Contact Center AI Is Only as Good as the Data Behind It – So Why Are We Ignoring the Data?

SuccessKPI on data governance, ground truth, and why excitement about AI is outrunning the ability to manage it

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Published: June 25, 2026

Rhys Fisher

Rhys Fisher, Associate Editor at CX Today, sits down with Dave Rennyson, CEO of SuccessKPI, to tackle one of the most pressing yet underexplored challenges in modern contact center operations: what it actually takes to build an AI-ready data foundation.

As AI agents become a fixture of the contact center, Dave makes a compelling case that the real risk isn’t the technology, it’s the lack of governance, measurement, and rigor underneath it.

If your organization is deploying AI without asking how you’ll manage it, this is essential viewing.As contact centers race to deploy AI, most are skipping the hard work that makes it sustainable. Dave Rennyson pulls no punches on what’s going wrong and what leaders need to do differently.

AI agents actually produce more data than human agents, including failure signals and turn-taking data that human conversations never generate. The opportunity is significant, but only if you have the architecture to capture and act on it.

“Ground truth” is the step almost everyone skips. Dave breaks down what it means to establish a reliable baseline for AI performance, why it demands real scientific rigor, and what model drift looks like when you ignore it.

Agentic AI is genuinely different from legacy IVR. The removal of linear flow constraints opens up a new design space, but only if organizations build the right orchestration and monitoring layers on top.

Rather than declaring surveys dead, Dave argues that generative AI can now appraise every single conversation at scale, turning a historically biased metric into something far more powerful.

For more Customer Experience tech news visit CX Today.

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