AI is already embedded in day-to-day work through public AI tools, copilots inside core business applications, code assistants, and early-stage agents. In many organizations, security teams are discovering the exposure after the workflows are already entrenched.
In this session, we’ll unpack the AI Control Gap: when adoption outpaces visibility, “approved vs. not approved” stops being an enforceable model. Security is left choosing between blunt controls that frustrate teams and permissive policies that miss the real risk. The outcome is familiar: shadow AI sprawl, sensitive data showing up in prompts, inconsistent guardrails across environments, and growing pressure to prove governance and accountability.
In this webinar, we’ll focus on what works in practice. We’ll cover how to establish reliable visibility into AI usage, define clear ownership across security and business stakeholders, and operationalize guardrails that protect data and reduce AI-specific threats like prompt injection and unsafe outputs, without slowing adoption.