KI- und Einstiegsjobs

Entry-level jobs are exposed because of what they contain. Junior staff in fields like software, marketing, customer support, law and finance often do the most codified, well-documented tasks: first drafts, research summaries, formatting, basic analysis and simple code. Generative AI is good at many of these. The hiring data is early but worth taking seriously. A 2025 working paper from Stanford's Digital Economy Lab by Erik Brynjolfsson and colleagues used payroll data from ADP. It reported that since late 2022, employment for workers aged 22 to 25 in the most AI-exposed occupations fell by roughly 13 percent relative to less-exposed groups, while older workers in the same occupations held steady or grew. The declines were concentrated where AI tends to automate tasks rather than augment people doing them. Caveats matter. Higher interest rates, a correction after pandemic-era over-hiring and tech-sector layoffs happened over the same period, and researchers disagree about how much each factor contributed. The effects also vary a lot by occupation. The deeper concern is the apprenticeship problem. If organizations automate the tasks juniors learned on, fewer people build the judgment that senior roles require, and the pipeline of future experts may shrink. For new graduates, practical strategies include: - Becoming fluent with AI tools while showing the domain judgment to review their output. - Building portfolios that show verified, explained work. - Pursuing internships and apprenticeships. - Targeting roles that combine AI-assisted tasks with client contact, physical work or accountability. One misconception is that AI has eliminated entry-level work across the board. The evidence points to uneven pressure concentrated in specific occupations, not a universal collapse.