Generative AI’s Impact on Student Achievement and Implications for Worker Productivity

Naomi Hausman, Oren Rigbi and Sarit Weisburd

No 11843, CESifo Working Paper Series from CESifo

Abstract: Student use of Artificial Intelligence (AI) in higher education is reshaping learning and redefining the skills of future workers. Using student-course data from a top Israeli university, we examine the impact of generative AI tools on academic performance. Comparisons across more and less AI-compatible courses before and after ChatGPT’s introduction show that AI availability raises grades, especially for lower-performing students, and compresses the grade distribution, eroding the signal value of grades for employers. Evidence suggests gains in AI-specific human capital but possible losses in traditional human capital, highlighting benefits and costs AI may impose on future workforce productivity.

Keywords: generative AI; student achievement; worker productivity; higher education; human capital. (search for similar items in EconPapers)
JEL-codes: I23 J24 O33 (search for similar items in EconPapers)
Date: 2025
New Economics Papers: this item is included in nep-ain, nep-hrm and nep-lma
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_11843

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