AI-Generated Pull Requests Now Comprise 25% of Code
Open source maintainers report longer review times and increased burnout as automated code submissions saturate the workflow.
Updated on Oct. 22, 2026 in Artificial Intelligence
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A new Linux Foundation Research report finds that AI-generated content now accounts for an estimated 25% of incoming pull requests in open source projects. The study, based on a survey of 234 contributors and maintainers, highlights a shift in software development workflows.
Why it matters
The influx of AI-assisted code creates a dual pressure on maintainers: while it lowers barriers for newcomers, it simultaneously increases review times and concerns regarding contributor burnout. This tension is forcing projects to reconsider how they govern automated submissions.
Maintainers report that code review times have increased for 64% of large projects due to AI-assisted contributions. Meanwhile, 35% of projects have established formal policies to manage this automated input.
The players
Linux Foundation Research
An arm of the Linux Foundation, the non-profit organization that supports the Linux kernel and various open source software projects.
The details
Open source projects are managing a significant shift in intake as AI-generated pull requests—proposed changes to a code repository—become standard. While AI tools enable contributors to author code 52% faster, maintainers are struggling with the oversight required to verify these automated submissions. Currently, 26% of projects operate without any mechanism to validate whether incoming code was authored by a human or an AI system.
Timeline
October 22, 2026: Linux Foundation Research published the survey results.
The Tech Race
This study marks the latest analytical milestone for the organization founded in 2021 to monitor ecosystem health. The data provides a quantitative benchmark against which future software governance models will be measured.
Maintainers should anticipate continued friction during review cycles, as 23% of projects intend to implement formal policies regarding AI usage in the near term. Contributors using AI tools may face stricter verification standards as more projects move away from their current lack of oversight.
The takeaway
The rise of AI-assisted contributions is fundamentally shifting the maintainer workload from creative development to high-volume verification. Projects currently lacking a contribution policy should look to the 23% of teams actively developing new frameworks for AI governance.
Further reading
Explore the broader implications of automated code in Artificial Intelligence.
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