Goldman Sachs study says AI-driven job losses are hitting entry-level workers hardest

Entry-level workers appear to be feeling the hardest squeeze from automation, according to a study discussed in recent reporting that cites Goldman Sachs research. The analysis suggests that while AI-related changes are affecting employment broadly, the impact is more concentrated among roles typically held by less experienced workers.

In the U.S., the report highlighted call-center work as a bellwether for that shift. It said call center positions were running 39% below their historical trend, a sign that tasks commonly handled through customer service workflows are among the most exposed to automation and AI-enabled tools.

The pattern, as described in the coverage, centers on the entry-level end of the workforce rather than higher-seniority roles. That matters because entry-level jobs often serve as stepping stones for people early in their careers, and layoffs or hiring slowdowns in those positions can ripple into broader labor-market momentum.

The reporting frames the findings as part of a larger “AI squeeze,” meaning the dual forces of productivity gains and changing job requirements that accompany adoption of AI systems. In that context, call-center work is portrayed as particularly vulnerable due to the repetitive, scripted nature of many customer interactions.

Goldman’s study, as summarized, implies a mismatch between which jobs are being reduced and what workers are able to move into next. When automation concentrates on entry-level tasks, displaced workers may face longer job searches or require retraining, especially if hiring elsewhere also slows during periods of economic uncertainty.

For Goldman Sachs, the research also fits into a broader effort by Wall Street firms to quantify how AI is reshaping industries. Such work is often used to inform economic outlooks and sector perspectives, and it can influence how investors think about labor costs, productivity, and demand for different types of skills.

That said, the coverage does not provide the full methodological details or time horizon of the Goldman Sachs analysis. It also does not specify which AI systems or workplace technologies were directly responsible for the call-center employment gap, nor does it disclose whether the 39% figure reflects net job losses, reduced hiring, or both.

What to watch next is whether Goldman, or other researchers, publish more granular breakdowns on occupations, regions, and time periods, and whether employers shift from shrinking call-center staffing to redeploying workers into different customer-facing roles that require new skills. The labor-market impact may become clearer as companies report how AI is changing day-to-day work and employment practices.