Watch On Demand: Why Enterprise AI Needs a Control Layer

How many AI agents are actively running right now in your organization, including the ones your IT team didn’t sanction?

If you can’t answer that confidently, you’re not alone. Most enterprise leaders are facing the same uncertainty. The reality is this: AI is no longer experimental. It’s operational infrastructure. And yet, most organizations are managing it the same way they managed SaaS in 2010: reactively, inconsistently, and without centralized visibility.

The gap between AI deployment and AI governance has created real, measurable risk across your organization.

You’ll come away with a framework you can apply immediately, whether you’re starting your AI governance journey or already have governance policies in place.

You’ll also gain:

• Clarity on what a “control layer” actually means in practice (it’s not what you think)
• Concrete examples of what unmanaged AI looks like when problems occur
• The four layers of risk that every enterprise leader should understand
• Why hyperscaler tools don’t solve this — and what does