Webinar Examines How Security Teams Can Keep Pace With AI-Driven Development

Artificial intelligence is enabling development teams to produce software at a much higher volume and speed, but security processes may not be scaling at the same rate. A new webinar, The True Cost of Building at Machine Speed, explores how organizations can manage that gap as AI-assisted coding becomes more common.

The session, produced with Chainguard experts, focuses on the operational challenges created when software output increases by multiples rather than incremental percentages. More code can mean more third-party packages, dependencies, vulnerabilities and remediation decisions. Simply expanding scanning activity may generate a larger queue of findings without helping teams determine which issues pose the greatest risk.

Beyond vulnerability backlogs

The webinar examines where conventional, CVE-centered vulnerability management can become less effective in an environment operating at machine speed. It also considers how secure-by-default practices, automated controls and development guardrails can reduce the amount of risk that reaches production.

Another topic is the expanding software attack surface. The AI systems used to generate, analyze and modify code are also available to adversaries, potentially increasing the pace and scale of attacks. This creates pressure for security teams to improve prevention and oversight without turning security reviews into a barrier to delivery.

Governance and accountability

AI-assisted development also raises questions that extend beyond engineering. Security and technology leaders must establish who owns the associated risks, define acceptable exposure and provide executives and boards with a clear explanation of how those risks are being managed.

Rather than recommending that organizations slow AI adoption, the webinar argues for adapting security programs to the way modern software is built. Topics include integrating controls earlier in the development lifecycle, prioritizing remediation based on meaningful exposure and establishing governance that can remain effective as AI usage expands.

The contributed webinar is available to watch online for organizations seeking practical guidance on securing AI-generated and AI-assisted software while maintaining faster development cycles.