Webinar

5 ways AI supercharges CRQ

Discover how AI enhances Cyber Risk Quantification, simplifies risk estimation, and helps justify security budgets with data-driven insights and ROI.

Join a panel discussion to learn why AI is the key for unlocking accurate Cyber Risk Quantification (CRQ), especially in complex scenarios involving specific assets or attack vectors. We’ll examine how other real-world approaches work, why they lead to wildly inaccurate loss projections, and their business implications.

In this session, we’ll cover:

  • How AI uses your existing security and IT data to estimate cyber risk, incorporating threat intelligence, asset values, and controls.
  • How large language models eliminate human error and simplify the risk estimation process.
  • How a data-backed CRQ strategy helps justify security budgets and demonstrate ROI, even with limited resources.
  • How data-driven insights can help you confidently assess and improve your security program’s effectiveness.
Who was this webinar for?

CISOs, risk owners, and IT/security leaders looking to quantify cyber risk with more precision—and finally move beyond gut-based prioritization and Excel gymnastics.

What were the key takeaways?

You saw how AI and large language models supercharge CRQ by tapping into existing data, reducing human error, and helping you defend risk decisions with clarity, speed, and confidence.

What made this session different?

No fluff, no theory—just real-world examples of CRQ in action, why traditional methods fall short, and how AI-driven insights can transform risk conversations with leadership and the board.

5 ways AI supercharges CRQ

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