Conversational AI (artificial intelligence) is a set of technologies that make it possible for computers to recognize and decipher various human languages, allowing humans to have conversations with digital systems. These AI technologies give voice to automated messaging and speech-enabled apps, facilitating communication between computers and humans in their ability to recognize speech and text, identify intent, and mimic human response. Successful conversational AI interactions depend on strong conversational design, and when done right, are virtually indistinguishable from human interactions, delivering conversational experiences that are easy and natural.

To comprehend and engage in human dialogue, conversational AI uses natural language processing (NLP) and other deep learning algorithms during customer engagement to determine what a customer is trying to say. Natural language understanding (NLU) can sift through conversation to decipher words and intent, work through grammatical and syntactical mistakes, and maintain context to comprehend what is said during an entire conversation in real time. Unlike speech recognition or text-to-speech technologies that record human speech as data, NLU focuses on the rearranging of unstructured data so that it can be understood and analyzed by a machine.

After intent is established, conversational AI uses machine learning to choose the appropriate response. Over time, as a result of customer interactions and guidance from human agents, conversational AI can recognize more variations of the intent, including the appropriate responses, improving user experience. After choosing a response, AI uses natural language generation to respond to incoming intents in a manner that is easily understood by the customer, either in text or by the artificial production of human speech using Natural Language Generation (NLG).

Conversational AI is used being used successfully in customer service environments, transforming the way companies communicate with their customers, and improving user experience.

Delivers a “more human” self-service design. When confronted with self-service options in a phone tree or with a chatbot, a customer’s first response is often to bypass them to get to a live agent. Using conversational AI humanizes the self-service experience, making it more enjoyable and productive for customers.
Improves customer service. Chat boxes are programmed to assist customers with a variety of requests, including product and purchase information, quickly and efficiently, without unnecessary human interaction. They also act as digital assistants when customer issues are more complex, quickly identifying and escalating the issue to the most qualified agent.
Easily scalable. Conversational AI evolves with a company. As service needs grow, digital assistants be added to perform a variety of functions, eliminating the need for human agents in some areas and reducing operating costs.
Optimizes data collection. Using sentiment analysis, conversational AI can assess a customer’s emotional needs, establish a personality profile for that customer, and target communication based on previous brand interactions. This valuable data helps companies discover more about their customers—from the products they choose, to the way they communicate with sales agents.

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