Goldman CEO says entry-level hiring may contract
Business Insider reports that Goldman Sachs CEO David Solomon told Bloomberg's "Odd Lots" podcast that the bank's out-of-school hiring could "contract a little" over the next three years as AI changes the talent mix, while adding, "We're still going to hire a lot of people out of school." Per Business Insider, Solomon said Goldman expects to bring on an estimated 2,400 to 2,500 interns this year and a similar number of permanent new hires starting in July, roughly in line with pre-COVID levels but below the more than 3,000 hires in 2021. He also described "subtle, subtle changes" toward more engineering talent since before ChatGPT. Bloomberg, which hosts the podcast, framed the remarks around AI potentially halting the steep rise in banks' engineer ranks.
What happened
Business Insider reports that Goldman Sachs CEO David Solomon, speaking on Bloomberg's "Odd Lots" podcast, said the firm's entry-level hiring may "contract a little" over the next three years as AI reshapes the talent mix. Solomon is quoted adding, "We're still going to hire a lot of people out of school." Per Business Insider, he said Goldman expects roughly 2,400 to 2,500 interns this year, with a similar number of permanent new hires starting in July, which the article characterizes as in line with pre-COVID levels and below the more than 3,000 hires in 2021. Solomon also described "subtle, subtle changes" in the new-hire mix and a multi-year shift toward more engineering talent.
Corroboration
Bloomberg, which produces "Odd Lots," reported the same appearance under the framing that AI may halt the steep rise in banks' engineer ranks. Secondary coverage of the podcast emphasized Solomon's view that AI will drive productivity gains while requiring workforce adaptation, and that the firm intends to "apprentice and teach people" rather than simply cut roles. Solomon has repeatedly pushed back on AI "job apocalypse" narratives in earlier appearances.
Editorial analysis, industry pattern
As a generic trend, organizations scaling AI tools often shift the entry-level mix toward software, data, and automation-capable roles. Early-career programs increasingly expect programming and data literacy alongside domain fundamentals, and firms that operationalize AI tend to emphasize reproducible data pipelines, MLOps practices, and code review, raising demand for engineering-adjacent junior hires. These are sector patterns rather than stated Goldman policy.
What to watch
- •Whether Goldman or peers disclose role-level breakdowns for graduates and interns in coming recruiting cycles.
- •Job postings or programs signaling expanded early-career training in software, data, or MLOps skills.
- •Changes to starting roles or promotion tracks that reflect higher technical expectations.
For practitioners, internship project descriptions and entry-level role requirements will signal how AI tooling is reshaping day-one expectations more clearly than headcount totals alone.
Scoring Rationale
A bellwether bank CEO publicly signaling that AI may modestly shrink and re-skill entry-level hiring is a notable, widely covered data point in the AI-and-jobs debate, corroborated by Bloomberg's own reporting on the same podcast. It matters to recruiters, early-career candidates, and teams running hiring and training, but the remarks are hedged commentary rather than an announced structural change. Scored as solidly notable, trimmed slightly from the original to reflect the conditional framing.
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