AI floods security teams with findings. The advantage is in what happens next

Over the past year, security teams on our platform cut the time it takes to fix a critical vulnerability by roughly 50%.

In the same period, their backlog of unresolved critical vulnerabilities grew nearly 29-fold.

These numbers describe the problem every security leader is about to inherit.

AI can now test software at a scale manual testing never reached.

Models read code and search thousands of assets for familiar vulnerability patterns, surfacing exposures earlier and faster than any human team could.

For businesses trying to keep pace with an expanding attack surface, that reach is genuinely valuable.

It is also exposing a weakness that has drawn far less attention: most organizations cannot validate, prioritize and remediate findings at anything close to the rate AI can produce them.

That imbalance is the whole game now.

Investment in AI discovery tools, on its own, does not make an organization more secure.

It makes it busier.

Left unaddressed, it leaves security teams with larger backlogs and less attention paid to the flaws that actually put the business at risk.

This is the problem Continuous Threat Exposure Management (CTEM) exists to solve.

CTEM gives organizations a continuous process for understanding their attack surface, finding weaknesses, proving which are genuinely exploitable, and directing remediation towards the exposures that carry the most business risk.

Discovery is one input.