The AI model is so effective at finding software vulnerabilities that the new constraint is the human capacity to triage, patch, and deploy fixes. This has inverted the problem, creating a surge in demand for security engineers to handle the influx of identified issues.

AI will find vulnerabilities at an unprecedented rate. The real crisis will be the organizational inability to patch them, especially in critical infrastructure with long update cycles and unsupported software where original developers are long gone. The problem shifts from finding flaws to fixing them at scale.

Palo Alto Networks' CEO explains that AI tools are discovering software vulnerabilities at an unprecedented rate. This will cause a short-term deluge of patches, but it's effectively cleaning up years of bad code and will ultimately strengthen the entire ecosystem.

AI models have solved vulnerability discovery so effectively they've exposed a new, larger bottleneck: remediation. With projects like Glasswing reporting a 10-to-1 ratio of bugs found to bugs fixed, the industry's challenge has rapidly shifted from finding flaws to having the human capacity to patch an overwhelming number of them.

Frontier AI models are dramatically reducing the time it takes for a newly discovered software vulnerability to be turned into a functional exploit. This acceleration means traditional, onerous patching cycles are no longer viable. Organizations must find new ways to patch systems almost immediately, as exploits can appear within hours of a vulnerability's announcement.

Experienced CISOs are less concerned about AI models 'going wild' and becoming malicious hackers. The more practical and immediate problem is that AI will dramatically increase the volume of vulnerabilities discovered in codebases. Security teams will be overwhelmed not by sophisticated AI attacks, but by the sheer quantity of legitimate issues to triage and fix.

While AI models excel at identifying security vulnerabilities, the next major innovation lies in automatic remediation. The "holy grail" for cybersecurity startups is developing AI systems that can instantly patch and fix identified threats, moving beyond simple detection to proactive, zero-day defense.

The average time for an enterprise to patch a zero-day vulnerability is 55 days. AI agents can now find and build an attack for that same vulnerability in a fraction of a second, fundamentally changing the speed and scale of cyber defense required.

The traditional cybersecurity model of humans finding and patching vulnerabilities cannot keep pace with AI that discovers thousands of exploits in hours. This fundamental mismatch in speed and scale will require a complete overhaul of how software security is managed.