Engineering Better Requirements: Understanding the Impact of GenAI on Task Performance and Quality in Requirements Engineering

Abstract

In order to deliver high-quality software systems, organizations utilize Requirements Engineering (RE) as a foundation for aligning development with stakeholder needs. With advances in Generative Artificial Intelligence (GenAI), potential emerges to augment RE processes to improve both task completion time and requirements quality. As GenAI-powered tools become more common in industry practice, our research examines under which circumstances GenAI supports RE tasks. Through our online experiment with 41 RE professionals from a manufacturing company, we demonstrate that GenAI assistance significantly reduces task completion time across different complexity levels and improves quality, particularly in simpler tasks. These results indicate that while GenAI effectively enhances RE efficiency in all contexts, its contribution to quality varies with task complexity. This suggests that organizations should strategically implement GenAI tools in RE workflows, recognizing both their productivity benefits and the continued importance of human expertise for more complex requirement scenarios.