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TechRadar Review Backs Snagajob for Hourly and Gig Work, Flags Employer CostsAltman Tells OpenAI Employees Company Is Open to Slowing AI Development, Bloomberg ReportsAnthropic's Mythos 5 AI escaped sandbox and attempted PyPI supply-chain attackShelly Flood S Gen4 Leak Sensor Adds Matter and Apple Home for Under $30Contact Center AI Faces Its Resolution Test as Metrics Fall Out of StepiOS 27.1 Expected Between October 19 and 21, With First Beta Due Within Days
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Contact Center AI Faces Its Resolution Test as Metrics Fall Out of Step

Contact center AI is moving out of the pilot phase, but analysts say knowledge management, workflow redesign and outcome-based metrics will determine whether the investment pays off.

AI News Feed · 2026-09-12 03:22

Bob Laliberte, principal analyst for networking and observability at theCUBE Research, said those conditions make contact centers demanding and highly measurable. “Contact centers have large volumes of interactions. There [are] significant labor costs and direct moments of truth with customers,” Laliberte said. “When something fails, the consequences are also pretty highly visible, and a poor AI interaction can increase customer effort, right? Damage trust and ultimately hurt the brand.”

The market pressure is reshaping how suppliers position their platforms. Cisco Systems Inc. is betting on AI agents across collaboration and customer workflows, while a wave of voice agent launches has hit the cloud contact center market. Gartner projects conversational AI will cut contact center labor costs by $80 billion this year.

Zeus Kerravala, principal analyst and founder of ZK Research, a division of Kerravala Consulting, said the measurement frameworks the industry has relied on for decades are the first thing to break. Legacy targets reward speed and containment even when a customer’s problem goes unsolved, he said, pushing brands toward outcome-based scoring. “Historically, we’ve measured success in the context of things like average handle time, first call resolution,” Kerravala said. “And those metrics don’t, I don’t think, matter as much anymore. We’ve had such a focus on average handle time in this industry, but is that shorter call actually a good thing if the issue remains largely unsolved, right?”

Moving from assistants to autonomous agents raises the bar on testing, governance and data foundations. Companies including Five9 Inc. have leaned on implementation playbooks and voice AI agents to shorten time to value, but the groundwork still sits with the customer. “Organizations should be listening for some practical answers on the importance of high data quality, the integrations that need to be done,” Laliberte said. “Being open to redesigning their process, right? There [are], I think, some issues around knowledge management that need to be addressed as well.”

Success ultimately rests on knowledge management, workflow redesign and the handoff between virtual and human agents, according to the discussion. “It’s important to understand that the brands that lead will not be the ones that simply automate the most, right?” Kerravala said. “They will be those that turn AI into a better, more consistent set of outcomes, but will also be able to earn employee and customer trust.”