational integrity, not academic integrity.
Are we preparing students to think, or merely to submit? Are we preparing them to judge, or merely to comply? Are we preparing them to build, question, collaborate, adapt, and lead, or merely to accumulate enough institutional approval to be handed a credential?
For years, too many universities have treated career readiness as a department, not a design principle. They have treated AI literacy as an add-on, not a foundational fluency. They have treated human skills as “soft”, even as the world keeps proving that judgment, empathy, communication, creativity, ethical reasoning, and cultural intelligence are anything but soft.
Soft skills? They are survival skills.
And if universities do not redesign education around them, students will keep graduating into a world they recognize only by rumor.
But students do not get a free pass either.
It is easy to blame institutions. Sometimes it is even correct. But at some point, adulthood begins when we stop asking whether the future has asked our permission.
Students cannot wait for universities to catch up. They cannot outsource their readiness to a syllabus. They cannot treat their anger as evidence of competence. They cannot reject the tool and then complain when those who learned to use it shape the world around them.
Real resistance requires fluency.
Learn the tool well enough to question it. Use it well enough to understand its limits. Study it deeply enough to see its bias, its hallucinations, its power, its danger, and its seduction. Refuse to become dependent on it, but also refuse to become ignorant of it.
There is nothing noble about being unprepared and nothing radical about becoming obsolete by choice.
The students who will thrive are not the ones who worship AI. They are not the ones who outsource their thinking to machines and call it productivity. They are also not the ones who perform rejection while the ground shifts beneath them.
The students who will thrive are the ones who learn to bring something AI cannot fully manufacture.
Taste. Judgment. Trust. Moral courage. Lived context. Relational intelligence. The ability to deal with ambiguity. The discipline to verify. The humility to revise. The imagination to build. The wisdom to know when speed is useful and when speed is dangerous.
That is the human advantage.
And it has to be cultivated deliberately.
The future of work will not reward people simply because they have degrees. It will reward people who can demonstrate value in a world where basic output is increasingly cheap. It will reward people who can ask better questions, frame better problems, work across cultures, interpret complexity, and build proof of their ability beyond institutional claims.
That is why education has to change.
Not cosmetically. Fundamentally.
We do not need more AI panels where everyone says the same six things in slightly different language. We do not need more companies pretending that inserting a chatbot into an old process is transformation. We do not need more institutions treating AI as a compliance issue while the labor market rearranges itself in real time.
We need a new pedagogy of proof.
Students should not merely write about what they know. They should demonstrate what they can do with what they know. They should build portfolios, projects, prototypes, campaigns, research, ventures, interventions, community work, creative artifacts, and evidence of judgment under real conditions.
They should learn with AI, against AI, beyond AI, and sometimes without AI.
They should be asked to defend their reasoning. To explain their process. To critique machine output. To compare sources. To work with people unlike themselves. To make decisions when the answer is incomplete. To produce work that carries the mark of human seriousness.
That is the work.
And it will not happen if universities continue to move at the speed of committees while technology moves at the speed of capital.
It will also not happen if students mistake protest for preparation.
The grief is real. I want to be clear about that. There is a genuine sadness in watching a generation walk into a future that feels less stable than the one they were promised. There is real anxiety in knowing that entry-level jobs may change or disappear before students even get a chance to prove themselves. There is legitimate anger in seeing technology companies profit from disruption while telling everyone else to be resilient.
But grief has to become construction. Otherwise, it curdles into resentment.
That may be the challenge of this moment for all of us.
For students, the challenge is to stop confusing refusal with power.
For universities, the challenge is to stop confusing policy with preparation.
For companies, the challenge is to stop confusing AI language with actual innovation.
For the rest of us in education, the challenge is to decide whether we are going to help students navigate the future, or simply sell more services to institutions that are afraid of it.
The future is not taking attendance. And it is not pausing.
It will not pause for our conferences. It will not slow down for our skepticism. It will not reward our slogans. It will not care how many times we used the word “AI” in a brochure.
It only cares about what we are building in response.
If students are angry, let them be angry. But then help them become ready.
If universities are worried, let them be worried. But then force them to redesign.
If companies want to talk about AI, fine. But then ask them what problem they are actually solving, what human capacity they are actually strengthening, and what future they are actually helping students enter.
In the end, the machine is not the mission.
The mission is still human development.
The mission is still wisdom.
The mission is still helping young people become capable, ethical, adaptable, courageous, and whole in a world that will not wait for them to feel prepared.
Boo if you must.
Question everything.
Distrust the hype.
Challenge the profiteers.
Demand better from universities.
But after the noise fades, learn the tool. Build the proof. Strengthen the human advantage. Prepare for the world as it is becoming, not the world as it was promised.
The future is not taking attendance.
But it is keeping score.
Ex Cogitatione, Progressus.
Girish
