Opportunities and Limitations of GenAI in RE: Viewpoints from Practice
Anne Hess, Andreas Vogelsang, Xavier Franch, Andrea Herrmann, Sylwia Kopczy\'nska, Alexander Rachmann

TL;DR
This paper presents empirical insights from industry practitioners on the practical applications, benefits, challenges, and training needs associated with using Generative AI in requirements engineering processes.
Contribution
It provides the first comprehensive industry-based evidence on GenAI's practical use in RE, highlighting real-world benefits, limitations, and skill development needs.
Findings
Practitioners see GenAI as beneficial for requirements elicitation and analysis.
Concerns include accuracy, trust, and ethical issues in GenAI outputs.
Training is needed to effectively integrate GenAI into RE workflows.
Abstract
Context and motivation: With the rapid advancement of AI technologies, there is an increasing need to understand how AI can be effectively integrated into RE processes. In recent years, several studies have explored the potential and challenges of applying GenAI to support or even automate RE-related activities. Question/problem: Despite the existing body of knowledge on AI's potential for supporting RE activities, there is limited evidence on its practical applicability and limitations from an industry perspective. Principal ideas/results: To address this gap, we conducted a survey with RE practitioners in collaboration with the IREB Special Interest Group on AI & RE. In addition to describing our research methodology and survey design, we present insights from our quantitative and qualitative data analyzes. These insights include practitioners' perspectives on current usage scenarios,…
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