The advancement of generative AI over the last 5 years has taken the labor market by storm. Initially, the debate in the academic and practitioner community focused on which occupations were most likely to be displaced by the new technology. More recently, the discussion has shifted to which class of workers is most likely to be affected, as AI is more likely to replace specific tasks than entire occupations. This shift has important implications for one group in particular: recent college graduates.
A Changing Starting Point for New Graduates
Historically, college graduates have enjoyed lower unemployment rates than their non-degree peers. That advantage, however, has eroded in recent years. Since the late 2010s — and more sharply after 2023 — unemployment rates for recent graduates have risen to levels comparable with those of the same age group without a college degree (see Figure 1).
Note: Rates are seasonally adjusted and smoothed with a three-month moving average. Shaded areas indicate recessions.
It is difficult to attribute this trend solely to generative AI. Research on AI and labor markets is too new to determine conclusively that generative AI is behind this trend.[1] Moreover, the trend started before major LLM (Large Language Model) software became popular. However, it is not far-fetched to speculate that entry-level jobs, which often focus on routine tasks, are more susceptible to replacement by generative AI, thereby reducing demand for younger workers with limited experience. AI could support senior positions, making them more productive, at the expense of those in the early stages of their careers. Therefore, AI may have contributed to accelerating an underlying trend.
The Disappearing Entry-Level Role
Inspection of real-time job postings on our JobsEQ platform seems to corroborate this displacement hypothesis. When looking at job posts for bachelor's degree-level positions that explicitly or implicitly did not require prior experience (a proxy for entry-level jobs),[2] we observe a steady decline in the share of advertised positions. The share of entry-level position ads has dropped by 40% since the summer of 2023.
The Experience Paradox
Entry-level jobs are critical stepping-stones in developing career pathways. They also represent an opportunity for recent college graduates, who often lack practical know-how, to apply what they learned in the classroom. If AI continues to replace these positions, will this trend create a transition cliff as people in senior positions exit the market?
The demand for entry-level jobs will never disappear, but it will slow down and change in nature. If tasks such as coding, data cleaning, and report drafting are to be replaced by AI technologies, entry-level jobs will focus more on higher-level competencies that enable immediate supervision or that complement these tasks. A successful candidate will have to possess this expertise before starting the job, placing additional pressure on educational institutions to prepare a new workforce that can begin working alongside AI on day one.
The good news is that the career progression of new young workers will probably accelerate, as they benefit from increased productivity from AI technology and can advance quickly to more experienced positions. The shorter duration of entry-level jobs may counter some of the decline in demand for entry-level positions, but it will have important implications for inequality, with some inexperienced workers unable to find employment while others quickly advance in their careers. A potential additional risk of this emerging trend is that frustrated young workers who cannot find employment in their field of study may eventually seek employment in other fields, creating a mismatch between formal education and career opportunities.
Implications for Education and Policy
A final consideration may help explain the recent weakness in entry-level hiring. The current situation may be temporary due to the lag with which higher education institutions adjust curricula to changing technological demands. Job postings suggest that some employers have reduced hiring for traditional entry-level roles, particularly in occupations where generative AI can perform routine analytical or administrative tasks. This decline may reflect not only technological substitution but also a temporary mismatch between the skills graduates possess and those employers increasingly require in an AI-augmented workplace. Colleges and universities often take time to revise curricula, integrate new technologies into coursework, and develop programs that emphasize applied AI literacy and data competencies. As educational institutions adapt and graduates enter the labor market with skills better aligned with evolving workplace technologies, entry-level hiring may recover, albeit with roles that emphasize oversight, interpretation, and integration of AI tools rather than the routine tasks that once characterized many early-career positions.
In conclusion, AI adoption may reinforce a longer-term shift in which firms rely less on internal training and increasingly expect workers to arrive with job-ready skills, placing greater pressure on educational institutions and workforce systems to prepare graduates for rapidly evolving technologies. Recent policy changes linking federal student loan eligibility to graduate earnings may intensify pressure on higher-education institutions to align curricula with evolving labor market demands.[3]
[1] https://www.piie.com/blogs/realtime-economics/2026/research-ai-and-labor-market-still-first-inning
[2] If a job ad does not mention prior experience requirements, it is assumed that, implicitly, this is an entry-level position. The idea is that if experience was relevant for the position, it would be noted in the ad.
[3] https://www.aei.org/education/low-earning-degrees-will-soon-lose-access-to-federal-loans-is-yours-on-the-list/
By Dr. Francesco Renna
