The Influence of Intelligent Automation on Employees' Sense of Meaningfulness at Work

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The past decade witnessed an accelerated adoption of Intelligent Automation (IA) technologies by organizations in nearly every sector of the economy (Amalean et al., 2018). While organizations compete to attract and retain talent, the effects of IA on employees have not been investigated thoroughly. Grounded in Hackman & Oldhamâ s (1976) Job Characteristics Model (JCM), this study investigates the influence of IA deployment on employeesâ sense of Meaningfulness at work. In this study, IA was posited to moderate the relationship between the three job characteristics in the JCM (Skill Variety, Task Identity, and Task Significance) and sense of Meaningfulness at work. This study adopted a cross-sectional design that surveyed 505 working adults in the U.S. The results indicate that IA did not influence employeesâ sense of Meaningfulness at work. However, the negative perceptions that IA is here to eliminate jobs within organizations and replace employees with robots and applications was not found either. Overall, the influence of IA in the workplace is a relatively new phenomenon and more work is needed both from an academic and practitioner standpoint.

Artificial Intelligence and Robotics, Business Administration, Management, and Operations, Human Resources Management, Management Sciences and Quantitative Methods, Technology and Innovation, Intelligent Automation, Robotic Process Automation, Machine Learning, Artificial Intelligence, Job Characteristics Model, Job Diagnostic Survey, Work Meaningfulness, Employee Satisfaction