Perceived AI Efficacy and Its Impact on Organizational Integration and Employee Attitudes: A Management Perspective

The strategic integration of Artificial Intelligence (AI) into organizational operations has become a pivotal area of interest for management scholars and practitioners alike. This research delves into the multifaceted impact of AI on employee efficiency and job satisfaction, with a specific focus on the Chinese workforce. By examining the determinants of perceived AI efficacy, this study sheds light on the intricate interplay between humanlikeness, adaptability, quality, and the affective responses of anxiety and insecurity among employees. Employing a quantitative methodology with a sample size of 512, this investigation leverages a locally validated scale and advanced statistical techniques, including Support Vector Machine (SVM) modeling, Lasso regression, and mediation analysis, to elucidate the dynamics of AI integration within work settings. The results underscore the positive influence of AI's humanlikeness, adaptability, and quality on enhancing the perceived personal utility of AI, counterbalanced by the negative impacts of AI-induced anxiety and job insecurity. The Lasso regression model, with an impressive R-squared value of 0.767, robustly identifies the key drivers of AI utility, providing a clear roadmap for management to navigate AI integration effectively. Furthermore, the mediation analysis reveals the pivotal mediating roles of AI use anxiety and job insecurity, offering critical insights into how these factors influence the efficacy of AI within an organizational context. This study enriches the management literature by providing empirical validation for the proposed hypotheses and by offering actionable guidance for the design and deployment of AI systems that are attuned to human attributes. It underscores the imperative for organizations to proactively address employee concerns related to AI, thereby optimizing the integration process and leveraging AI's full potential to enhance operational efficiency and job satisfaction. The findings also pave the way for future research into the subtleties of AI-human dynamics and contribute to the formulation of effective AI management strategies within the workplace.