In 2026, there’s one question that keeps echoing across classrooms, offices, and group chats: Are we witnessing AI replace entry-level jobs, or are we just scared of change? The question feels very personal to us because entry-level jobs mark the transition to adulthood. Entry-level jobs include internships, graduate schemes, junior analyst roles, assistant roles, and many more. They’re the bottom rung on the ladder.
Now that generative AI can write emails, summarize meetings, create slides, respond to customer inquiries, and even write code, there’s a fear that the bottom rung on the ladder is being replaced by AI. But let’s move away from fear and take a look at the data to understand the situation better and see what it really says.
What does the research say regarding entry-level job hiring?
Research on labor markets between 2023 and 2026 indicates that the labor market may be feeling pressure on young workers in highly AI-exposed roles. A Study by the Digital Economy Lab at Stanford University indicates that employment for workers aged 22-25 years in AI-exposed roles decreased compared to older age groups in similar roles.
According to LinkedIn labor market data, entry-level hiring has slowed down more significantly compared to overall hiring after the pandemic boom. However, LinkedIn’s broader analysis indicates that it’s not entirely AI that’s to blame for this situation.
In simple terms, the numbers indicate stress in early-career hiring, especially in some fields. But they don’t indicate a catastrophic failure due to AI alone.
Where the stress seems most critical
It’s most evident in fields centered on repetitive knowledge-based work.
Advertising agencies in the UK have reported a decrease in staff numbers and a reduction in hiring younger people during the same period when AI content tools reached the mainstream. This includes entry-level positions for creative and copywriting roles, where the primary task is writing and revising.
In the consulting and professional services space, the hiring of younger people for graduate schemes has increased. This is while firms have been experimenting with AI tools to assist in their work.
In the tech space, coding assistants may write functions, test code, and even generate documentation. There are also reports of companies holding off on hiring junior developers because they see the value in hiring experienced developers with AI capabilities to produce much better results.
This may not be an isolated occurrence, and it may be part of the larger tech slowdown caused by the overhiring during the pandemic.
Transformation vs. Replacement
There is a tendency to think in binary when it comes to AI and the workforce, either it replaces jobs, or it does not. The reality seems to be a transformation.
Research from hiring platforms indicates that generative AI does not eliminate entire professions; it changes the makeup of the work.
If an entry-level employee spends 60 percent of their time drafting and 40 percent making decisions, the AI may increase the drafting time to 20 percent and the decision-making time to 80 percent.
Many junior roles were designed around “practice tasks.” Writing first drafts. Cleaning data. Preparing background research. If AI performs those tasks instantly, companies may reduce hiring or expect new hires to contribute at a higher level immediately.
This is where the phrase AI replacing entry-level jobs gets really dramatic and may not necessarily be the case.
Why the story is not entirely negative
Despite the seeming negativity, there are several large companies that are indicating they may be taking a different approach to the AI and entry-level hiring.
IBM is one such company that has made announcements regarding increasing entry-level hiring and using AI.
The reasoning behind the hiring is simple: AI creates output, but humans provide the checks and balances, the ethics, the creativity, and the responsibility.
The increased productivity does not necessarily equate to fewer workers. It can equate to more services, more markets, or more types of work. There are many historical precedents. The rise of spreadsheets replaced the traditional method of using an accounting ledger. The role of accountants did not become obsolete. It changed.
Economists have also pointed out that the long-run impact of AI depends not on the technology itself, but on corporate strategies. It depends on corporate policies. The impact depends on whether the company chooses to put its savings into growth strategies or to cut costs further. The former creates more types of work, while the latter reduces the number of new entrants to the labor market.
A simple way to look at the shift
Suppose we have a school project. Before, one student might copy information from books, another student might type the information, and another student might create slides. Now, one student can use AI to create a draft instantly. Does that mean the project needs fewer people?
Maybe. But the project still needs someone to check information, enhance arguments, create good slides, and present well. The difference is that simply copying information no longer qualifies you for a job. Thinking does.
In the workplace, the same principle applies. AI can handle the easy tasks. Humans can handle the complex ones.
The statistics suggest that in highly AI-exposed professions, new workers in the industry may be at greater risk than mid-career professionals. New workers tend to perform tasks that can most easily be automated. That is why the pressure feels concentrated at the bottom.
What the data ultimately shows
So, is the fear justified?
The data from 2023 to 2026 shows that hiring of early-stage employees in AI-saturated industries is slowing down. Some industries have seen measurable drops in early-stage employment. However, other factors affect this story, and large corporations are investing more in redesigned early-stage hiring pipelines.
The best conclusion is that AI replacing early-stage employment is partially true on a task-based level. It is partially true on an industry-based level. It is simply not true on a job-based level.
We are not witnessing the elimination of the first step of the ladder. We are witnessing it being re-engineered.
The ladder can be climbed by anyone who is willing to learn how to utilize the tools.
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