Emotion AI, also known as Affective AI, refers to the area of artificial intelligence where systems are designed to recognize, interpret, process and simulate human emotions. The goal is to allow machines to understand and respond to human emotions in a way that feels more intuitive and human-like. The techniques used in Emotion AI include facial expression analysis, voice tone analysis, physiological measurement (e.g., heart rate variability), and natural language processing. Integration with other systems like CRM and virtual assistants also facilitates emotionally-aware interactions. Using these various techniques to analyze emotions in real time has spawned new use cases for customer experience enhancements, employee wellness and many other areas, including entertainment, healthcare, automotive, retail and advertising and education.
Gartner defines the enterprise conversational AI platform market as the market for software platforms used to build, orchestrate and maintain multiple use cases and modalities of conversational automation. The enterprise conversational AI platform consists of: A capability layer providing runtime capabilities that include: Natural language understanding (NLU), Dialogue management, Channel integration, Back-end integration, Access control for platform users, Life cycle management; A tooling layer geared toward business users that includes: A no-code environment for building and maintaining, applications, Analytic tools for understanding dialogue flows, NLU intent and entity tuning tools, A/B flow testing tools.