Organizations are taking a slapdash approach to AI-generated code, with many spending far too little time on oversight, new research suggests.
The vast majority (93%) of respondents to Cloudsmith’s 2026 Artifact Management Report said their organization was using AI-generated code, more than twice as many as last year.
Yet despite this sharp increase, around than one-third (31%) spend 10 hours or less per month validating, auditing, or securing it. Indeed, just 58% spend at least 11 hours per month on this front while one-in-twenty said they don’t audit AI code at all.
While AI models have become a leading artifact type, only 12% of organizations are managing them using the same security policies and provenance tracking as traditional binaries, such as language packages and operating system libraries.
This is despite the fact that organizations are mostly aware of the risks, with only 17% very confident that AI is not introducing new vulnerabilities into their codebase.
“We are at a huge inflection point in the history of software development. In a matter of months, we’ve gone from, ‘How can AI help me write better code?’ to, ‘How can I help AI write better code?’”, said Glenn Weinstein, CEO of Cloudsmith.
“But at the same time, AI tools are expanding the attack surface, introducing more open source dependencies. And those same tools are being used by malicious actors to find more vulnerabilities in existing libraries, leading to more CVEs.”
Sloppy practices could come back to haunt devs
Poor security practices on this front could have wide-reaching regulatory implications for enterprises, the study warned.
Under the EU’s Cyber Resilience Act (CRA), organizations are required to provide a detailed assessment 48 hours after becoming aware of a breach – and this includes providing provenance data.
More than half (53%) of respondents told Cloudsmith they’d need to put in a significant amount of manual effort or time to produce a comprehensive report of artifact versions, origins, and security attestations.
Only a quarter of engineering teams automatically generate and verify Software Bills of Materials (SBOMs) at every build, with the rest doing it manually, reactively, or only when an auditor asks.
Notably, nearly three-quarters (74%) said they’d struggle to produce a complete report quickly if they were hit with a surprise audit tomorrow.
The majority (83%) run outdated artifact management systems, often because they’re worried that upgrading is risky or painful.
Software supply chain threats are growing
Weak software supply chain security has become a high-profile issue over the last year, not least with the Axios npm compromise that hit earlier this month.
With threat campaigns including Shai Hulud 2.0 and SANDWORM_MODE specifically targeting the software supply chain via upstream repositories, 44% of respondents said they’d experienced a security incident caused by a third-party dependency.
The same number said their organization spent over 50 hours per month investigating potential security issues linked to third-party dependencies, whether or not they resulted in a breach.
“Agentic development is an incredibly powerful way to build software, and teams will be far more productive and write even more software as a result. That is a good thing, because the world certainly needs more software and more automation,” said Weinstein.
“For enterprises to manage this new velocity and productivity, automated guardrails and context are the new keys to unlock the production of safer, more efficient code.”
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