Paper Type
Complete
Paper Number
PACIS2026-1338
Description
Digital innovation is produced through software development work systems, and Generative AI (GenAI) transforms these systems in ways that reshape work practices and learning trajectories differently for junior and senior developers. While prior research highlights productivity benefits and emerging challenges, it offers limited insight into how these transformations differ across developer roles. This study addresses this gap by examining how GenAI reconfigures the structure and performance of software development as cyber-human work systems. Drawing on a qualitative, multi-perspective design involving 35 developers, we thematically analyze how AI-enabled capabilities reshape tasks, responsibilities, learning dynamics, and innovation-relevant outcomes. The findings show that junior developers experience productivity gains and AI-assisted learning, whereas senior developers leverage GenAI for architectural reasoning, strategic insourcing, and high-level problem-solving. These role-differentiated effects reveal how GenAI redistributes expertise, reshapes capability development, and influences digital innovation performance. The study advances understanding of digital transformation and emerging future digital work skills.
Recommended Citation
Balasuriya, Balasuriya Lekamalage Prasanna; Hjalmarsson Jordanius, Anders; and Juell-Skielse, Gustaf, "Generative AI and the Transformation of Software Development Work Systems in Digital Innovation: A Comparative Study of Junior and Senior Developers" (2026). PACIS 2026 Proceedings. 3.
https://aisel.aisnet.org/pacis2026/di_entren/di_entren/3
Generative AI and the Transformation of Software Development Work Systems in Digital Innovation: A Comparative Study of Junior and Senior Developers
Digital innovation is produced through software development work systems, and Generative AI (GenAI) transforms these systems in ways that reshape work practices and learning trajectories differently for junior and senior developers. While prior research highlights productivity benefits and emerging challenges, it offers limited insight into how these transformations differ across developer roles. This study addresses this gap by examining how GenAI reconfigures the structure and performance of software development as cyber-human work systems. Drawing on a qualitative, multi-perspective design involving 35 developers, we thematically analyze how AI-enabled capabilities reshape tasks, responsibilities, learning dynamics, and innovation-relevant outcomes. The findings show that junior developers experience productivity gains and AI-assisted learning, whereas senior developers leverage GenAI for architectural reasoning, strategic insourcing, and high-level problem-solving. These role-differentiated effects reveal how GenAI redistributes expertise, reshapes capability development, and influences digital innovation performance. The study advances understanding of digital transformation and emerging future digital work skills.
Comments
09-Transformation