LivePerson

Somewhere between writing the AI policy and deploying the AI agent, most companies lose control over what their system does in production. The pattern is consistent: an AI committee forms, usage guidelines get written, an approval workflow gets built, and then something goes sideways at 2 am when a real customer shows up with an edge case nobody anticipated. The postmortem happens, lessons get documented, and the policy gets updated. Then it happens again. The gap that most CX leaders don't talk about openly is the distance between having an AI policy and having AI assurance. A policy document tells your system how to behave. Assurance is the continuous, verifiable proof that it actually did, in production, at scale, with all the unpredictability that real customer conversations bring. The brands pulling ahead today aren't necessarily the ones with the most sophisticated AI models. They're the ones who've figured out how to make AI behavior testable before deployment, enforceable during live interactions, and verifiable after the fact. That combination is what turns AI from a liability into something you can actually stake your brand reputation on. I wrote a piece on the seven common misconceptions holding CX teams back from reaching that standard. If you're in the middle of figuring out where your governance program stands - https://lnkd.in/grx2pg8H #Syntrix #CustomerExperience #AI #LivePerson #AIAssurance #LivePerson