While the public has been debating AI’s potential impact on firms and their workers, research and data have been catching up. Our goal in this brief is to synthesize the fastgrowing body of research on AI’s impact for policymakers and others eager to understand how AI is affecting the labor market right now. For ease of exposition, we organize this empirical evidence into a set of stylized facts, as follows: AI’s impact on aggregate employment is likely small right now. A tough market for recent graduates may be partly due to AI. AI’s impact on worker productivity is mixed but generally positive. Firm adoption has accelerated but unevenly across the economy. xEarly evidence is hardly the last word on AI’s impacts. We will now explore each of these points in greater depth. AI’s impact on labor market conditions is likely small right now.
No one can predict the future, but there is little evidence that AI is causing significant job losses right now. Unemployment among workers in occupations most exposed to AIdriven disruption is rising, but not faster than among those least exposed.[2] As shown in Figure 1, the unemployment rate for the top quintile of AI-exposed workers has risen by 0.77 percentage points since 2022, while the unemployment rate for the least-exposed workers rose slightly more, by 0.85 percentage points over the same period. These aggregate trends suggest a broadly softening labor market, rather than one characterized by AIdriven job losses. There is also little evidence of AI depressing employment or job postings in the most highly exposed occupations.
Employment trends in occupations with high exposure to AI are fairly stable.[4] While employment growth in coding-heavy occupations has slowed somewhat, it remains positive. There is no evidence that AI adoption has negatively impacted firms’ job postings. Indeed, online job postings for software developers — a very highly exposed occupation — have been growing faster than for other occupations over the last year. Among firms that adopted enterprise AI, employment grew by 10 percent in the two years following adoption, an effect driven by firms with the highest per capita AI spending.[ What about the companies announcing layoffs, increasingly citing AI as a driving factor? Both industry leaders and labor economists express some healthy skepticism about these claims. While some narrow layoffs may be connected to AI-related automation, others appear driven by a desire to free up cash flow for AI investments or to reduce headcount after pandemic-era over-hiring.
Human resource executives say the impacts of AI are more evident in role consolidation and hiring avoidance in roles where AI can automate many tasks. This doesn’t mean AI isn’t having any negative impact on some workers; rather, the effects so far are more nuanced than an imminent “AI jobs apocalypse” would suggest. AI could be creating pockets of disruption that aren’t easily visible in aggregate economic data. In particular, there is some evidence that AI may be negatively affecting demand for young white-collar workers, as we discuss next. A tough labor market for young workers may be partly due to AI Recent graduates are facing the most challenging job market in years, with unemployment rates for new grads reaching 5.6 percent in early 2026, up 1.6 percentage points from three years earlier.
This rise has fueled concerns that AI is replacing many of the jobs recent graduates once sought. Junior roles often involve routine research, analysis, and writing tasks that can now largely be done with AI. Consistent with this intuition is empirical evidence that AI may be dampening demand for new hires. In a widely discussed paper, Brynjolfsson, Chandar, and Chen report a notable decline in employment among early-career workers in AI-exposed occupations, notably software developers and customer service representatives, since ChatGPT’s launch in 2022. As shown in Figure 2, by contrast, employment among older workers in those same occupations remained relatively stable or continued to grow. The authors liken these young workers to “canaries in the coal mine,” the first to experience labor market disruption from AI. Other researchers have since identified similar negative effects on the hiring of young AI-exposed workers in the U.S. and the U.K., beginning in 2022.
The timing of this impact is somewhat surprising. AI model capabilities were very limited in 2022. Other factors may be at play, including rising interest rates, pandemic over-hiring, and remote work. For example, in response to rising inflation, the Federal Reserve aggressively hiked interest rates beginning in March 2022 — several months before ChatGPT’s public release the following November. Two new papers find that hiring in AI-exposed occupations began to decline after the Fed’s monetary policy shift but before ChatGPT’s debut. Also, the rapid shift to remote work during the pandemic, which can slow on-the-job learning, erodes the value of hiring younger workers.
New evidence suggests hiring in remote-friendly occupations began to skew toward more experienced workers after the pandemic. In response to concerns about these and other possible confounding effects, Brynjolfsson and coauthors added new controls. In these results, employment declines among entry-level workers are not notable until 2024. It thus seems plausible that factors other than AI are driving declines in hiring young workers around 2022. However, by 2024, both AI adoption and model capabilities had advanced significantly, making the direct impacts of AI more plausible. Hiring of entry-level workers in AI-exposed occupations clearly declined markedly around 2022.
What is harder to determine is whether this decline constitutes clear evidence of AI’s impact on demand for young workers, now or in the future. Given other macroeconomic shocks to labor demand around this time, isolating AI’s impact is empirically challenging. This remains an open and active area of research.
