Predictive analysis of the psychological state of charismatic leaders on employees' work attitudes based on artificial intelligence affective computing

Abstract

With the progress of social production, the competition for talents among enterprises is fierce, and the market often lacks capable leaders, which leads to the lack of management of enterprise employees and cannot bring more economic benefits to enterprises. Traditional leaders make subordinate employees work actively and achieve the common goal of the enterprise by exerting their own leadership characteristics and observing their subordinates, but they cannot take care of the psychological state of each employee, resulting in the employee's work efficiency is not very high. In recent years, charismatic leadership has become an important economic leader in the new era, and the theoretical spirit of charismatic leadership can well guide employees to work actively. Artificial intelligence affective computing can well identify the psychological state of the subject, and the combination of artificial intelligence affective computing and charismatic leadership can achieve effective management of employees through the predictive analysis of employees' psychological state. This paper compares the psychological state prediction analysis of employees' work attitudes between charismatic leaders based on artificial intelligence affective computing and traditional leaders through experiments. The results show that: charismatic leaders based on artificial intelligence affective computing predictive analytics can improve sensitivity to employee needs, resulting in an 8.2% increase in employee trust in leadership, a 4.4% increase in employee commitment to achieving organizational goals, and a 19.3% increase in employee job satisfaction. The psychological state prediction analysis of charismatic leaders based on artificial intelligence affective computing on employees' work attitudes can improve the work efficiency of employees and the economic benefits of enterprises.

Shaping the Future Together: The Inaugural Vision for AI and Tech in Behavioral and Social Sciences

“…These studies showcase AI's potential in improving human resource management practices and understanding the emotional aspects of decision-making in organizations (AllenBecky et al, 2021;Fan et al, 2023;Zhou et al, 2022). In the realm of patient care and mental health, studies by Hong et al (2021), Liu & Song (2022), and Lei et al (2023) demonstrate AI's capacity to enhance patient care, support mental well-being, and provide comprehensive intervention strategies through personalized interventions (Hong et al, 2021;Lei et al, 2023;Liu & Song, 2022).…”