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Who is using AI to code? Global diffusion and impact of generative AI
Simone Daniotti1,2, Johannes Wachs1,3,4, Xiangnan Feng1
1Complexity Science Hub, Vienna, Austria.
Science (New York, N.Y.)
|January 22, 2026
Summary
Generative AI tools boost experienced developers' productivity, but early-career coders see no gains. Uneven AI adoption may widen skill gaps in software development.
Area of Science:
- Computer Science
- Software Engineering
- Artificial Intelligence
Background:
- Generative coding tools offer potential productivity increases.
- Uneven adoption of these tools may exacerbate skill and income disparities.
- Understanding AI's impact on software development is crucial.
Purpose of the Study:
- To analyze the adoption rate of AI-generated code across software developers.
- To quantify the productivity impact of AI coding tools on different experience levels.
- To investigate the potential for AI to widen skill gaps in the tech industry.
Main Methods:
- Trained a neural classifier to identify AI-generated Python functions.
- Analyzed over 30 million GitHub commits from 160,097 developers.
- Tracked the adoption speed and geographical distribution of AI coding tools.
- Estimated the impact on quarterly output and developer productivity.
Main Results:
- AI currently generates an estimated 29% of Python functions in the US, with a decreasing lead globally.
- Quarterly output, measured in online code contributions, increased by an estimated 3.6%.
- Experienced, senior-level developers showed significant productivity gains and domain expansion.
- Early-career developers exhibited no substantial benefits from AI adoption.
Conclusions:
- AI coding tools disproportionately benefit senior developers, potentially widening the skill gap.
- The rapid adoption of AI in coding necessitates strategies to ensure equitable skill development.
- Future career trajectories in software development may be reshaped by AI integration.
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