AI in Customer Service

AI is transforming customer experience — but not always for the better. Too many contact centers are automating broken processes instead of fixing them. Here’s what it really takes to make your operation AI-ready — and deliver results that last.

A friend’s quest for the perfect Cadbury Creme Egg turned into a lesson in the strengths — and limits — of AI in customer service. While chatbots are great for automating routine tasks, her experience showed that true understanding and empathy still come from humans. The future of great customer experience lies in combining both — technology for efficiency, and people for connection.

Workforce Management (WFM) is critical for balancing automated systems and human agents in call centers by optimizing resource allocation, improving efficiency, and ensuring customer satisfaction. Here’s how it helps: Demand Forecasting and Scheduling : WFM systems use historical data and AI-driven analytics to predict call volumes, chat inquiries, and peak times. WFM tools, such as NICE or Verint, analyze patterns to determine when automation (chatbots, IVR systems) can hand