Will AI Replace Entry-Level Jobs?

Not across the board, and not all at once. But AI may make entry-level work harder to get before it visibly reduces the number of people already employed. The strongest early signal is not mass AI-driven layoffs. It is weaker hiring for young workers in some occupations with many repeatable digital tasks.

A layoff is visible: a company announces it, people leave, and the news is easy to count. A job that never opens is much harder to see. An employer can post fewer junior roles, leave departures unfilled, or let an experienced employee using AI handle work that once helped train a newcomer.

That does not mean AI has already replaced entry-level workers. It does mean that it can quietly remove the first rung of a career ladder without producing a headline about a reduction in force.

The U.S. has the clearest early warning sign

A Stanford Digital Economy Lab analysis of anonymized payroll data found no evidence of economy-wide AI displacement. However, employment among workers ages 22 to 25 in the most AI-exposed occupations was 19% below the level expected if it had kept pace with less-exposed groups.

The important detail is how that gap appeared. Stanford found that it was driven primarily by reduced hiring, not by an increase in separations. Young people were not necessarily being laid off from existing jobs. They were finding it harder to get a first job in areas such as software development, customer service, clerical work, and other digital roles. Read the Stanford analysis.

At the same time, the broader U.S. labor market does not show a national layoff surge. The latest JOLTS release reported 1.6 million layoffs and discharges, or 1.0% of employment, in August 2026. See the BLS data.

That combination is consistent with an early labor-market effect: AI can change who gets hired before it produces a visible drop in total employment.

Canada shows how the entry point can narrow

Statistics Canada found that, by the third quarter of 2025, vacancies for coding-intensive jobs requiring three years of experience or less had fallen about 60% from their late-2022 level. Vacancies for comparable jobs requiring more experience fell about 30%. In other occupations, vacancies requiring less experience declined by roughly 45%, compared with about 20% for positions requiring more experience.

This is a striking pattern, but it is not proof that AI caused it. Statistics Canada explicitly cautions that the drop may also reflect a correction after the 2021–22 hiring boom in software roles. Read the Statistics Canada analysis.

The United Kingdom shows a different stage of adoption

In the United Kingdom, around 35% of businesses with 10 or more employees reported using at least one AI technology in June 2026, up from about 12% in late 2023. Yet most adopters reported no change in overall headcount. Fewer than 7% of medium-sized businesses reported a reduction, while around 10% of businesses said they were automating or replacing roles.

Training existing staff is currently more common than external hiring or large-scale restructuring. Read the Office for National Statistics report.

What this does not prove

Weak entry-level hiring is not automatically an AI effect. Young workers are usually hit first when the economy slows, and AI-exposed sectors such as technology, finance, and professional services are also highly sensitive to interest rates and business cycles. OECD analysis found no clear break in U.S. junior job-posting trends that can be confidently tied to widespread LLM use. Read the OECD Employment Outlook 2026.

AI Caver take

The immediate risk is not that AI suddenly replaces every junior worker. It is that companies cut too many entry points without building new ones: AI-assisted apprenticeships, supervised work, review processes, and a clear path from basic tasks to independent judgment.

If the first rungs disappear, employers may eventually face a more serious problem: where will the next generation of experienced professionals learn the work?

Read the full research

For the broader question of where AI is genuinely changing workforce decisions and where companies may be using it as a convenient explanation for restructuring, read Are AI Layoffs Real — Or Just a Convenient Excuse?.