Your Contact Center AI is Failing - And You Probably Built it That Way - Omilia

In this CX Today discussion, host and Associate Editor Rhys Fisher sits down with Claudio Rodrigues, Chief Product Officer at Omilia, to cut through the AI hype and get real about why so many contact centers are underperforming despite significant investment.If your AI deployment isn't delivering, Claudio argues the problem started long before you went live, and he's got the framework to fix it. This is a must-watch for any CX leader tired of chasing metrics that don't tell the full story.The contact center AI gold rush has left a lot of organizations holding fool's gold. Claudio Rodrigues has seen it firsthand... and he's not mincing words.Key discussion points:The root cause of AI failure: Most deployments collapse at the problem definition stage. Organizations chase “agentic AI” as a strategy rather than a solution, with no clear metric to measure success againstContainment rate isn't enough anymore: It's still a valid metric, but Claudio makes a compelling case for shifting the language from containment to resolution – and expanding the lens to include upsell, churn reduction, and revenue growthStatic vs. dynamic AI assets: A contact center frozen at a point in time will depreciate in value. Omilia's Self-Learning Agentic CX platform is built to continuously learn from real interactions, removing the need for armies of manual annotatorsWhat CX leaders aren't getting but should be: Faster time-to-value, deployment-ready data pipelines, and a clear line of sight between their AI investment and company growth metrics.Audit your current AI deployment against a clearly defined problem statement and explore whether your metrics capture resolution, upsell, and growth – not just containment.