Goldman Sachs expects new hires to manage AI agents from their first day
Goldman Sachs is preparing for a major shift in how entry-level finance jobs work. Instead of spending their early careers only building spreadsheets, checking numbers, and preparing presentations, new employees may now be expected to supervise AI agents from the moment they arrive.
Kevin Sneader, Goldman Sachs’ Asia-Pacific chief excluding Japan, said at the Milken Institute Asia Summit in Singapore that young employees joining the bank are already stepping into roles where they “manage agents.” In other words, their first team may not be made up of analysts or associates, but a collection of AI tools designed to handle repetitive and time-consuming tasks.
The comment points to a fast-changing reality on Wall Street: artificial intelligence is no longer just a back-office experiment. It is becoming part of the daily workflow, even for junior staff. For a company like Goldman Sachs, the appeal is clear. AI agents can help employees analyze information faster, automate routine work, draft materials, and potentially improve productivity across teams.
But the shift also raises a bigger question: what happens to the traditional career ladder in investment banking?
For decades, junior bankers learned the business by doing the groundwork. They built financial models, reviewed data, prepared pitch books, checked calculations, and spent long hours learning the small details that shape major financial decisions. That process was demanding, but it also created the foundation for future bankers, dealmakers, and managers.
If AI agents now perform much of that work, young employees may move more quickly into supervisory roles. They will need to know how to give instructions, review AI-generated output, identify mistakes, and decide when human judgment is required. That sounds efficient, but it creates a challenge: how can someone confidently review complex work if they have not spent years learning how to do it manually?
This is one of the biggest unanswered questions in the growing use of artificial intelligence in finance. AI can process large amounts of information quickly, but it can still make errors, miss context, or produce results that look convincing while being incorrect. In investment banking, where accuracy matters, employees must be able to catch those mistakes before they become costly problems.
The change could also put pressure on middle management. If junior employees are managing AI systems from day one, the role of managers may evolve. Instead of overseeing teams that handle basic execution, managers may need to focus more on strategy, risk control, client relationships, and training employees to use AI responsibly.
Goldman Sachs is not alone in exploring the productivity benefits of AI. Across industries, companies are using artificial intelligence to automate tasks, reduce costs, and speed up decision-making. Some businesses have even pointed to AI efficiency as a reason for cutting jobs. However, the economics are not always simple. Running advanced AI systems can be expensive, and some companies are discovering that automation does not always replace human labor as cheaply or effectively as expected.
For banks, the stakes are especially high. Financial work depends on trust, precision, and experience. AI may be able to accelerate analysis, but it cannot fully replace the judgment that comes from years of working through complex deals, market cycles, and client demands.
The future of entry-level finance jobs may therefore look very different. New hires at Goldman Sachs and other major firms may need to combine technical fluency with traditional financial knowledge. They will not only be expected to understand banking, but also how to direct AI tools, evaluate their output, and recognize when something does not add up.
That could make junior roles more powerful and more demanding at the same time. Instead of simply completing assigned tasks, young professionals may become coordinators of automated workflows. The best performers may be those who can use AI to move faster without losing the discipline and skepticism that finance requires.
Still, the long-term question remains: will this new model produce better bankers, or will it create a generation of employees who know how to manage software but lack deep hands-on experience?
Goldman Sachs’ approach signals where the financial industry may be heading. AI agents are becoming part of the workforce, and even entry-level employees are being asked to adapt. The firms that succeed will likely be the ones that find the right balance between automation and human training.
AI may change the first day on the job, but it cannot remove the need for expertise. For young bankers, the challenge will be learning faster than ever while making sure they still develop the judgment that no machine can fully provide.
