Conversational AI involves the technologies behind application interfaces that accept human input in natural language as text or voice and produce context-appropriate responses.
Conversational AI uses Natural Language Processing (NLP) technologies and Machine Learning (ML) to provide an engaging interface for applications. Conversational interfaces are able to interpret inputs using Natural Language Understanding (NLU) technology and respond with a context-appropriate output or action.
Input may be in text or speech form, and the output generally follows the form of the input (e.g., a typed input results in a text output; a voice input garners a verbal response). Internally, speech is converted to text on input, and voice is synthesized from text on output. When triggering a system to take an action, these actions can range in complexity from raising the volume on the system to triggering a secure financial transaction.
Conversational AI is rapidly becoming more sophisticated, and is on track to enable more effective employees, processes, and enterprises.
Although conversational AI should not be viewed as a solution, as technologies are becoming more advanced, it can be part of a solution to enabling conversations with customers, partners, and employees. This research note overviews four trends contributing to the adoption of conversational AI and discusses four vendors who are offering conversational tools.
Conversational AI has the potential to transform customer, employee, and partner experiences. Register for this upcoming webinar to learn more about the latest advances in conversational AI and where to get started in your enterprise.