AI Coding Tools Are Piling Up Security Work Faster Than Teams Can Clear It

AI coding tools are delivering clear benefits—faster development and less routine work—but they are also creating a growing problem for security teams.

When developers use AI to generate code, they can pull in open-source packages within minutes. That speed means more dependencies for security teams to review, covering vulnerabilities, licensing, maintenance, and ownership. The work doesn't disappear just because the code was produced faster. The result is what researchers call remediation debt: security tasks accumulating quicker than teams can resolve them.

A new webinar from ActiveState, based on a survey of 300 security and engineering leaders across technology, financial services, healthcare, manufacturing, and government, looks at how teams are handling this AI-driven open-source risk. The data examines where remediation programs are struggling and how debt connects to audit failures, breach frequency, and lost productivity.

The session, led by ActiveState's Rebecca Banks and Moris Chen, breaks down how AI coding is changing remediation workloads, how your program compares with 300 enterprise peers, where debt starts affecting security and business results, and which governance models are working today. It also flags approaches that may create more problems than they solve.

This isn't another warning that AI creates risk. It's a practical look at what the risk is becoming, how other organizations are responding, and where your process may need to change before AI-generated code scales further.