Artificial Intelligence and Emotional Intelligence in Employee Engagement: using Machine Learning to Improve Workplace Satisfaction
Year: 2026
Type: conference-paper
Abstract: There has been increasing awareness that what they do and how they do it has a deep impact on productivity, person interest and long-term satisfaction and well-being of the company as a whole. The classical humanistic approach is being deconstructed, and human ingenuity and heart feeling is replacing the former approach that organizations discover, practice and foment contact. This syncretic coupling of new AI technologies, specifically ML, with the principles of EI constitutes a game-changing prospect to introduce more responsible, sensitive and accommodative cultures in the workplace. Being data intensive, Artificial Intelligence can enable organizations to process huge volumes of employee data, draw patterns, and generate insights that would otherwise be information blind spots among people. Each of the sources and types of data, such as employee feedback, performance indicators, concentration indicators of a sentiment analysis of internal communications, social networks, and so on, can be analyzed using the Machine Learning models. This helps the HR professionals and management teams to predict the feeling of disengagement, understand what drives teams and therefore handle issues related to burnout, dissatisfaction or even isolation. The forecasting ability of AI allows forecasting and personal intervention in time to make employees feel noticed and attended. AI may well be able to count the numbers to identify efficiency and accuracy but it lacks the emotion sense that provides the touch that a human interprets in behavior. It is at this point that Emotional Intelligence can give us the solution to bridging the divide between AI-based strategies. Empathy, being a good listener and being mindful of your feelings and others is propagated by EI, which is converted into a real human relationship, trust and psychological safety. Companies can go even further than people analytics by incorporating EI into AI models and building systems that would more closely predict how workers may both feel and what they do. Consider AI-driven virtual assistants with the ability to understand natural language and respond in a sympathetic manner to sentiment identification and provide real conversation, mental health and guidance to the most human-like answer. Also, ML algorithms may be trained to detect emotional indicators of written or spoken communication to give managers real-time feedback involving the mood and emotional well-being of the team. Those prepare leaders to make such a turn in their own way, develop people skills, and create a culture of inclusion and appreciation at work. The wellbeing of any working environment is then a matter of two ratios and their derivatives where the first ratio is a ratio of AI, and the second ratio is a ratio of EI.
Institutions: Graphic Era University, COER University, Adamas University
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7203685828