Adaptive Emotional Intelligence in AI-Powered Contact Centers

Abstract

As digital technologies develop, conversational artificial intelligence (AI), as well as human/machine workflow hybrid models, are being increasingly implemented in contact centers. Emotional intelligence—the ability to detect, understand, and respond to human emotional states—has remained largely absent from these automated systems. This article presents an Adaptive Emotional Intelligence (AEI) framework for AI-assisted contact centers that dynamically adjusts tone, content, and conversation methodology based on multimodal emotional signals. The AEI framework incorporates affective computing, reinforcement learning, and contextual reasoning to enable virtual agents and human agents to engage empathetically and at scale. Evidence from studies of affective computing and customer experience suggests that AEI could substantially improve customer satisfaction, reduce escalations, and enhance first-call resolution. The article discusses issues of architecture, data ethics, and longer-term effects on responsible and emotionally sustainable automation.