UBS adds AI skills as a hiring requirement for entry-level bankers

The bar is more specific than it might sound. Simply having tried ChatGPT won't cut it. Candidates need to be able to explain what task they were working on, what they fed into the AI, and how the outcome improved as a result. Interviews will include questions probing exactly which tools were used and how.

To put it plainly, junior bankers are the entry-level staff who typically handle gathering data, checking numbers, and building presentation materials. That's precisely the list of tasks AI is currently taking over fastest.

The requirement doesn't stop at the hiring bar. UBS will also put new hires through what it calls an "AI Fluency Pathway" — a staged training program covering how AI is used in banking work and how to use it responsibly.

The intent behind this design is clear. UBS isn't looking for fully formed experts on day one — it's looking for people ready to learn. The bank has said AI proficiency isn't meant to replace academic performance or interpersonal skills, but to sit alongside them as an additional criterion.

Spain's Santander is also requiring a high level of AI competency for some of its trainee hiring. This isn't one bank experimenting — it looks like an industry-wide shift in standards.

Put simply, what this requirement actually screens for isn't experience using tools — it's the ability to explain your work. Candidates need to be able to describe, as a single concrete example, what task they were assigned, what materials and conditions they fed into it, and specifically how the output differed from before.

For applicants, this changes how to prepare. A list of models you've tried carries less weight than a single detailed account of carrying one task from start to finish with AI as part of the process.

That's also why the bank built this requirement into the hiring stage rather than leaving it to onboarding. Tool skills can be taught after hiring, but the judgment needed to break down a task, delegate it, and check the results is something the bank apparently believes is faster to assess during recruitment itself.

Looked at industry-wide, this move runs in a different direction from the prevailing trend. Until now, banks have mostly responded to AI by shrinking entry-level hiring. JPMorgan's Jamie Dimon has said AI has cut staffing by 30-40% in some divisions, and European banks have been trimming graduate hiring for several years running.

UBS is taking a different path. It's keeping graduate hiring intact while raising the bar to get in. Rather than eliminating entry-level roles, it's redefining what those roles actually do.

That comes with its own risk. JPMorgan's Conor Hillery has warned that junior staff who skip the fundamentals may never develop the instinct for digging into a problem. When AI writes the first draft, everything junior employees used to learn by writing that draft themselves disappears along with it.

The same logic is about to land in Korea's job market. It won't be enough for applicants to write in a cover letter that they're good at using AI — they'll need to be able to explain, in a paragraph, what task they applied it to, what materials they used, and how much the result improved.

For anyone preparing now, the thing to do is keep records. Whether it's a school assignment or internship work, documenting the before-and-after of a task done with AI turns directly into an interview answer. Being able to walk through one example in full detail matters far more than memorizing a list of tool names.

Companies face a different kind of homework. If they demand AI proficiency from entry-level hires without also designing foundational training alongside it, they risk creating a generation that has to review first drafts without ever having learned how to write one.