Artificial intelligence is changing entry-level work around the world, with more than one in three young workers employed in occupations facing medium-to-high exposure to AI-driven task change, according to research from the World Economic Forum and PwC.
The immediate concern is job availability. But a broader problem is emerging as AI takes over routine work traditionally assigned to junior employees: how will inexperienced workers acquire the judgment, institutional knowledge and practical experience needed to become tomorrow’s senior professionals?
The World Economic Forum’s research suggests that the transition is not simply a choice between humans and automation. Companies may need to redesign entry-level work itself.
37% of Young Workers Are in AI-Exposed Occupations
The World Economic Forum and PwC examined the changing role of entry-level work through their Artificial Intelligence and the Future of Entry-Level Work report.
Globally, 37% of young workers are employed in occupations with medium-to-high exposure to AI-driven task change.
Exposure does not mean that 37% of young workers will lose their jobs. Instead, it measures how significantly AI could change the tasks performed within those occupations.
That distinction is important.
AI can automate parts of a job without eliminating the entire position. For entry-level employees, however, many of the tasks most susceptible to automation are also the tasks traditionally used to learn how an organization or profession works.
Routine research, data processing, basic coding, drafting and administrative work can give inexperienced employees opportunities to learn processes before taking responsibility for more complex decisions.
As AI handles more of that work, the first rung of the career ladder changes.
Young Workers Are Curious About AI but Worried About Security
The WEF/PwC research also found a complicated mix of optimism and anxiety among early-career workers.
Entry-level respondents reported more curiosity and excitement about AI than outright worry. According to the report, 47% described themselves as curious about the technology and 38% as excited, compared with 29% who reported feeling worried.
But optimism about AI does not remove concerns about employment.
Job security was a priority for 76% of entry-level respondents. Thirty-nine percent expected AI to improve their job security over the next three years, while 18% expected it to make their position less secure.
The findings suggest young workers are not uniformly hostile to workplace AI. Many appear willing to use the technology while remaining uncertain about how it will affect their careers.
Entry-Level Work Is Shifting From Execution to Judgment
One of the most important changes is in what employers may expect from junior employees.
If AI can produce a first draft, summarize documents, write basic code or perform routine analysis, companies can ask human employees to spend more time evaluating outputs, handling exceptions and making decisions.
That can increase productivity, but it also raises expectations.
A new employee who once learned through repetitive execution may now be expected to exercise judgment earlier in a career.
The challenge for employers is ensuring workers have enough knowledge and supervision to make those judgments well.
This is especially relevant in remote and hybrid workplaces, where informal learning from experienced colleagues can already be harder to reproduce. Gignomist’s broader analysis of remote and hybrid work and AI integration examines how technology is changing the structure of knowledge work beyond the traditional office.
Eliminating Junior Jobs Can Create a Senior-Talent Problem
The consequences may become more visible several years from now.
Entry-level positions do more than complete low-level tasks. They also create a pipeline of workers who eventually become specialists, managers and senior leaders.
That pipeline becomes vulnerable if companies automate junior work without replacing the learning that came with it.
The problem is particularly clear in software development.
In an August 2026 World Economic Forum analysis, BairesDev co-founder Nacho De Marco argued that companies still need to cultivate technical craft, domain knowledge, architecture skills and judgment even as AI performs more routine coding work.
The question is straightforward: if companies stop hiring junior developers because AI can perform basic tasks, where will experienced developers come from five or 10 years later?
Similar questions can apply to finance, consulting, law, marketing and other knowledge-intensive professions where employees traditionally learn through progressively more difficult assignments.
Hiring Decisions Matter Alongside Automation
AI’s impact on early careers also extends to the hiring process itself.
Companies increasingly use automated systems to screen, rank and assess candidates, adding another way AI can influence access to the first stages of a career.
That creates questions not only about efficiency but also about fairness. Gignomist has reported on research into bias in AI-assisted hiring, illustrating why organizations need to evaluate how automated systems affect different groups of applicants.
For young workers, AI can therefore influence both sides of the employment relationship: whether they get an opportunity and what work remains after they are hired.
Employers May Need to Redesign the First Rung
The WEF report proposes looking at the transition through four connected areas: access to jobs, the design of those jobs, talent pipelines and alignment between education and employment.
That framing matters because simply teaching workers how to use AI does not solve the entire problem.
Employers need to determine which tasks should be automated, which should remain developmental opportunities for junior staff and how inexperienced employees will acquire practical judgment.
Educational institutions face a related challenge. If workplaces expect graduates to arrive ready to supervise or evaluate AI-generated work, curricula may need to provide more opportunities for applied experience rather than focusing only on theoretical knowledge.
Workers themselves will increasingly need both AI literacy and skills that remain valuable when routine execution becomes easier to automate.
AI May Change the Career Ladder Rather Than Remove It
The evidence does not support a simple conclusion that AI will eliminate entry-level work worldwide.
It does show that the traditional structure is under pressure.
Some junior tasks will be automated. Others will be augmented. New roles will emerge around AI systems, data, cybersecurity, governance and human oversight.
The larger risk is allowing short-term productivity gains to undermine long-term workforce development.
Companies can save time when AI performs work previously assigned to junior employees. But if those companies fail to create new ways for inexperienced workers to learn, they may eventually discover that they have automated part of the process that produced their future experts and leaders.
For young workers, that makes AI proficiency important — but not sufficient. Judgment, domain knowledge, problem-solving and the ability to evaluate machine-generated work may become increasingly important precisely because AI can handle more of the routine tasks that once defined the beginning of a career.
