Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow
Rasmus Ulfsnes, Nils Brede Moe, Viktoria Stray, Marianne Skarpen

TL;DR
This paper presents an empirical study on how generative AI tools like ChatGPT and Copilot are transforming software development workflows, collaboration, and productivity, highlighting significant shifts in developer practices and team dynamics.
Contribution
It provides new empirical insights into the impact of GenAI on software development workflows, collaboration, and developer motivation, based on interviews with industry professionals.
Findings
GenAI enables more efficient and motivated developers.
It accelerates learning and reduces repetitive tasks.
It alters team collaboration dynamics.
Abstract
Generative AI (GenAI) has fundamentally changed how knowledge workers, such as software developers, solve tasks and collaborate to build software products. Introducing innovative tools like ChatGPT and Copilot has created new opportunities to assist and augment software developers across various problems. We conducted an empirical study involving interviews with 13 data scientists, managers, developers, designers, and frontend developers to investigate the usage of GenAI. Our study reveals that ChatGPT signifies a paradigm shift in the workflow of software developers. The technology empowers developers by enabling them to work more efficiently, speed up the learning process, and increase motivation by reducing tedious and repetitive tasks. Moreover, our results indicate a change in teamwork collaboration due to software engineers using GenAI for help instead of asking co-workers which…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsScientific Computing and Data Management
