Physical security teams managing hundreds or thousands of devices across multiple sites face a maintenance challenge that spreadsheets and site visits simply can't keep up with. Firmware updates, password rotations, certificate management, and end-of-life tracking are no longer occasional tasks; they're continuous operational requirements. As Ari explains, the only path to staying on top of device health and compliance at scale is automation.

Most physical security teams assume their device environments are in reasonable shape — but the data tells a different story. Our 2026 Trends Report found that only 3% of enterprise security teams have full centralized visibility into their devices, and the consequences of that gap go far beyond day-to-day operations. As Ari explains, AI doesn't correct for an unhealthy environment. It multiplies whatever it finds there, gaps and all.

The "garbage in, garbage out" principle isn't new, but it takes on new weight when AI is making decisions about physical security at scale. Every AI tool, regardless of complexity, is only as reliable as the data feeding it, and in physical security that data comes directly from your device environment. As Ari explains, the device health and compliance work that physical security teams already know they need to do is the exact foundation AI requires to deliver any meaningful value.

Adding AI to an unprepared physical security environment puts more pressure on the weaknesses that already exist. Just as a house with a cracked foundation can't support additional weight, a device environment with offline cameras, disconnected access control panels, and compliance gaps can't reliably support AI-driven decision-making. As Matt explains, the quality of what AI produces is directly tied to the quality of the environment it's operating in, and a mixed input will always produce a mixed output.

It's easy to think of AI readiness as preparation for something that's still on the horizon. But the operational benefits of a healthy, visible, well-governed device environment start the day you achieve them. Gaining centralized visibility, ensuring devices are online and compliant, and reducing dependence on manual processes all deliver immediate value regardless of when AI enters the picture. As Matt and Ari discuss, the work of getting ready for AI is also the work of running a better security operation today.

Governance gets a bad reputation as the thing that slows organizations down, but in the context of AI it's what keeps automated decisions connected to human accountability. AI isn't capable of defining its own boundaries, enforcing its own policies, or flagging when its outputs are based on flawed assumptions. That requires human oversight, clear direction, and structures that were established before AI was introduced. As Ari explains, the organizations that get the most from AI will be the ones that built the right guardrails first.