Goldman Sachs executive warns AI is weakening “thinking” skills, citing declines in junior hiring

Goldman Sachs is drawing attention to a growing concern in finance and other knowledge-based industries, that AI is not only automating tasks but also affecting how people build core judgment skills. In comments reported by Yahoo Finance, a Goldman Sachs executive argued that AI is eroding bankers’ ability to “think,” and that the impact can be seen in how younger workers are being hired and employed in fields most exposed to AI.

The executive’s warning is tied to hiring data that, according to the report, shows employment among younger workers in AI-impacted industries has fallen in recent years. The implication is that, even if AI helps produce outputs faster, it may reduce the amount of supervised, hands-on learning that typically happens when junior employees take on progressively more responsibility.

Goldman’s statement comes as banks and other professional services firms have accelerated the deployment of AI tools for tasks ranging from research support to document handling and internal workflow automation. For junior staff, those tools can shorten cycles and reduce repetitive work. But they also raise questions about what gets left for entry-level employees to practice, particularly when AI can perform parts of a task without the same human trial-and-error.

From a workforce-management standpoint, the report’s focus on “junior hiring data” highlights a tension: employers want to remain competitive with AI-enabled productivity, yet they also depend on early-career development pipelines to supply future analysts, managers, and dealmakers. If fewer juniors are hired or if junior roles are redesigned around AI-assisted workflows, firms may need new training programs to recreate the learning benefits of traditional apprenticeship-style work.

For finance sector employers more broadly, the debate is not only about hiring volumes but also about role structure. AI exposure can change entry-level work in ways that make learning less visible, because outputs may be produced with less incremental work by the junior staffer. The reported comments suggest Goldman sees this as a risk to skill formation, not just a staffing issue.

The company did not provide, in the Yahoo Finance report as summarized by its headline, specific internal metrics such as Goldman’s own junior hiring numbers, pass-through training costs, or detailed evidence about which roles are most affected. It also did not lay out a specific policy response, such as mandatory training time, redesigned apprenticeship steps, or AI-use constraints for junior staff, at least within the information reflected in the published post’s framing.

Still, Goldman’s message points to an emerging managerial challenge for AI adoption in high-complexity services: the firm must balance productivity gains against the development of independent reasoning. If organizations increasingly rely on AI outputs for first drafts, summaries, or analytic scaffolding, they may need to invest more deliberately in exercises that require juniors to demonstrate their own logic rather than merely validate machine-assisted results.

What to watch next is whether Goldman, and other large financial firms, adjust their onboarding and training to ensure that junior workers practice judgment under uncertainty. Analysts and industry observers will likely look for disclosures or policy shifts around junior development, hiring plans in AI-impacted functions, and how banks measure whether AI-assisted workflows are strengthening or weakening core thinking skills over time.