Contributions to generative AI projects on GitHub grew 59% YoY from October 2023 to September 2024 and Python overtook JavaScript as the most popular language
In this year's Octoverse report, we study how public and open source activity on GitHub shows how AI is expanding as the global developer community surges in size.
Context & Ripple Effects
GitHub’s language rankings had previously placed JavaScript, Python and Java at the top; this report marks a shift from that earlier JavaScript-led ordering while showing rapid expansion in public generative-AI work.
The results also extend a coding-AI arc already visible when GitHub reported substantial code creation with Copilot: AI-assisted code production and open-source generative-AI development are now advancing together on the same platform.
First-order effects
- Public generative-AI repositories receive a much larger flow of contributions, increasing the pace at which maintainers and contributors iterate on shared AI tooling and projects.
- Python becomes GitHub’s most-used language for the period, displacing JavaScript in a closely watched indicator of developer activity.
Second-order effects
- AI-project maintainers and developer-tool vendors have a stronger incentive to prioritize Python workflows, packages and documentation as more visible generative-AI activity concentrates there.
- The growth in public AI work makes GitHub’s developer network more strategically important as a distribution and collaboration layer for coding-AI products, reinforcing the relevance of its existing Copilot footprint.
Third-order effects
- If this pattern persists, the center of software development shifts further toward AI-native, open-source building blocks, with language ecosystems competing on their ability to support model development and deployment.
- The combination of AI-assisted coding and expanding public AI projects could make repository platforms increasingly important infrastructure for how developer tools are adopted, governed and monetized.
The trend: Generative AI is becoming embedded in mainstream software production, reshaping both open-source contribution patterns and the language ecosystems developers choose.