How does artificial intelligence impact employees’ engagement in lean organisations?

• Autores: Tortorella, Guilherme Luz; Powell, Daryl; Hines, Peter; Mac Cawley Vergara, Alejandro; Tlapa Mendoza, Diego; Vassolo, Roberto Santiago
• Año de publicación: 2024
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Artificial intelligence; Industry 4.0; Lean production; Employees’ engagement
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Driven by the digital transformation currently pursued by organizations, artificial intelligence (AI) applications have become more frequent. Nevertheless, its impact on employees’ behaviors and attitudes is still poorly known. As employees’ engagement (EE) is a key element for a successful Lean Production (LP) implementation, there is the need to understand such AI’s implications on EE in this scenario. This paper aims to investigate the impact of AI on EE in lean organizations. We performed a qualitative-empirical approach in which we first interviewed twelve academic experts to grasp the investigated problem. Then, we conducted a multi-case study in manufacturing organizations undergoing a LP implementation to refine such understanding based on the observation of real-world evidence. Identifying commonalities between these stages allowed the formulation of propositions for future theory testing and validation. Findings indicate that AI may positively impact EE dimensions (physical, cognitive, and emotional) in human-centered work environments, such as lean organizations, although not at the same extent. Results also suggest that employees’ psychological conditions (safety, meaningfulness, and availability) are positively affected by the relationship between AI and EE. The demystification of AI’s effect on EE helps practitioners anticipate potential issues that can impair the LP implementation in the Fourth Industrial Revolution era. As digital transformation evolves, organizations undergoing a LP implementation must learn how to cope with the integration of AI into their processes and benefit from it without undermining the principles and behaviors that commonly drive a lean organization.
Fil: Tortorella, Guilherme Luz. University of Melbourne; Australia
Fil: Powell, Daryl. Norwegian University of Science and Technology; Noruega
Fil: Hines, Peter. South East Technological University; Irlanda
Fil: Mac Cawley Vergara, Alejandro. Pontificia Universidad Católica de Chile; Chile
Fil: Tlapa Mendoza, Diego. Universidad Autonoma de Baja California (universidad Baja California);
Fil: Vassolo, Roberto Santiago. Universidad Austral. Instituto de Altos Estudios; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina