AI Disruption in the Workplace : Navigating Employee Engagement in an Age of Automation

Sammanfattning

The increasing integration of Artificial Intelligence (AI) is reshaping workplace dynamics, particularly within logistics, where automation plays a crucial role in operational efficiency (Bankins et al., 2024). While AI enhances productivity and streamlines processes, it also presents challenges in maintaining employee engagement, requiring managers to adapt managerial strategies to support motivation and workforce adaptability (Parker & Grote, 2022). This thesis investigates how managers navigate employee engagement in an AI-integrated logistics environment, applying Kahn’s (1990) employee engagement framework and the Job Demands-Resources model (Bakker & Demerouti, 2007). Through qualitative interviews with managers across multiple hierarchical levels, departments, and countries, the study identifies key managerial strategies. These include redesigning tasks to foster meaningfulness, building psychological safety through transparent communication, and supporting employees’ availability through workload management and targeted training. Additionally, the research underscores the importance of human oversight in AI-driven workplaces and the role of adaptive leadership in reinforcing trust and motivation. By combining managerial perspectives with engagement theory, this study provides practical recommendations for managers facing AI-driven transformations, ensuring that technological advancements enhance rather than decrease employee engagement.