GenAI Reshapes Expertise and Performance in System Administration

While Generative AI is often touted for its immediate productivity gains and automation capabilities, its deeper impacts on professional practices, particularly in fields like system administration, are still emerging. Through interviews with IT professionals, this research uncovers two significant, unanticipated socio-technical effects of GenAI integration into daily routines such as troubleshooting, scripting, and system verification. Firstly, the study identifies a "compression of traditional expertise pathways." GenAI acts as both a mentor and a "ladder-shortening" tool, accelerating task performance in unfamiliar areas. However, it may inadvertently reduce exposure to the foundational, hands-on debugging and failure cycles critical for developing deep technical expertise. Secondly, a "performance perception shift" is observed, where the speed of AI-assisted work resets expectations for productivity, potentially creating a "two-speed culture" and "productivity guilt" for necessary manual tasks. These findings raise crucial questions about expertise development, professional value assessment, and the role of human judgment in high-stakes technical environments.