"59% of maintainers report growing contribution volume since the rise of GenAI," according to a new study published by Linux Foundation Research. But 25% of their incoming pull requests "are estimated to be low-quality, also known as 'AI slop'." And on large projects, 69% see growing contributions — and estimate that 31% are low-quality/AI slop. So what do these results show us? "Generative AI is fundamentally changing how people participate in open source," says the head of Open Source Ecosystem Development at Huawei's R&D subsidiary Futurewei, which helped support the study. Specifically GenAI is "lowering barriers to contribution" but also "creating new challenges" for maintainers and communities. Their recommendation? "Build the governance, transparency and trust mechanisms that allow AI-assisted contributions to strengthen, but not overwhelm, the open source ecosystem." "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." More from the blog It's FOSS: LF Research is the Linux Foundation's research arm. It was set up in 2021 and publishes studies on how open source is built and used, drawing on surveys and project data. Its latest report, Navigating Open Source Software Development in the Generative AI Era, surveyed 234 contributors and maintainers on how generative AI is affecting the way open source gets made... 64% say reviews now take longer. Burnout is their top concern at 63%, narrowly ahead of contribution quality at 60%. You will also find that policies have not caught up to the AI-assisted coding and vulnerability reporting trend. Of the 119 respondents who answered the question, 35% said their project has a formal policy permitting AI use. Another 32% have none and no plans for one, 23% plan to write one, and 10% ban AI contributions outright.... Most maintainers (71%) say AI makes it easier for newcomers to start contributing. Other interesting findings: "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." "71% of maintainers agree GenAI reduces barriers to entry for OSS, but 53% of maintainers disagree that GenAI has improved community trust." 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. 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. OpenSSF and LF AI & Data also helped support the study.

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"Despite massive investments and widespread hype around AI , the technology has delivered zero financial payoff to corporate America outside of tech," writes the chief economist at U.S. asset management firm Apollo Global. He adds that "there are still no signs of AI boosting productivity growth... [M]ainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins." VC-backed companies are spending more and more on tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it. As long as agentic AI and token spending are confined to a small part of the economy, the macroeconomic effects of AI will be very limited... The question looking ahead is whether, even as models become commoditized, mainstream corporate America can turn increasingly cheap intelligence into higher revenue growth and higher profit margins. That may be harder than it sounds. AI may be a great calculator, but in business, intelligence is mostly judgment. Judgment depends on context, and the answer varies with which human or which model you ask. Perhaps most importantly, AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness, all of which shape reputational risk and ultimately drive revenue growth and profit margins. The bottom line is that the AI story will be decided in the S&P 493, not the Mag 7, and so far, there is no evidence that revenue growth or margins are improving outside the tech sector. More details from TechCrunch: Apollo's Torsten Slok focuses on what he calls the S&P 493 — the S&P 500, minus Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla — finding that profit margins and revenue per worker appear to be flat, with no evidence that AI is improving productivity... Recent studies have also found that AI has yet to deliver significant productivity gains.

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