Goldman Sachs Group Inc. released a comprehensive research report on April 17, 2026, detailing the specific labor market consequences for workers displaced by artificial intelligence. The study, authored by a team led by Chief Economist Jan Hatzius and economist Joseph Briggs, finds that individuals who lose their positions due to AI automation face a more difficult path to financial recovery than those laid off for cyclical or structural reasons unrelated to technology.
According to the report, workers displaced by AI-driven automation experience an average 15% reduction in earnings upon re-employment. This wage scar is notably deeper than the 8% average pay cut observed among workers who lose jobs due to general business closures or downsizing. Furthermore, the Goldman Sachs data indicates that these individuals face a 25% slower rate of wage growth in the three years following their return to the workforce, as their previous skill sets often command less value in an increasingly automated environment.
The research highlights that the duration of unemployment for AI-displaced workers is significantly longer than the historical average for displaced labor. On average, it takes these individuals 8.4 months to secure a new full-time position, compared to 5.2 months for workers displaced by non-AI factors. Goldman Sachs attributes this discrepancy to a skills mismatch where the specific cognitive or administrative tasks previously performed by the worker are now handled by generative AI systems, necessitating a more intensive and time-consuming retraining period for the individual to remain competitive.
Joseph Briggs noted in the report that while AI continues to drive aggregate productivity gains across the broader economy, the microeconomic impact on individual workers is characterized by persistent earnings losses. The study tracked employment data across several high-exposure sectors, including administrative support, legal services, and financial operations. In the legal sector, for example, paralegals and legal assistants displaced by AI-assisted document review and contract analysis tools saw a 20% drop in starting salaries in their subsequent roles.
The report also analyzed the effectiveness of corporate severance and retraining programs currently in place. Goldman Sachs found that while 45% of large-cap companies have implemented AI-specific transition policies, only 12% of displaced workers successfully transitioned into higher-paying technical roles. The majority of re-employed workers moved into service-sector positions with lower baseline pay. This research follows Goldman's earlier projections regarding the automation of 300 million full-time jobs globally, though the April 17 report focuses specifically on the quality of labor reallocation rather than the total quantity of jobs lost.