AI Code Growth Threatens Security Controls

Development teams are shipping software faster than ever, thanks to AI. But security teams still operate at human speed, reviewing vulnerabilities, managing dependencies, and prioritizing fixes. When code output jumps 10 to 50 times, the bottleneck shifts from finding vulnerabilities to keeping security from losing control of what gets shipped.

This is the focus of a new webinar from Chainguard, titled “The True Cost of Building at Machine Speed,” which is now available to watch. The session is designed for security leaders grappling with the scale of AI-driven development, according to the company's announcement.

AI Changes the Security Game

For years, application security followed a predictable cycle: developers wrote code, scanners found problems, security teams prioritized them, and engineers fixed what mattered most. AI puts that model under pressure, as teams can now generate many times more code, leading to more components, dependencies, findings, and fixes to manage.

Simply scanning more doesn't solve the problem; it can actually create a larger backlog. This isn't just a defensive challenge. The same AI models that help developers write and understand software are also available to attackers. As both software production and attacker capabilities accelerate, security teams are squeezed from both sides.

The core question becomes simple: How do you move at AI speed without accepting AI-speed risk?

That question is at the heart of the webinar, which looks beyond whether AI-generated code is secure and focuses on what happens to security when software creation outpaces human review and remediation.

Traditional Remediation Breaks Down

The webinar examines where traditional CVE-driven remediation starts to break down. At machine scale, existing vulnerability-management processes may struggle, and organizations need stronger guardrails before code reaches production.

The session also discusses how AI is expanding the software attack surface and why current vulnerability management may not keep up. It offers a practical framework for securing AI-driven development, emphasizing that slowing developers down is not the answer.

Governance Becomes Critical

AI-assisted development is quickly becoming more than an engineering decision. Security leaders need to understand who owns the risk, how much exposure the organization is accepting, and how to explain those choices to executives and boards.

Companies are adopting AI to build faster, so security controls must be designed for how software is built now, not five years ago. The webinar aims to provide a framework for making security work at AI speed, according to the announcement.

Watch the Webinar

Interested viewers can watch “The True Cost of Building at Machine Speed” to get insights into securing AI-driven development. The announcement suggests that the webinar can help organizations close the gap between development speed and security control.

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Why It Matters

The challenge highlighted in this webinar is not hypothetical. As AI adoption grows, the gap between development speed and security control is likely to widen, making it increasingly difficult for security teams to ensure that every code change is properly vetted. If left unaddressed, this could lead to more vulnerabilities slipping through, potentially exposing organizations to greater risk of breach. The webinar's call for a new operating model suggests that the industry may need to rethink how security is integrated into the development lifecycle, or risk losing control of the software supply chain.