Splitting User Stories Into Tasks with AI -- A Foe or an Ally?

TL;DR

This study explores how Generative AI can assist in splitting user stories into tasks in agile development, showing potential benefits and current limitations.

Contribution

It provides empirical evidence on AI-assisted task splitting, highlighting the need for human oversight and hybrid approaches in agile workflows.

Findings

AI can generate more detailed task lists.

Participants prefer hybrid AI-human methods.

AI tools currently cannot fully replace developers.

Abstract

In agile software development, breaking down user stories into actionable tasks is a critical yet time-consuming process. This paper investigates the potential of Generative AI tools to assist in task splitting, aiming to enhance planning efficiency. We conducted a controlled experiment comparing traditional task-splitting methods with AI-assisted approaches using GitLab Duo. Our findings indicate that while current AI tools are not yet mature enough to replace developers, they can aid in generating more granular task lists and ensuring no important tasks are overlooked. Participants favored a hybrid approach, combining AI tools with conventional methods to maintain high accuracy in planning. This study highlights the potential benefits and limitations of integrating Generative AI into agile development processes, suggesting that AI tools can serve as valuable aids in task splitting, provided there is human oversight to filter out irrelevant tasks.