New LF Research Survey Shows Generative AI Cuts Open Source Coding Time in Half, but 25% of Incoming Pull Requests are Considered AI Slop

Generative AI boosts developer productivity and lowers contribution barriers, but rising volume of requests and maintainer workloads demand stronger project governance

Summary

• Linux Foundation Research published a new study examining how generative AI (GenAI) is reshaping open source software (OSS) development.
• The research uncovered significant productivity gains alongside growing maintainer pressures.
• A majority (59%) of project maintainers report growing contributions to OSS, but 25% of incoming pull requests (PRs) are estimated to be low-quality “AI slop.”
• For both contributors and maintainers, GenAI boosts productivity by up to 50% across all types of OSS development tasks.
• The findings point to a need for stronger AI governance, including clear contribution policies, standardized attribution and verification and continued investment in human mentorship.

RALEIGH, N.C., Oct. 20, 2026 – All Things Open 2026 – The Linux Foundation, the nonprofit organization enabling mass innovation through open source, today announced a new research report, Navigating Open Source Software Development in the Generative AI Era: Challenges and Opportunities for Project Communities, exploring how GenAI is reshaping OSS development. Published by LF Research with sponsorship from Red Hat, the world’s leading provider of open source solutions, and additional support from Futurewei, OpenSSF and LF AI & Data, the findings will be presented at All Things Open, taking place Oct. 19-20 in Raleigh, N.C.

As GenAI becomes increasingly embedded across the software development lifecycle, findings reveal a complex picture. While AI tools can speed up development and lower barriers to contribution, the research revealed that increases in contributions have consequential impacts on project maintainers. While 59% of maintainers report growing contribution volume since the rise of GenAI, increasing to 69% among large projects, 25% of incoming PRs are estimated to be low-quality, also known as “AI slop,” and that percentage rises to 31% among large projects.

“Open source projects need to design for a growing AI-generated contributor base, not simply react to it,” said Hilary Carter, SVP of Research at the Linux Foundation. “That means setting clear expectations for GenAI, putting responsibility for testing and disclosure on contributors and giving maintainers better tools to manage incoming pull requests. If we get those fundamentals right, AI can expand participation without overburdening and increasing costs for maintainers.”

Among the study’s other significant findings:

• GenAI is lowering barriers to open source participation, but increasing friction: 71% of maintainers agree GenAI reduces barriers to entry for OSS, but 53% of maintainers disagree that GenAI has improved community trust.
• Productivity gains are substantial but vary by task complexity: GenAI accelerates OSS development in more ways than simply writing code faster. Respondents estimate average time reductions across all six OSS development activities measured, including proposal discussions (19%) and code authoring (52%). For high-complexity tasks, however, 21% of respondents report taking more time when using GenAI.
• Developers are reinvesting the time they save back into open source: 66% report using productivity gains to address technical debt, 63% to develop new features and 58% for learning and upskilling.
• Governance hasn’t caught up with adoption: Only 35% of projects have a formal policy permitting GenAI use, while 32% have no policy and no plans for one. Among contributors, 61% conduct detailed reviews and full functional testing of AI-generated code before submission, but disclosure of AI assistance remains inconsistent.
• Continued investment in human mentorship remains important: 46% of maintainers say GenAI increases the need for mentorship of new contributors, compared with 32% who say it decreases that need.

In order to realize the most value from GenAI in OSS development, the research suggests that projects should establish clear written policies for AI-assisted contributions, strengthen transparency and disclosure requirements, demand contributors test and document AI-assisted changes before submission and standardize attribution practices. The research further recommends that communities treat governance, verification and trust as core infrastructure for AI-assisted development.

To learn more, read the full report here.

Supporting Quotes

“Generative AI’s impact on open source should be measured by the quality of contributions and the health of the communities behind them, alongside productivity gains,” said Mark Collier, GM of AI & Infrastructure at the Linux Foundation. “This research shows why investment in AI tools must go hand in hand with investment in maintainers, mentorship and trust. Through LF AI & Data, we’re bringing communities together to advance open source AI and help translate these gains into sustainable progress for the open source ecosystem.”

– Mark Collier, GM of AI & Infrastructure, The Linux Foundation

“Generative AI is fundamentally changing how people participate in open source, lowering barriers to contribution while also creating new challenges for maintainers and project communities. The answer is not to slow innovation, but to build the governance, transparency and trust mechanisms that allow AI-assisted contributions to strengthen, but not overwhelm, the open source ecosystem.”

– Anni Lai, Head of Open Source Ecosystem Development, Futurewei

“AI can write code faster, but contributors still need to understand and test what they submit. This research shows why clear contribution policies and careful review matter as AI adoption grows. Keeping open source secure is a shared responsibility, and maintainers should not have to carry it alone.”

– Adrianne Marcum, Chief of Staff, OpenSSF

"Generative AI offers interesting potential to make software contributions far more accessible, but true productivity means little if we compromise on quality or community trust. As the volume of incoming contributions expands, project maintainers need transparent practices, dependable model lineage and consistent governance to manage this shift effectively. Ensuring a sustainable ecosystem means backing our contributors with shared standards, reliable verification and strong mentorship—guaranteeing that open source continues to thrive on human collaboration."

– Brian Proffitt, Senior Principal Community Architect - Strategic Insights, Open Source AI Program Office, Red Hat

About Linux Foundation Research

Founded in 2021, Linux Foundation Research explores the growing scale of open source collaboration, providing insight into emerging technology trends, best practices, and the global impact of open source projects. By leveraging project databases and networks and committing to best practices in quantitative and qualitative methodologies, Linux Foundation Research is creating the go-to library for open source insights for the benefit of organizations worldwide.

About the Linux Foundation

The Linux Foundation is the world's leading home for collaboration on open source software, hardware, standards, and data. Linux Foundation projects, including Linux, Kubernetes, Model Context Protocol (MCP), OpenChain, OpenSearch, OpenSSF, OpenStack, PyTorch, Ray, RISC-V, SPDX and Zephyr, provide the foundation for global infrastructure. The Linux Foundation is focused on leveraging best practices and addressing the needs of contributors, users, and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.

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