Are You Solving Problems or Just Blocking Users?

We deployed an aggressive AI chat assistant trained to intercept every incoming support ticket before a human agent could touch it. Within 30 days, our first-line ticket volume plummeted by 40%, and our cost per ticket metrics dropped significantly.

The catch? The AI wasn't resolving complex user issues; it was exhausting users with endless loops of generic knowledge base articles. Frustrated customers gave up on getting support, closed the chat window, and chose to quietly cancel their subscriptions rather than fight through layers of automated gatekeeping.

Deflecting a ticket is not the same as resolving a problem. When efficiency metrics prevent customers from getting real help when they need it most, you aren't saving money you're just transferring support costs into churn costs.

How do you strike the right balance between AI-driven self-service efficiency and fast, frictionless access to human support?