AI is no longer just generating content—it’s retrieving, reasoning, and increasingly making decisions. And yet, many organizations are approaching it as if better prompts or better models will solve everything. In reality, AI is only as effective as the content it relies on. The more autonomous these systems become, the more they depend on content that is structured, connected, and governed with intent.

In this conversation, Kristina Podnar sits down with Carrie Hane to unpack what that actually means in practice. They explore the difference between formatting and true semantic structure, why duplication and inconsistency quietly undermine AI performance, and how weak or nonexistent content models introduce risk at scale. They also get into a question that doesn’t get asked often enough: who actually owns the content model in an organization—and what happens when no one does?

This episode is a reminder that AI doesn’t eliminate the need for structure—it exposes where it never existed. If organizations want AI to perform reliably, content can no longer be treated as a byproduct of publishing. It has to be treated as infrastructure.