For decades, the world of high finance ran on a ritual of endurance. Thousands of Ivy-League graduates entered investment banking knowing the price of entry: 100-hour weeks, midnight Excel checks, and slow climb toward decision-making power. Today, that system is being quietly rewritten. At NewsTrackerToday, we see a new dynamic emerging: artificial intelligence isn’t just joining Wall Street – it is learning to become the junior banker itself.
Under a project codenamed Mercury, OpenAI has reportedly hired hundreds of former analysts and associates from firms like Goldman Sachs, JP Morgan and Morgan Stanley. Their task, paid at around $150 per hour, is to train AI models to perform the grinding work that once forged the industry’s future leaders – building discounted cash flow models, preparing deal decks, and assembling due-diligence analysis.
We at NewsTrackerToday view this not as a niche experiment, but as a structural signal: AI is moving from chat windows into the workflows that define global finance. It’s being trained not only to summarize meetings, but to structure valuation arguments and anticipate the formatting preferences of managing directors.
Economic analyst Ethan Cole explains: “This is not a hostile takeover of finance – it is evolution. AI absorbs the mechanical layers, while humans move faster toward judgment and capital decisions. Careers accelerate, but the skill mix changes dramatically.”
Yet the pivot raises a deeper question. Investment banking wasn’t just spreadsheets – it was apprenticeship. Analysts learned by suffering through every cell and slide. That grind created intuition: spotting inconsistencies, understanding client psychology, building muscle memory around precision. If AI takes that foundational layer, what forms the next generation of dealmakers?
As NewsTrackerToday’s technology analyst Sophie Leclerc notes, “Automation isn’t the threat – complacency is. If junior talent never learns to build the machine, they risk becoming supervisors without the instincts that only lived experience teaches.”
Reactions inside the financial community reflect this split. Some veterans say automation frees young minds for higher-value work sooner. Others warn that “checking the robot’s homework” is not training, but stagnation. Still others see poetic irony: the same industry that pushed analysts to burnout may now train the technology that replaces them.
Financial institutions argue they will still need human analysts, but in a different capacity – guiding models, validating assumptions, and applying ethical judgment. Many HR departments are already redefining entry-level roles: less midnight formatting, more decision-making supervision. A compressed learning curve, but also a steeper one.
We observe a clear theme: the future analyst isn’t just Excel-literate. They must become AI-literate – able to train, question, and refine automated systems. The hard skills arrive faster; the soft skills matter earlier. It’s not the end of banking as a career – it’s the end of suffering as training.
If Mercury succeeds, firms will restructure career ladders and competitive advantages will shift. Those who marry algorithmic precision with human intuition will lead. Finance has always rewarded speed and accuracy; AI now forces both to scale at once.
And as we frame it at News Tracker Today, AI is not here to take Wall Street. It is here to force Wall Street to evolve – faster, smarter, and with a level of accountability the old system often lacked. The grind is changing. The ambition isn’t.
