AI's Real Labour Market Hit: Entry-Level Workers Face 16% Employment Decline in High-Exposure Roles
New research reveals AI is reshaping jobs faster for young workers, with employment falling 16% in early-career software and support roles since ChatGPT's launch.
AI’s Real Labour Market Hit: Entry-Level Workers Face 16% Employment Decline in High-Exposure Roles
Key Developments
Recent research has identified a stark pattern in how AI is reshaping employment: while headlines warn of mass job losses across the economy, the real disruption is hitting a specific group—young workers trying to launch their careers.
Using granular payroll data from millions of workers across thousands of private companies, researchers at Stanford’s Digital Economy Lab found that employment for workers aged 22 to 25 in high-AI-exposure roles fell 6% between late 2022 and July 2025. For software developers specifically, the decline reached nearly 20% from its late-2022 peak. Yet in the same roles, employment for workers aged 30 and older grew between 6% and 13%.
A separate analysis from Stanford published in November 2025 identified a 16% decline in early-career employment across the most AI-exposed occupations since ChatGPT’s release. The disruption is concentrated in roles like software development and customer support—precisely the entry-level positions that traditionally serve as training grounds for new professionals.
Industry Context
This pattern contradicts the “AI will eliminate all jobs” narrative. Aggregate unemployment remains near historic lows at around 4%. The broader labour market has shown surprising resilience, with data painting a picture of a relatively stable labour market in which AI disruptions remain largely speculative.
However, the data reveals something more nuanced and concerning: when AI can perform most tasks in a particular job, the share of people in that role within a company falls by about 14%, but when AI’s impact is concentrated in just a few tasks within a role—leaving other responsibilities untouched—employment in that role can grow.
From a European perspective, the European Training Foundation emphasises that job transformation outweighs job loss, and countries with strong labour protections, effective social dialogue and forward-looking skills policies are better equipped to steer AI towards job upgrading rather than job erosion.
Practical Implications
For builders and organisations deploying AI, the message is clear: task-level automation doesn’t equal wholesale job elimination. The challenge lies in how you implement the technology. Firms adopting AI to augment workers rather than replace them are seeing productivity gains translate into sustainable employment.
For job seekers and educators, the urgency is different. Entry-level positions in AI-exposed fields are vanishing as a pathway into the profession. Graduates in computer engineering, graphic design, and software development face significantly higher unemployment rates than their peers in less-exposed fields.
For European policymakers, this underscores why sustained investment in digital and AI literacy, targeted upskilling and reskilling, and social protection systems that can adapt to changing forms of work matter more than ever.
Open Questions
What remains unclear is whether this pattern is temporary—a transition period as firms reorganise workflows—or structural. Will firms eventually hire entry-level workers again, or will AI reshape career progression entirely? How can Europe’s labour protections and social dialogue mechanisms prevent widening inequality as AI tends to amplify existing labour market inequalities, with education remaining the strongest predictor of who benefits, while workers with limited digital skills or lower incomes face higher risks of job degradation?
The full impact will likely take years to materialise, but the window to shape how AI integrates into the workforce—and who benefits—is closing fast.
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