Generative AI is already reshaping the U.S. labor market by reducing job opportunities for young workers in entry-level roles, according to a new study from Stanford University. Published this week, the research presents the first large-scale evidence that AI technologies are having a measurable and disproportionate impact on early-career employment.
The study, conducted by Erik Brynjolfsson, Bharat Chandar and Ruyu Chen of Stanford’s Digital Economy Lab, analyzed anonymized payroll data from ADP covering millions of workers across thousands of companies between late 2022 and mid-2025. The findings reveal that workers aged 22 to 25 in occupations highly exposed to generative AI, such as software development and customer service, experienced a 13 percent decline in employment compared to older counterparts in the same roles. In some models, the figure reached 16 percent.
The researchers identified generative AI as the key factor behind the employment drop. As companies adopted AI tools like chatbots, large language models and code generation platforms, many entry-level tasks traditionally assigned to junior employees were automated. The study ruled out other possible causes, including macroeconomic conditions, remote work trends and company-specific factors, concluding that AI implementation aligned directly with the decline in early-career hiring.
Notably, the impact was concentrated on the number of available jobs rather than on wages. Average compensation for these roles remained stable across all age groups, suggesting that companies are eliminating positions rather than reducing pay. By contrast, more experienced workers and employees in less AI-exposed sectors such as healthcare and education saw no comparable job losses and in some cases experienced growth in employment.
Young US workers face steep job losses due to AI
The study also differentiated between roles where AI augments human capabilities and those where it replaces them. Jobs involving collaboration with AI systems showed greater resilience, while roles defined by routine, automatable tasks were more likely to disappear. This pattern underscores how the way AI is deployed either as a support tool or as a substitute shapes its impact on employment.
The authors described young workers as “canaries in the coal mine,” signaling early warning signs of how generative AI may restructure traditional career pathways. Without entry-level roles to build experience, future professionals may face obstacles to advancement, posing challenges for workforce development and long-term economic mobility.
Publicly available job listing data supports the payroll findings, with fewer junior-level positions posted in AI-sensitive fields. The trend suggests that if entry-level positions continue to erode, the training ground for the next generation of skilled workers could narrow significantly, leading to structural changes in labor market dynamics.
Entry-level employment no longer shielded from disruption
The researchers called on employers, educators and policymakers to adapt to the rapid integration of AI by rethinking hiring practices and aligning training programs with the changing demands of the digital economy. They emphasize the need for proactive strategies that ensure early-career workers remain part of the evolving labor force rather than being displaced by emerging technologies.
The Stanford study provides clear empirical evidence that generative AI is not a future disruptor but a current force already reshaping access to employment. Its effects are most visible at the entry level, raising urgent questions about how businesses and institutions will respond to protect and prepare the next generation of workers. – By Content Syndication Services.