Conversational AI refers to the different types of AI software or solutions that are designed for people to talk to and communicate with. We train conversational AI using vast amounts of input data, essentially language and phrases that teach it how to recognize words and imitate human interactions. In a business context, this is useful in many different situations, especially customer care. With conversational AI, we can train virtual assistants to help customers solve common problems, more quickly find insights in their documents, or automate repetitive tasks using natural language commands.
Natural language processing (NLP) is one of the techniques we use, along with machine learning and sometimes other forms of AI as well, to train conversational AI. It is focused on teaching computers to analyze language. A robust conversational AI that’s in the field and helping customers resolve their issues, buy products or execute tasks is the end result of combining NLP with other forms of AI that put that comprehension to work.
At IBM, we’ve developed several different types of conversational AI solutions to help businesses deliver better customer care experiences and help their employees be more productive. For example, IBM Watson Assistant, which is our core conversational AI solution, automates engagement with customers to accelerate the resolution of their issues or answer questions that might be buried in hard-to-read FAQs and webpages. It uses machine learning and natural language processing to understand customers, in the appropriate context, and to provide fast, consistent, and accurate answers across any application, device, or channel. We’re also developing conversational AI solutions that are being put to work for automated order taking in quick service restaurants as well as solutions for digital employees that allow your team members to use natural language to automate repetitive tasks.