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  What does a conversational AI chatbot actually do? A customer messages a bank on WhatsApp late in the evening: "EMI ka due date kya hai aur late fee lagega kya?" A scripted bot replies with a five option menu, none of which fit. The customer waits for the call centre to open the next day. A conversational AI chatbot reads the intent behind that Hinglish sentence, pulls the due date from the core banking system, checks the late fee rule and replies in the customer's language. That is the difference between a bot that talks and a bot that resolves. For enterprises, three capabilities define the category: language understanding, system integration and workflow execution. A bot missing any one of them stays a small tool. Why do chatbots struggle with Indian languages? Indian customers rarely write in clean, single language sentences. A user in Pune mixes Marathi and English in one line. Someone in Patna types Hindi in Roman script. Voice adds accents, background noise and ...

For a while, chatbots used to perform like magic. You typed a question, and something answered instantly, no music and no waiting. But fast-forward to 2026, and that charm has faded. Customers aren’t impressed anymore. In fact, many are quietly frustrated. The problem isn’t that chatbots exist. It’s that most of them haven’t evolved. Today’s users expect conversations, not scripts. And traditional chatbots, those rigid, rule-based systems, are struggling to keep up. And how multilingual conversational AI chatbots are assisting businesses in achieving higher customer satisfaction. What Are the Limitations of Traditional Chatbots? The Illusion of Help If you’ve ever typed a simple question into a chatbot and received a wildly irrelevant response, you’ve seen the issue firsthand. Most legacy chatbots are built on predefined decision trees. They work fine until a customer steps even slightly outside the script. Then everything falls apart. According to Deloitte, over 60% of customers aban...