How Conversational AI Is
Changing Call Routing

Traditional IVR systems — "Press 1 for Sales, Press 2 for Support" — route calls through rigid, pre-defined menus. Conversational AI takes a different approach: instead of navigating a menu tree, callers simply speak their intent and the system interprets it. This article explains how the two approaches differ and what to consider when evaluating AI call routing.

The Limitations of Menu-Based IVR

Menu-based IVR works by presenting callers with a fixed hierarchy of numbered options. The caller must correctly identify which menu option matches their need and navigate through potentially several layers of sub-menus to reach the right destination.

Common problems with this approach include callers selecting the wrong option (either from misunderstanding or because no option closely matches their need), callers abandoning the call during long menus, and the overhead of maintaining and updating menu structures as business needs change.

How Conversational AI Routing Works

Conversational AI routing uses natural language processing (NLP) to interpret what a caller says rather than which number they press. When a caller says "I need to check the status of my order," an AI auto attendant processes that intent and routes the call to the appropriate team — or in some cases resolves the query directly if the information can be retrieved automatically.

This requires a trained language model that understands the range of ways callers might express a particular intent, integration with relevant back-end systems for resolution or routing logic, and fallback paths for cases where the system cannot confidently identify the intent.

The quality of conversational routing depends heavily on how well the model has been trained on the vocabulary and use cases relevant to your business. Off-the-shelf solutions vary considerably in performance across different industries and languages.

What to Evaluate Before Deploying AI Routing

AI call routing can reduce the friction of navigating menus and, where resolution is possible without an agent, reduce handle time. Whether this represents a meaningful improvement for your contact centre depends on your call mix, the nature of your inbound queries, and the quality of the AI system you deploy.

Key questions to ask of any AI routing or AI agent solution include: what call types can it handle automatically versus route to an agent; how does it behave when it cannot identify intent; what happens if a caller does not want to interact with an automated system; and how is the model trained and maintained over time.