Intelligent technology and enhanced well-being: can artificial intelligence mitigate digital overload?

Abstract Artificial Intelligence (AI) technology plays a pivotal role in shaping discussions about the future of work. The rapid evolution of AI continues to transform the responsibilities of human resource (HR) managers by redefining how employees interact with technology. This research examines the impact of AI, emphasizing its capacity to enhance employee well-being and efficiency, while also acknowledging its tendency to lead to technology-related overload. Employers are encouraged to prioritize employee well-being by setting realistic goals, providing adequate training, and managing technological demands effectively. A total of 306 valid responses were collected from employees in technology-based organizations. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4 software to test both direct and indirect relationships. Findings indicate that while AI adoption positively influences organizational efficiency, it can also lead to techno-overload, which negatively impacts employee well-being. By highlighting the mediating role of techno-overload, this study offers empirical insights into how organizations can strike a balance between technological advancement and human sustainability. Owing to the reliance on self-report measures for the study constructs, there is a potential for respondent bias, which may compromise the objectivity of the data. The research contributes to the growing body of knowledge on AI in the IT industry by offering theoretical and practical implications for aligning AI implementation with employee well-being and organizational success. The study contributes to the growing body of knowledge on AI in the IT sector by using the TAM model to examine the development of AI technology. It also explores the challenges this advancement creates for employees, focusing on their well-being and its impact on organizational success. The study also identifies current research trends in this field and provides insights into future research directions.