TY  - RPRT
        AU  - Westby, Samuel
AU  - Modestino, Alicia Sasser
AU  - Cheng, Peiran
        TI  - Generative AI and the Redefinition of Entry-Level Software Work
        PY  - 2026/Jun/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 18723
        UR  - https://www.iza.org/publications/dp18723
        AB  - Generative AI may change how firms define occupations. We study this process in software development, where large language models overlap with tasks commonly assigned to junior workers. Using the near-universe U.S. online vacancy data from Lightcast, we examine how the public release of ChatGPT changed entry-level software hiring standards. Event-study and difference-in-differences estimates show a 14–15 percent relative decline in junior versus senior software developer vacancies, larger than in related technical occupations and absent in mechanical engineering. A shift-share decomposition shows that rising experience requirements were driven primarily by employers asking for more experience within the same job titles, not by asking for a different composition of titles. Remaining junior vacancies shifted toward problem solving, communication, and attention to detail, not AI-specific skills. The results show how generative AI redefines entry-level work by raising the bar for what counts as a qualified junior hire.
        KW  - generative AI
KW  - economics of information systems
KW  - labor demand
KW  - job vacancies
KW  - hiring standards
KW  - entry-level work
        ER  -