Generative Artificial Intelligence in Agile Software Development Processes: A Literature Review Focused on User eXperience

Generative Artificial Intelligence in Agile Software Development Processes: A Literature Review Focused on User eXperience

연구 분야: Software Development

학회: International Conference on Human-Computer Interaction

The integration of Generative Artificial Intelligence (GenAI) into Agile Software Development (ASD) is reshaping the way development teams automate tasks, optimize processes, and enhance user experience (UX). This study presents a systematic literature review to analyze the impact of GenAI on ASD, focusing on three research questions: (1) How can GenAI tools optimize user experience in agile software development projects? (2) What are agile teams’ main challenges when integrating GenAI tools into software development projects? and (3) What stages of the agile software development cycle benefit from implementing GenAI tools? A total of 21 relevant studies published between 2020 and 2024 were selected and analyzed. Findings indicate that GenAI improves UX by facilitating automated test generation, personalized user interfaces, and enhanced documentation processes. However, challenges such as data quality, model transparency, security vulnerabilities, and team resistance hinder its adoption. Moreover, the research highlights that GenAI contributes across multiple ASD phases, including planning (requirement analysis and user story generation), implementation (automated code generation and debugging), testing (self-generated test cases), maintenance (documentation and refactoring), and retrospectives (data-driven team performance analysis). Despite its growing adoption, the study reveals a gap in empirical evaluations of GenAI’s long-term impact on Agile methodologies. Future research should explore hybrid frameworks that balance automation and human oversight, longitudinal studies on GenAI’s adoption trends, and strategies to ensure ethical and bias-free AI implementation in Agile environments. The findings contribute to a deeper understanding of GenAI’s transformative role in software development and provide practical insights for industry professionals and researchers.