Artificial intelligence can write code, analyze threats, generate convincing explanations, and increasingly act autonomously.

But does intelligent-looking behavior justify trust?

As organizations delegate more responsibility to AI, a dangerous gap emerges between what these systems appear to understand and what we can actually verify.

This talk challenges popular AI myths, explores the difference between intelligence, reliability, and accountability, and examines how human assumptions, cultural perspectives, and automation bias influence security decisions.

We investigate what happens when AI confidently produces incorrect results, when autonomous agents exceed their intended boundaries, and when humans stop questioning machine-generated recommendations.

The session offers a practical framework for preserving meaningful human control as AI capabilities expand.

Because the greatest security risk may not be that AI becomes too intelligent.

It may be that we trust it before we understand its limitations.