Rana Abou Khamis, Hala Assal, Ashraf Matrawy — arXiv preprint (2026). 📄 Full text (arXiv)
Synthesis
Drawing on 14 semi-structured interviews with IT professionals, this study explores how GenAI integration reshapes professional practice in system administration — troubleshooting, scripting, and system verification.
Two unanticipated socio-technical findings: 'compression of traditional expertise pathways' — GenAI acts as both mentor-like tutor and 'ladder-shortening' tool, accelerating unfamiliar-domain task performance while reducing exposure to the foundational build-fail-debug cycles that historically built expertise.
'Performance perception shift': AI-assisted speed resets organizational and self-expectations, creating a 'two-speed culture' within teams and 'productivity guilt' — a metacognitive cost of AI-augmented work.
The findings extend concerns about cognitive offloading and skill decay from classroom settings to professional practice, with implications for professional training programs and workplace learning.
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Citation
APA: Abou Khamis, R., Assal, H., & Matrawy, A. (2026). Unanticipated effects of generative AI on expertise pathways and performance perception in system administration. arXiv:2607.28650.