Shipping More AI Code Than You Can Secure? Watch How to Control Remediation Debt

The Hacker NewsAug 24, 2026AI Security / Webinar

If your developers are using AI coding tools, you are probably already seeing the upside: faster development, more code, and less time spent on routine work.

The harder part is what comes after. AI can also introduce open-source packages at a pace your security team was never built to handle. More dependencies mean more vulnerabilities to review, more remediation work, and a backlog that can quietly keep growing.

Our latest AI Coding and Open Source Risk webinar examines what this means for security and engineering teams, drawing on data from 300 enterprise leaders.

The Real Problem Is What AI Adds to Your Stack

AI coding itself is not the issue. The problem is how quickly generated code can bring new open-source components into your environment.

A developer can add a dependency in minutes. Your team may then need to assess vulnerabilities, licensing, maintenance, ownership, and whether that package should be there at all.

That work does not disappear just because the code was generated faster. Over time, you end up with remediation debt: security work accumulating faster than your team can close it.

And as AI tools become more autonomous, that gap could widen significantly.

See How Your Program Compares

ActiveState surveyed 300 security and engineering leaders across technology, financial services, healthcare, manufacturing, and government.

The research examines how teams are handling AI-driven open-source risk, where remediation programs are struggling, and how that debt relates to audit failures, breach frequency, and lost productivity.

This webinar walks through those findings so you can compare your own program with what other enterprises are seeing.

That benchmark matters. It gives you a clearer sense of whether your current controls are keeping up or simply pushing more unresolved work downstream.

What You’ll Take Away

ActiveState’s Rebecca Banks and Moris Chen break down:

• How AI coding is changing open-source remediation workloads
• How your program compares with 300 enterprise peers
• Where remediation debt starts affecting security and business outcomes
• Which governance models are working today
• Which approaches may create more problems than they solve

This is not another session telling you that AI creates risk. It is a practical look at what the risk is becoming, how other organizations are dealing with it, and where your current process may need to change before AI-generated code scales further.

Watch the AI Coding and Open Source Risk webinar to see what the data shows and how enterprise teams are responding.