Emotionally adaptive AI assistants for managing distributed IT teams: conceptual foundations and integration methodology

The article explores the concept of emotionally adaptive artificial intelligent assistants (EAIS) for managing distributed IT teams. The innovation of the approach lies in the integration of neural networks capable of recognizing and interpreting the emotional states of developers through the analysis of communication channels, biometric data and patterns of work activity, followed by dynamic adaptation of work processes (workflow) in real time. Unlike existing AI agents that optimize operational costs, the focus of this concept is shifted to the psychophysiological aspects of labor productivity, which becomes critically important in the context of hybrid and geographically distributed teams. This paper substantiates the relevance of developing EAIA, analyzes the necessary technological components (affective computing, communication analysis, adaptive management systems), suggests a methodology for their integration, and discusses key implementation challenges. It has been established that the synthesis of achievements in the field of affective computing and IT management, which is in the initial stage of development, is a necessary condition for the implementation of the EAIA concept.