What's your AI quality check?

The quality check for AI output looks different when the stakes go up. Reviewing a draft email is one thing. Reviewing an AI-built audience segment before it goes into a live campaign, or validating the logic behind an agent's journey decision before it reaches thousands of customers, that's a different conversation entirely.

As AI moves deeper into customer experience workflows, the review process has to evolve with it. Some teams are building structured validation steps. Others are still figuring out where the human checkpoint belongs when agents are making decisions in real time.

So I'm curious: what does your quality check look like when AI is touching customer-facing work (versus internal work)? How do you validate AI-driven decisions, segments, or content before they go live? And has that process changed as the use cases have gotten more complex?

Whether you're reviewing agent logic, auditing AI-generated audiences, or building governance into agentic workflows, I'd love to hear how you're approaching it.

Drop your process below. 👇