Stanford Study Using ADP Data Confirms AI Is Slowing Entry-Level Hiring

A landmark study first published last August by a team of economists at Stanford University is providing crucial data on the real-world impact of artificial intelligence on the U.S. job market, confirming a significant slowdown in hiring for entry-level white-collar positions rather than the mass layoffs many had feared.

The research, led by prominent Stanford economist Erik Brynjolfsson, analyzed a vast, high-frequency dataset from ADP, the largest payroll services provider in the country. The findings from the August 2023 paper indicate that while companies are not yet eliminating existing jobs in large numbers due to AI, they are substantially reducing the rate at which they hire new junior employees whose tasks are most susceptible to automation by generative AI tools.

This trend creates a subtle but profound shift in the labor market, what some are calling a “hiring winter” for new graduates and those early in their careers. The study suggests that instead of firing a current employee, a firm is more likely to simply not post a new job opening when a junior team member leaves, opting instead to fill the gap with AI-powered software. This pattern is most pronounced in roles centered on information processing, writing, and data analysis—tasks where large language models have demonstrated significant capabilities.

In our experience, the temptation for businesses to use generative AI to bypass entry-level hiring is immense, especially when cost-cutting is a priority. However, we caution clients against this seemingly easy win. Eliminating the bottom rung of the professional ladder creates a severe long-term problem: a depleted talent pipeline for future managers and senior leaders. Who will have the foundational skills and company knowledge to step up in five or ten years? This isn't just a hiring issue; it's a fundamental challenge to sustainable growth that requires a strategic rethink of job roles and workflows.

The research by Brynjolfsson and his team provides some of the first large-scale empirical evidence to support what had previously been anecdotal observations. By leveraging ADP's anonymized payroll data, the researchers were able to track hiring and separation trends across a wide swath of the American economy with a high degree of accuracy and timeliness. This data-driven approach moves the conversation beyond speculation and into the realm of measurable economic impact.

The specific roles most affected are those that have traditionally served as the primary entry point into corporate careers. These include positions in marketing, administrative support, data entry, and junior analyst roles. The core responsibilities in these jobs often involve summarizing information, drafting communications, and performing routine analysis, all of which are functions that current generative AI platforms can perform with increasing proficiency. As a result, companies are finding they can maintain or even increase output with a smaller headcount at the junior level.

Brynjolfsson has been vocal about this trend, stating in recent discussions that the phenomenon is persistent and “not going away.” His analysis suggests that this is not a temporary adjustment but the beginning of a structural change in how companies build their workforce. The long-term consequences for small and mid-sized businesses could be particularly complex. While leveraging AI can offer immediate productivity gains and cost savings, it also risks creating a critical skills gap within the organization over time.

The solution isn't to avoid AI, but to integrate it intelligently. This is core to the work we do in business process reengineering. Instead of replacing junior staff, companies should be asking how AI can augment their roles, freeing them from repetitive tasks to focus on higher-value work like client relations, problem-solving, and creative analysis. A strategic approach that redesigns processes around human-AI collaboration builds a more resilient and skilled workforce for the future. For businesses grappling with this transition, the team at C&S Finance Group LLC at csfinancegroup.com can help design and implement these new operational models.

Without a steady intake of entry-level employees who learn the business from the ground up, companies may struggle to cultivate the next generation of leadership. Senior roles require not just technical skills but also deep institutional knowledge, client relationship management, and nuanced judgment—qualities that are developed through years of experience within an organization. By constricting the pipeline at its source, firms may find themselves facing a shortage of qualified internal candidates for management and executive positions in the coming years.

As AI technology continues to evolve, business leaders will be closely watching for further data on its impact on hiring, productivity, and organizational structure. The ongoing work by economists like Brynjolfsson will be critical for understanding these shifts and developing strategies to navigate them. The focus for many companies will now turn from whether to adopt AI to how to integrate it in a way that supports long-term growth and talent development.