
Primary workers saw job-finding rates drop 13 points since Nov 2022; the Richmond Fed ties the slide to AI exposure, and July payrolls stayed negative.
Job-finding rates, the share of unemployed workers who land a new job within a month, have fallen further for America's most reliably employed workers than for any other group in the labor market, according to a new Federal Reserve Bank of Richmond analysis. The old rule, that people who always have a job can always find one, no longer holds.
'Primary workers,' about 55% of the US labor pool, are 'almost always employed,' per the analysis. They have steady work histories and usually appear in unemployment statistics only when something has gone wrong. Historically, they had the best odds of finding a new job. Between a November 2022 high and a September 2025 low, their job-finding rate dropped 13 percentage points, the steepest decline for any category the study covered.
Secondary workers, roughly 14% of the labor pool, are often out of work or cycling between jobs. They account for most of measured unemployment, and their job-finding rate is lower in absolute terms. Over the same window, that rate fell two percentage points, a fraction of the primary worker decline. The gap between the groups has narrowed.
This pattern is new. In past major recessions, primary workers saw the biggest job-finding declines, followed by secondary workers. This time the most attached group took the larger decline, and less attached workers barely moved. The report flags the timing as a puzzle: the US economy was growing through most of the period.
Richmond Fed researchers identify AI exposure as the dividing line. They define exposed roles as jobs whose tasks overlap with capabilities listed in AI patents, using patent records to measure what AI systems can do. Before 2023, the year ChatGPT became publicly accessible, job-finding rates for roles at every level of AI exposure moved together. Since then, the analysis found, outcomes for AI-exposed fields worsened sharply.
The report also looks at how AI has changed hiring for workers who might otherwise become strongly attached to the job market. Research cited in the report finds generative AI can 'substantially increase productivity at the task level (particularly for less-experienced workers), potentially altering the composition of new hiring.' For entry-level workers, the analysis says, the productivity shift means a tighter market where roles demand a wider variety of skills.
Experienced white-collar workers in AI-exposed occupations have responded with drastic measures, including pay cuts, the report said.
White-collar sectors held up in July's employment report. Professional and business services added payrolls, and the information sector did too. Those gains were not enough to offset losses elsewhere. The US lost jobs overall in July.
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