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Human-AI Collaboration in Software Development Activities: Perspectives of Agile Practitioners
Conference proceeding   Open access   Peer reviewed

Human-AI Collaboration in Software Development Activities: Perspectives of Agile Practitioners

Daniel Planötscher, X Wang, M Adil, P Gregory and S Larimian
Agile Processes in Software Engineering and Extreme Programming: 27th International Conference on Agile Software Development, XP 2026, São Paulo, Brazil, April 8–11, 2026, Proceedings, Vol.578, pp.274-289
Lecture Notes in Business Information Processing, 578
27th International Conference on Agile Software Development, XP 2026 (São Paulo, 08/04/2026–11/04/2026)
2026
Handle:
https://hdl.handle.net/10863/52188

Abstract

Human-AI Collaboration Agile software development Software Development Activities Generative AI
While Generative AI (GenAI) has rapidly transformed software development and GenAI tools receive widespread adoption, how humans and AI should collaborate has become a focal point for Agile practitioners, whose values emphasise teamwork and collaboration. Yet, despite growing interest, research on human-AI collaboration in software engineering, especially within Agile contexts, remains limited. Our study investigates Agile practitioners' perceptions of collaborating with GenAI in software development activities. We conducted a survey with 73 Agile practitioners, revealing how they currently collaborate with GenAI across various activities and how they expect this collaboration to evolve. Key findings include that GenAI is currently not a substantial part of real-world workflows, being either unused or limited to an assistant role, but that there is a clear tendency towards greater AI involvement in the future, with practitioners increasingly viewing AI as a collaborator rather than merely a tool. These findings advance our understanding of human-AI collaboration in Agile settings and can guide both future research and the practical adoption of GenAI in Agile environments.
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https://link.springer.com/chapter/10.1007/978-3-032-22375-3_17View

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