AI-generated editorial illustration; not a documentary photograph.
Contact-center AI is entering a more demanding phase: companies must prove that automated interactions actually solve customer problems, not merely shorten calls or contain more contacts. Analysts speaking during theCUBE’s coverage of the AI ROI in Contact Center Summit said weak knowledge management and outdated measurements are becoming the main obstacles to credible returns.
Speed Is No Longer Enough
Traditional measures such as average handle time and first-call resolution reward efficiency, but they can hide whether a customer’s issue was resolved. Zeus Kerravala of ZK Research said the industry is moving toward outcome-based scoring because a shorter interaction is not necessarily a successful one.
The Data and Workflow Burden
The shift from assistants to more autonomous agents raises requirements for data quality, system integrations, governance and testing. Bob Laliberte of theCUBE Research said customers also need to redesign processes and address knowledge-management gaps before automation can consistently support service teams.
Agents Still Need Human Handoffs
The operating model must account for the transition between virtual and human agents. The analysts identified knowledge management, workflow redesign and handoffs as connected parts of the same problem, rather than isolated implementation tasks. Companies including Five9 have promoted implementation playbooks and voice AI agents, but the source says customers remain responsible for much of the underlying preparation.
A Large but Conditional Opportunity
Gartner projects conversational AI will reduce contact-center labor costs by $80 billion this year, a forecast cited in the discussion rather than an independently verified result. Contact centers provide a visible test because they handle large interaction volumes, carry substantial labor costs and expose failures directly to customers. Poor automated interactions can increase customer effort and damage trust, according to Laliberte.
Source: Contact center AI faces its resolution test as metrics fall out of step
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