AI is changing the labor market, but not in the way many expected

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AI is changing the labor market

The disruption is showing up first among young workers

The clearest warning comes from jobs where AI can already perform a meaningful share of routine work. Stanford University's 2026 AI Index found that employment among U.S. software developers aged 22 to 25 has fallen nearly 20% since 2024, even as employment among older developers continued to grow.

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That creates a problem beyond the immediate number of jobs lost. Junior employees traditionally learn by doing simpler tasks before progressing to work that requires greater judgment and responsibility. AI can increasingly handle precisely those first assignments.

PwC found a similar shift after analyzing more than 1 billion job advertisements around the world. Entry-level U.S. roles with high AI exposure are increasingly asking for skills traditionally associated with experienced workers, including judgment, leadership and creativity.

“AI is removing some of the routine work that once acted as an apprenticeship,” said Pete Brown, PwC's global workforce leader.

If machines increasingly do the work through which beginners once gained experience, companies will need another way to produce the experienced professionals they still want to hire.

AI is changing jobs faster than eliminating them

The broader picture remains considerably less dramatic. The International Labour Organization (ILO) estimates that one in four workers globally has a job with some exposure to generative AI, but cautions that exposure should not be confused with redundancy.

Clerical jobs remain among the most exposed, but AI is increasingly reaching into skilled professions such as finance and software development. In many cases, that means changing what people do rather than removing the job altogether.

A financial analyst may use AI to produce a first draft of research but still decide whether the analysis makes sense. A software developer may generate code faster while spending more time reviewing and testing it, potentially reducing the number of people needed for some tasks without eliminating the occupation itself.

The impact will look different around the world

AI will not land in every labor market in the same way. Demographics, wages, skills and regulation all affect whether the technology is more likely to replace work or help people do it faster.

In Singapore, more than a quarter of companies now use AI, according to the Ministry of Manpower, yet only 6.2% of adopters reported reducing headcount. Companies were considerably more likely to redesign existing jobs or create new AI-related positions.

India faces a different calculation. Its technology-services and business-process outsourcing industries employ millions of people in digitally delivered work that generative AI can increasingly handle. A technology that could help aging economies cope with worker shortages may create greater pressure in younger economies that need to produce large numbers of white-collar jobs.

Europe could follow another path. Stronger employment protections may make immediate layoffs less common, with disruption appearing instead through changing responsibilities, slower hiring and fewer entry-level openings.

The divide may increasingly be about skills

AI is also creating demand for new kinds of work. PwC found that jobs requiring AI skills have grown 69% since 2019, compared with 9% across the wider job market. The bigger divide may therefore be between workers who can use AI alongside their own judgment and expertise, and those whose jobs rely heavily on tasks AI can perform cheaply.

The difficult part is getting from one group to the other. Employers increasingly want people who can supervise AI output, spot mistakes and make decisions, but those abilities usually come from experience. If companies hire fewer beginners because AI can do junior-level work, they risk weakening the pipeline that produces experienced employees later.

The first rung of the career ladder may be changing

The jobs apocalypse has not arrived. So far, much of the disruption is appearing through changing tasks, different skill requirements and pressure on particular groups rather than mass unemployment.

Young workers may be among the first to feel it because the work traditionally given to beginners is often exactly the kind AI can perform well. Companies may therefore have to rethink what entry-level jobs are for and how people learn once they get them.

What may already be disappearing is an older assumption about careers: that people enter a profession by doing its simplest work and gradually move upward. If AI takes over more of that first step, the challenge will be not only preserving jobs, but finding a new way for people to become good at them.

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