Generative AI, Job Satisfaction and Type of Work

This study examines how generative artificial intelligence (GenAI) relates to job satisfaction among employees in the financial services sector, considering differences across types of work. Drawing on socio-technical systems theory, job satisfaction is conceptualized as an emergent outcome shaped by the alignment between technological change and organizational conditions. The analysis is based on a survey of 433 white-collar employees in Poland’s financial services industry and employs ordered logit models. The findings show that job satisfaction is positively associated with organizational support for AI and leadership effectiveness in managing AI-driven change, whereas individual enthusiasm toward GenAI is not positively related to satisfaction. Moreover, AI-related technostress is more strongly associated with lower job satisfaction in roles with higher exposure to AI-driven task transformation. Overall, the results highlight the contingent nature of GenAI’s impact on job satisfaction and emphasize the importance of socio-technical alignment in AI-enabled work environments.