In recent years, Artificial Intelligence (AI) has gained significant attention across disciplines and industries, with the adoption of Generative Artificial Intelligence (GenAI) in organizations accelerating, particularly through the introduction of user-friendly conversational chatbots. While numerous studies have investigated either the factors influencing AI adoption within organizations or the effects of AI adoption on organizational performance, the role of human-centered factors in shaping its adoption and their subsequent impact on employee quality of working life remains largely unexplored. To address this gap, and drawing on socio-technical systems theory, this study proposes a theoretical model investigating the interplay between key human-centered factors, GenAI adoption, and employee quality of working life. Specifically, employee trust in GenAI is identified as a key human-centered antecedent of GenAI adoption. GenAI adoption is conceptualized through two main constructs: GenAI use and GenAI hedonic experience. Workplace well-being is used as the indicator of employee quality of working life. The model is tested using Partial Least Squares Structural Equation Modeling on survey data collected from 214 Italian professionals with experience in using GenAI in their work activities. The findings demonstrate that employee trust in AI positively influences both GenAI use and GenAI hedonic experience, and that these two factors, in turn, strongly impact workplace well-being. Additionally, while trust in AI also directly affects workplace well-being, its impact is weaker compared to the effects of GenAI use and GenAI hedonic experience. This study provides important practical implications for organizations aiming to improving employee well-being through the adoption of GenAI. Additionally, limitations of the study are discussed, along with suggestions for future research directions.