On a Tuesday evening during exams week, more than 50 Cornell students crowded into a classroom to face a stark reality: the traditional finance career path is being rapidly automated in favor of something very different. The workshop, led by Obin AI, transformed the room into a laboratory for the next generation of financial professionals who are learning to supervise the very artificial intelligence tools that are currently shrinking junior headcount at the world’s largest banks.
The urgency in the room was backed by sobering industry data. Recent reports from Anthropic and Bloomberg place business and finance at the top of AI task coverage, with theoretical automation potential exceeding 94%. At firms like Goldman Sachs and JPMorgan, tasks that once occupied six-person teams for weeks—such as drafting S-1 filings or building investment decks—are now being completed by LLMs in a matter of minutes or seconds.
During the hands-on portion of the evening, students built AI agents capable of ingesting thousands of pages of Walmart’s 10-K filings. Within hours, these student-built systems were extracting data, structuring it in Excel, and producing sophisticated benchmarking reports with written narratives. It was a demonstration of how a single human supervisor can now execute a day’s worth of analyst work in a fraction of the time.
The shift has created what experts call the "one-generation problem." If banks automate 95% of junior work, they risk losing the training ground where future leaders develop pattern recognition and domain expertise. While law schools have already partnered with platforms like Harvey and Legora to integrate AI into their curricula, finance education has largely lagged behind, leaving students to seek out their own training in agent-based workflows.
“The entry-level jobs you had two to three years ago, AI can do most of them,” noted an attendee. For the Cornell students in attendance, the workshop was less about learning a new tool and more about survival in a restructured organization. The traditional 6:1 ratio of junior to senior bankers is already collapsing toward models where fewer, more technically adept generalists oversee vast networks of AI agents.
As the evening concluded with pizza and intense debate over the value of a modern finance degree, the message was clear. The industry isn't just looking for people who can use AI to move faster; it is looking for "systems architects" and "validators" who can build the operating models of the future. For these students, the work of redesigning their own careers has already begun.
Obin executives note that finance has nothing to prepare students for this new AI future. The profession with the highest theoretical AI task coverage has no structured program preparing the next generation to work with agents and workflows. The students who will be asked to supervise AI output at Goldman or JPMorgan in two years have, in most cases, never built or used an agent.
Obin is planning similar events at major US universities in the coming months with the same idea, to put practitioners and real AI tools in front of the students entering finance, and let them build.
