We are the first generation of students who can genuinely ask whether the thing we are learning will still be relevant by the time we graduate.
I am studying a Masters in Analytics and Management at London Business School. Every day I sit in lectures about strategy, finance, and data science, while outside the classroom AI is reshaping all three at a pace nobody predicted.
It is a strange position to be in. On one hand, the fundamentals still matter. Understanding how businesses work, how capital flows, and how to think about risk are skills that do not expire. On the other hand, the tools we use to apply those skills are changing faster than any curriculum can keep up with.
The students who are thriving are the ones who treat university as a launchpad, not a destination. They use the structure and the network to build things, test ideas, and develop taste for what matters. The ones who struggle are waiting for someone to tell them what to learn next.
AI has not made university irrelevant. But it has made the passive version of university irrelevant. You cannot sit in lectures for two years, collect a degree, and expect that to be enough. The degree gets you in the door. What you build while you are here is what sets you apart.
My approach has been simple: learn the theory in class, then go build something with it. Every project I have shipped during my masters has taught me more than any exam. Not because the exams are bad, but because building forces you to confront the gap between knowing and doing.
The era of AI does not make education less valuable. It makes the wrong kind of education less valuable. And it makes the right kind, the kind where you actually build things, more valuable than ever.