It's a weird time to be a student at Cornell.
Seniors have spent four years and nearly $300,000 getting ready to enter a bleak economy that isn't made for them or their talent.
Juniors in Big Tech, consulting and finance have just survived a grueling recruitment cycle. Now, many are left wondering if they even want these jobs.
As a sophomore, I'm seeing up close how my friends spend hours on calls with banks, schmoozing with just the right number of bankers to get themselves through the door … only to find themselves working 8 a.m. to 10 p.m., six days a week next summer.
Freshmen, on the other hand, have just arrived at Cornell thinking that they have the perfect path: coffee chat with the big consulting clubs, join a few, go through rigorous new member education programs for each and … bang! They'll land their dream internship.
Cornell Career Services too will tell you this is the formula: outwork your peers, network harder, stand out. What they won't tell you is that the formula is now outdated, designed for a world that no longer exists.
What a lot of us are slowly waking up to is that the real world now operates by different rules. You're not just competing with other analysts — you’re also competing with machines. ChatGPT's latest model can build a client-ready slide deck in minutes. Anthropic's Claude can run through a financial model and generate a cost-benefit analysis in seconds. Just last month, Anthropic launched Claude Cowork, a feature that even senior management at top tech and insurance companies fear. Top consulting firms have already rolled out their own internal AI models to automate the routine tasks once handled by junior staff. AI models can now produce the traditional bread and butter of interns, junior analysts and associates — and they can do it faster, cheaper and more efficiently.
Last summer, I worked at a small public affairs firm supporting Big Tech clients on AI policy communications. I'm actively involved in a strategy consulting club at Cornell, and I also founded a political consulting club on campus my freshman fall. Across these environments, I've seen and experienced tasks I used to spend hours perfecting get automated away in real-time. To date, we’ve seen nearly 80,000 jobs automated by AI, and that number is only increasing.
I don’t write this piece as an argument for giving up on traditional recruiting. Learning how industries work, building real professional relationships, developing judgment under pressure — those experiences are still useful. I wouldn't have known any of this if I hadn't experienced it myself. But there's a difference between doing something because it builds durable skills, and doing it because the path feels safe. The former is an intentional strategy, whereas the latter is sleepwalking.
Yet, if you walk into the Career Center today, you'll find the same advice that was handed out a decade ago: optimize your resume, practice your behavioral interviews, network early and often and you should be fine. We are yet to see a real curriculum address how AI is reshaping the industries we as students are preparing to enter. Conversations about which entry-level roles are most exposed are rare and there is no guidance on how to extract durable value from a recruiting cycle that may be training you for work that won't exist in five years. The institution tasked with preparing us for our careers has largely looked away.
What this moment calls for is reflection on your trajectory ahead. If you’re going on the traditional path, you should be actively asking what you're looking to get out of it, and already thinking about what comes next. Some people are learning operations at consulting firms before launching their own ventures. Some are deliberately choosing work that resists automation, not because they couldn't do anything else, but because they’ve thought hard about what's durable. Some are building at the frontier itself, writing new rules instead of following old ones. Whatever it may be, start preparing now.
Whatever it is you choose to be your next step, the most foolproof thing you can do right now is not add another club to your resume or try to optimize your LinkedIn. None of that matters as deeply as developing contextual judgment — the ability to know which questions to ask, which outputs to trust and where human taste and discernment still matters. In practice, that means using AI tools actively, not passively; running your own financial models, then run them again with Claude or ChatGPT and study where they diverge; take a consulting case, solve it yourself, then stress-test your framework against an AI-generated one. The goal throughout building contextual judgement is to use these tools as sparring partners. The students who will thrive in this new economy aren't the ones who avoid AI or the ones who outsource everything to it, but the ones who understand it well enough to know exactly when it fails.
There's something sad about writing this. For decades, the formula was simple: grind in college, land the offer, climb the ladder. But this moment is also an incredible opportunity for anyone with the agency and creativity to write new rules entirely — to build the frameworks, tools and ventures that define what work looks like on the other side of this shift, rather than compete for a shrinking slice of the old one.
Career service offices across the country were built to support the old formula, and to their credit, they've done it well. But with AI in the picture, that equation has to change. Cornell Career Services has the reach and the trust to lead this conversation … but only if we ask for it! As students and inheritors of this economy, we should push for panels with professionals navigating AI disruption firsthand, ask our clubs to run sessions on AI literacy alongside case prep and request advising conversations about which roles are most exposed. Institutions only change when the people inside them insist on it. The question is whether we’ll be the generation that does.
Kashyap Rajesh is a sophomore in the College of Arts and Sciences. He can be reached at kr583@cornell.edu.
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