Daniotti, Simone and Wachs, Johannes and Feng, Xiangnan and Neffke, Frank (2026) Who is using AI to code? : Global diffusion and impact of generative AI. SCIENCE, 391 (6787). pp. 831-835. ISSN 0036-8075
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Abstract
Generative coding tools promise big productivity gains, but uneven uptake could widen skill and income gaps. We train a neural classifier to spot AI-generated Python functions in over 30 million GitHub commits by 160,097 software developers, tracking how fast, and where, these tools take hold. Currently AI writes an estimated 29% of Python functions in the US, a shrinking lead over other countries. We estimate quarterly output, measured in online code contributions, consequently increased by 3.6%. AI seems to benefit experienced, senior-level developers: they increased productivity and more readily expanded into new domains of software development. In contrast, early-career developers showed no significant benefits from AI adoption. This may widen skill gaps and reshape future career ladders in software development.
| Item Type: | Article |
|---|---|
| Subjects: | H Social Sciences / társadalomtudományok > HB Economic Theory / közgazdaságtudomány Q Science / természettudomány > QA Mathematics / matematika > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 20 Feb 2026 07:47 |
| Last Modified: | 20 Feb 2026 07:47 |
| URI: | https://real.mtak.hu/id/eprint/234712 |
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