The AI Frontier: Mapping and Prioritizing the Drivers and Challenges of Generative AI in Employee Engagement

Organizations are rapidly adopting Generative Artificial Intelligence (GenAI) for significant productivity gains, yet they are often not ready for its serious negative impacts on the workforce. This creates a major challenge for management. There is a significant research gap regarding the paradoxical effect of GenAI, where technological advancement undermines the employee psychological safety. This study directly addressed this gap by investigating the overall effect of this dual impact on employee engagement. A mixed-methods design was employed, combining a PRISMA-compliant systematic review of ۲۷ articles with the Best-Worst Method applied to the judgments of eight organizational experts. Findings revealed a clear contrast. While knowledge management, dynamic content generation, and workflow automation were confirmed as positive drivers of job engagement, their benefits were significantly offset by specific risks. Ethical concerns, privacy breaches, and widespread distrust emerged as significant negative factors that substantially weaken engagement, resulting in technostress, cognitive overload, and job insecurity. Based on these findings, we proposed a conceptual-empirical framework for human-centered GenAI integration. The study concluded that without implementing robust data governance and specific measures to manage technostress, the potential of GenAI will not be realized, leading to widespread and persistent employee disengagement.

کلیدواژه ها:

Artificial Intelligence (AI) ، Employee Engagement ، Digital Human Resource Management ، Best&ndash ، Worst Method (BWM)