Unveiling the impact of employee-AI collaboration on help-seeking behavior among service employees in china: A social cognitive perspective

As employee-artificial intelligence (AI) collaboration becomes increasingly prevalent, understanding how it shapes employees' interpersonal dynamics has become imperative. Professional help-seeking, as an interpersonal behavior, plays a critical role in fostering employees' social connections and well-being, particularly in AI-embedded workplaces. However, research on how employee-AI collaboration influences professional help-seeking remains limited, constraining a comprehensive understanding of its consequences. Drawing on social cognitive theory, this study develops and tests a theoretical model to explain how and under what conditions employee-AI collaboration affects employees' help-seeking behavior. We propose that employee-AI collaboration negatively predicts professional help-seeking by increasing psychological availability, and that organizational AI readiness amplifies this effect. Using three-wave survey data from 303 service employees in China, our hypotheses were supported. The results show that employee-AI collaboration reduces professional help-seeking both directly and indirectly by enhancing psychological availability. Moreover, this negative relationship is further strengthened when organizational AI readiness is high. This study provides empirical evidence for a more nuanced understanding of the consequences of employee-AI collaboration and offers new theoretical insights into how organizations can effectively manage interpersonal behaviors in the AI era.