Sam Altman’s tech giant has enlisted more than 100 ex–investment bankers to help train its AI models on how to build financial models that could automate hours of entry-level tasks, according to documents seen by Bloomberg and reported Tuesday. The recruits, including former employees of JPMorgan Chase, Morgan Stanley, and Goldman Sachs, are contributing their expertise to a project code-named “Mercury,” Bloomberg reported.

But experts tell Fortune the move will likely transform rather than replace entry-level roles, a prevailing thought among economists following the AI-adoption wave.

“I’m not convinced that we get rid of entry-level workers anytime soon, but I could imagine a world where the skill set we need those entry-level workers to have is different,” Shawn DuBravac, an economist and CEO of Avrio Institute, a research and consulting firm, told Fortune.

DuBravac believes a “first wave of automation” will hit structured, repeatable tasks junior analysts spend hours during the week working on for their superiors, like cleaning and formatting spreadsheets, building financial models, and assembling pitch decks. 

Investment banking analysts regularly clock more than 80 hours a week when working on live deals, leveraging Microsoft’s Excel program to deliver financial models for mergers and leveraged buyouts. 

“These are all areas where the data is plentiful, the templates are standardized, and the process can be learned from repetition,” DuBravac said. “Within the next year, I’d expect firms will move quickly to try to automate 60% to 70% of the time analysts currently spend on these lower-level tasks.”

As routine, mundane tasks are automated and AI is more embedded into junior analysts’ workflows, senior analysts will find more “sophisticated” tasks for them to execute—like building financial models with greater complexity, or performing more quantitative analysis, which are skills they might usually learn further along in their careers—he added.

“We often overestimate how impactful some of the technology will be when it comes to eradicating work as we know it,” DuBravac said. “Just like Excel spreadsheets did back in the day, [AI] will streamline some work.”

But just 38% of organizations that use AI predict use of generative AI models will have little effect on the size of their organization’s workforce in the next three years, according to a McKinsey report published in March.

“Respondents at larger organizations, however, are more likely than others to say their organizations have reduced the number of employees as a result of time saved,” the report said.

For strategy and corporate finance, 29% of respondents predicted no change in the number of employees at their firms as a result of gen AI use, according to the report. Just under a third expect headcount reductions, and 30% predict an increase of headcount within the next three years.

“I could see headcounts staying mostly flat, but at the same time, workloads will become lighter in some areas and heavier in others,” DuBravac said.

Ram Srinivasan, managing director of consulting at JLL, a global commercial real estate and technology services company, told Fortune OpenAI’s initiative to train AI models in financial modeling represents “a natural evolution in investment banking.”

“AI will give every analyst superpowers and allow banks to compound human insight,” Srinivasan said. “Analysts become reviewers and customizers rather than builders from scratch, allowing each person to support more deals simultaneously.”

But some experts don’t share this rosy outlook. The World Economic Forum’s Future of Jobs Report revealed in January that 40% of employers expect to reduce their workforce where AI can automate tasks.

The essential-skills transfer to automation also brings into sharp focus the value of education for entry-level workers. A survey published last year by Indeed’s Hiring Lab found that roughly half of U.S. Gen Z job hunters (49%) believe AI has directly reduced the value of their higher education in the job market. But this may just mean financial firms will be looking for candidates with new skills to help support banks in a time of rapid adjustment, DuBravac said. Candidates experienced in working with AI models will help financial firms build their own products, he added.

“There could be a stronger demand for people who have a deeper expertise in AI,” DuBravac said. “You bring some of that in-house, because at the end of the day, finance is all about not just getting the right answer, but getting it more quickly than your competitors, or getting a more differentiated answer than your competitors.”