How AI Exposed Cybersecurity’s Biggest Blind Spot, According to Rob Gurzeev

Artificial intelligence is reshaping the way software is created, deployed, and secured. But while AI has unlocked rapid innovation across industries, it has also dramatically widened the number of internet-facing assets that organizations must defend. For Rob Gurzeev, CEO and Co-Founder of CyCognito, the real problem isn’t simply finding known vulnerabilities anymore. It is understanding what an organization actually owns and what is truly exposed to attack.

The rapid adoption of AI tools has created a massive blind spot in cybersecurity. Many companies are rushing to integrate AI into their operations without a clear picture of their expanding attack surface. Gurzeev argues that traditional security approaches, which focus on patching known weaknesses, are no longer sufficient. The modern threat landscape requires a fundamental shift in perspective: you cannot protect what you do not know exists.

As development cycles shorten and cloud environments grow more complex, assets are often spun up, moved, or decommissioned without proper oversight. This chaotic growth, fueled by AI-driven automation, leaves organizations vulnerable to attackers who are quick to exploit unknown or forgotten entry points. Gurzeev stresses that the first step to closing this gap is gaining complete visibility into every external-facing asset, from APIs to microservices to third-party integrations.

Without a comprehensive map of the attack surface, even the most advanced AI-powered defenses will fail. The real opportunity lies in using AI not just to detect threats, but to discover and catalog every potential point of entry before adversaries do. For Gurzeev, this is the defining challenge of modern cybersecurity: moving from a reactive patch-and-pray model to a proactive, intelligence-driven approach that leaves no blind spot unexamined.