Conversational AI, which uses Natural Language Processing (NLP), Automatic Speech Recognition (ASR), Advanced Dialog management, and Machine Learning (ML), are likely to pass the Turing Test and provide a more realistic experience than traditional chatbots.
Today’s AI-based chatbots can have full blown conversations that leave people feeling like they just finished a conversation with a living person.
Conversational AI chatbots can be predictive and highly personalized, with more complex, fluid responses that are very similar to human decision-making.
The consumers and brands are embracing conversational AI because it can be used to provide personalized experiences that are quicker and more convenient than traditional ways of interacting with brands.
Digital personal assistants, such as Alexa, Siri, & Google Assistant are an example of the active use of conversational AI.
Digital customer assistants are another example of active conversational AI, and they can be found on business websites, built into apps or responding to customer service tickets.
“We are now seeing digital experiences shift from human to machine interactions, to execute their strategies at the speed and volume required to deliver the experiences that are expected by customers”.
Conversational AI uses predictive analytics to determine the next “best step” in the customer or employee journey.
Finally, the AI app uses machine learning to accept corrections and learn from each experience, which enables it to produce better and more accurate responses in the future.