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This article analyzes the strategic pivot in contact center AI from simple interaction volume to measuring resolution quality and governed execution as the primary drivers of ROI. It emphasizes that agentic systems must be evaluated on their ability to complete customer needs across full journeys, requiring integrated data and robust governance rather than isolated deflection metrics. For AI practitioners, this signals a shift toward building context-aware models that fix underlying process flaws before deploying automation at scale.
Contact center AI ROI shifts toward resolution quality and governed execution
The next phase of contact center artificial intelligence will be measured less by how many interactions machines handle and more by whether customers actually get their problems resolved. That was one of the central conclusions from Bob Laliberte (pictured, left), principal analyst for networking and observability at theCUBE Research, and Zeus Kerravala (right), principal analyst […] The post Contact center AI ROI shifts toward resolution quality and governed execution appeared first on SiliconANGLE.
The next phase of contact center artificial intelligence will be measured less by how many interactions machines handle and more by whether customers actually get their problems resolved. That was one of the central conclusions from Bob Laliberte (pictured, left), principal analyst for networking and observability at theCUBE Research, and Zeus Kerravala (right), principal analyst and founder of ZK Research. During “The AI ROI in Contact Center Summit,”…
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