AI code boom drives production failures, higher spending
AI + ML
AI code accelerates production failures and spending, study finds
CloudBees survey exposes verification gap
The rapid adoption of AI-generated code is driving production failures and higher costs for enterprise customers.
Eighty-one percent of enterprise technology leaders among more than 200 surveyed reported an increase in production issues linked to AI-generated code, according to a study published by enterprise software delivery biz CloudBees.
Sunil Gottumukkala, CEO of Averlon, an agentic vulnerability remediation biz, told The Register in an email that these issues tend to refer to functionality bugs, performance issues, availability problems, and security vulnerabilities rather than CI/CD failures.
"These are issues that surface after code has already been deployed to production, which means the code passed every review and deployment gate and still broke things," said Gottumukkala. "When failures happen post-deployment, it signals that the validation process itself isn’t keeping pace with what AI is producing."
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