Controlling Advanced AI: The Gap Between Theory and Reality

As governments work to establish clear AI regulations, organizations are left navigating the frontier on their own. Meanwhile, static restrictions are reaching their limits. When access to proprietary models is constrained, enterprise demand naturally shifts toward open-weight alternatives—models offering incredible performance that require tailored internal controls.

This rapid evolution forces companies to redefine their internal governance: How do you empower teams to innovate and stay competitive while ensuring the system architecture, security controls, and workforce readiness are in place to keep AI operating safely?

Watch now for a practical, capability-first look at modern AI adoption. We will explore:

• The Reality of Model Behaviors: Why traditional boundaries struggle under real-world conditions and how to design better technical guardrails.
• Frontier vs. Local Models: What the rise of highly performant open-weight models means for your architecture and internal threat modeling.
• Proactive Security Strategy: Moving beyond static compliance toward continuous developer red teaming, threat simulation, and measurable operational readiness.