With AI chatbots, the conversation is the hard part, not the frameworks and tools.
Think about prototyping an insurance bot, integrating IBM Watson, Facebook Messenger, and claims databases. The most challenging component, by far, is the conversation. We have to understand the audience and their communication patterns. Talk to customers who have filed claims or are filing claims over the phone and online. Talk to customer service reps and claims adjusters. Listen to logged phone calls and read case emails. Researching conversation patterns in messaging.
Right now chatbot developers are treating the conversation component like a simple decision tree. But people don’t talk in decision trees. It’s a back and for negotiation. Non-developers are using the “no coding frameworks” and they are disappointing. When developers try to integrate conversational intelligence, they fail. When there is a problem definition, developers are great at integrating tools and frameworks. But mapping out how ordinary people converse or within a domain is a different skill set. Most UX professionals aren’t prepared for that either, so there is a talent gap.
tl;dr: There are lots of good use cases for AI chatbots, but too many people see it as a gold rush. Most are not doing the work to solve real problems.
Jun 17, 2016