Organizations are rapidly adopting Generative Artificial Intelligence 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 and a significant research gap: the paradoxical effect of generative Artificial intelligence, where technological advancement undermines employee psychological safety, has been insufficiently studied. This study directly addresses 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 27 articles with the Best-Worst Method applied to the judgments of eight organizational experts. Findings reveal a clear contrast: while knowledge management, dynamic content generation, and workflow automation are confirmed as positive drivers of job engagement, their benefits are significantly offset by specific risks. Ethical concerns, privacy breaches, and widespread distrust emerge as significant negative factors that substantially weaken engagement, resulting in technostress, cognitive overload, and job insecurity. Based on these findings, we propose a conceptual-empirical framework for human-centered generative Artificial intelligence integration. The study concludes that without implementing robust data governance and specific measures to manage technostress, the potential of generative Artificial intelligence will not be realized, leading to widespread and persistent employee disengagement.