2026-10-05T21:32:40Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:27977 2026-10-05T06:44:02Z ddc:004 open_access

Out of Place in My Own Work: How Generative AI Displaces Software Engineers Tavantzis, Theocharis Lambiase, Stefano Russo, Daniel AI-induced displacement Generative AI Human-centered AI Software Engineering Background. Generative AI (GenAI) makes software engineers faster, yet a growing number of them report feeling less like engineers. They describe feeling disconnected from their own code, uncertain about their skills, and uneasy about what their profession is becoming. Prior studies capture fragments of this experience in isolation, yet no shared concept or framework describes it as a whole. Aim. Drawing on postphenomenology, Floridi’s re-ontologization of the infosphere, and Feenberg’s critical theory of technology, we introduce AI-induced displacement: the multi-dimensional way in which GenAI tools unsettle engineers' sense of craft, identity, and professional belonging. Method. We interviewed 21 software engineers across different roles and organizations, and analyzed their accounts through thematic analysis. Results. We identify six dimensions of displacement, concerning (i) how engineers justify and adopt AI-generated solutions, (ii) shifts in professional identity, (iii) tensions with normative and ethical standards, (iv) disruptions to individual focus and cognitive flow, (v) changing dynamics of recognition and collaboration within teams, and (vi) the erosion of intrinsic meaning and long-term professional sustainability. Conclusions. This typology offers researchers a theoretically grounded lens for investigating the human side of GenAI adoption in software engineering, and helps practitioners design integration strategies that foreground augmentation rather than replacement. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Theocharis Tavantzis and Stefano Lambiase and Daniel Russo 2026 Is Part Of LIPIcs, Volume 394, 20th International Symposium on Empirical Software Engineering and Measurement (ESEM 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ESEM.2026.9 urn:nbn:de:0030-drops-279777 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESEM.2026.9 eng https://creativecommons.org/licenses/by/4.0/legalcode