Endpoints are no longer defined by physical boundaries. They’re fluid and invisible—a challenge for traditional security. Large Language Models (LLMs) are changing the game. They predict, not just detect, leveraging global threat data and your internal knowledge for real-time, adaptive defense. Imagine AI-powered responses to new malware instantly, without waiting for patches.

But the threat evolves. AI strengthens attackers, too, creating polymorphic malware that outpaces traditional defenses. This talk explores how AI-driven security strategies—reasoning frameworks, dynamic re-calibration—can secure modern endpoints. We’ll confront the critical question: How do we ensure our defenses with the right strategy in an era of AI-driven attacks?

Key takeaways:
• Have a strategy: A strategy that aligns tools, people, and processes and is based on organizational policy would give better visibility to your digital assets.
• Proactive AI Defense: Embrace LLMs to move beyond reactive security, leveraging predictive analytics for real-time, context-aware threat mitigation.
• Zero-Trust Imperative: Adopt a Zero-Trust approach, understanding that endpoints are fluid and boundaries are blurred, requiring continuous verification and adaptive security frameworks.