The Role of Generative AI in Software Development Productivity: A Pilot Case Study

TL;DR

Addresses the scarcity of empirical evidence on how generative AI affects productivity in real-world software development. It reports a pilot case study in a large software company with 13 participants across roles, collected via four weeks of questionnaires and Slack observations, analyzed qualitatively. Findings indicate generally positive perceived productivity gains, particularly in time savings and content generation, alongside reliability and security challenges. The work provides initial empirical insights, guides industrial practice, and outlines directions for broader, multi-role studies with more robust metrics. Overall, it lays groundwork for understanding how generative AI can be integrated into software development workflows to enhance efficiency and knowledge work.

Abstract

With software development increasingly reliant on innovative technologies, there is a growing interest in exploring the potential of generative AI tools to streamline processes and enhance productivity. In this scenario, this paper investigates the integration of generative AI tools within software development, focusing on understanding their uses, benefits, and challenges to software professionals, in particular, looking at aspects of productivity. Through a pilot case study involving software practitioners working in different roles, we gathered valuable experiences on the integration of generative AI tools into their daily work routines. Our findings reveal a generally positive perception of these tools in individual productivity while also highlighting the need to address identified limitations. Overall, our research sets the stage for further exploration into the evolving landscape of software development practices with the integration of generative AI tools.