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Experts on Experts: Why AI and Compliance Are Forcing A New Security Operating Model

Rapid7 VP of Global Government Affairs and Public Policy Sabeen Malik says frontier AI is forcing security leaders to adopt a new operating model that integrates vulnerability discovery, compliance, and operational resilience at machine speed. The shift requires moving from reactive to preemptive security, where AI-driven tools surface actionable risks but human governance and judgment remain essential for validation and accountability.

read2 min views1 publishedJun 25, 2026

This week on Experts on Experts, I sat down with Sabeen Malik, Rapid7’s VP of Global Government Affairs and Public Policy, to discuss a shift security leaders can’t afford to treat as separate threads: frontier AI, vulnerability discovery, cybersecurity compliance, and operational resilience.

AI is changing how quickly vulnerabilities can be found, validated, and potentially exploited. At the same time, regulators, boards, and customers are asking for stronger proof that controls are working and risk is being reduced. Security leaders are being pushed to move at machine speed while proving the business is resilient.

Sabeen and I started with the policy question. Many of the systems security teams rely on today were designed for a slower era of human-led discovery. Vulnerability disclosure processes, scoring systems, prioritization frameworks, and regulatory expectations all assume organizations have time to assess, verify, and respond.

Frontier AI challenges that assumption. If models can help find and chain vulnerabilities faster, the industry needs stronger standards around verification, access, disclosure, and accountability. Access to powerful models matters, but access alone does not solve the governance problem. The bigger question is whether the ecosystem can responsibly validate, prioritize, and act on what these systems produce.

For defenders, faster discovery is only useful if it leads to faster action. Finding more vulnerabilities does not automatically make organizations safer. In many cases, it creates more noise for teams already under pressure. The real challenge is exploitability. Security teams need to understand which risks are actually reachable, which issues matter most in their environment, and where action will reduce exposure fastest. That is where the shift from reactive security to preemptive security becomes critical. The goal is to use data, context, AI, and expertise to act earlier, not simply respond faster after something happens.

We also discussed how the compliance environment is changing. Organizations are no longer being asked to prove readiness once a year. Increasingly, they need to provide detailed evidence on shorter timelines across a growing set of regulatory and assurance requirements.

That creates a real challenge when evidence is collected manually or disconnected from live security operations. Leaders need to show what changed, what was fixed, who owns the response, and what risk remains. Static snapshots are no longer enough.

One of the clearest themes from the conversation is that the future of security operations will be AI-driven, but human-led. AI can help teams move faster, surface what matters, and respond with greater scale and consistency. But governance, accountability, and judgment still matter.

That same principle applies to compliance. Security and compliance teams need live operational context, not disconnected reports. They need to connect what they detect, what they fix, and what they can prove.

Watch the full episode to hear our conversation on what this moment means for AI in cybersecurity, cybersecurity compliance, and resilient security operations:

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