🤖 AI Summary
This study reveals a systemic misalignment between the practical adoption of generative artificial intelligence (GenAI) in agile software development and existing organizational policies. Drawing on the Technology–Organization–Environment (TOE) framework, the research synthesizes findings from 17 semi-structured interviews and document analyses across three German companies, employing both within-case and cross-case thematic analysis. The results indicate that GenAI is predominantly leveraged for ideation, documentation, and code assistance, enhancing both efficiency and creativity, yet its deployment is constrained by data privacy concerns, high validation costs, and insufficient governance mechanisms. The study underscores the necessity of coherently aligning technological capabilities, organizational structures, and environmental contingencies within the TOE framework to enable compliant and effective GenAI integration, thereby offering both theoretical insights and practical pathways to bridge the gap between policy and practice.
📝 Abstract
Context: The rapid emergence of generative AI (GenAI) tools has begun to reshape various software engineering activities. Yet, their adoption within agile environments remains underexplored. Objective: This study investigates how agile practitioners adopt GenAI tools in real-world organizational contexts, focusing on regulatory conditions, use cases, benefits, and barriers. Method: An exploratory multiple case study was conducted in three German organizations, involving 17 semi-structured interviews and document analysis. A cross-case thematic analysis was applied to identify GenAI adoption patterns. Results: Findings reveal that GenAI is primarily used for creative tasks, documentation, and code assistance. Benefits include efficiency gains and enhanced creativity, while barriers relate to data privacy, validation effort, and lack of governance. Using the Technology-Organization-Environment (TOE) framework, we find that these barriers stem from misalignments across the three dimensions. Regulatory pressures are often translated into policies without accounting for actual technological usage patterns or organizational constraints. This leads to systematic gaps between policy and practice. Conclusion: GenAI offers significant potential to augment agile roles but requires alignment across TOE dimensions, including clear policies, data protection measures, and user training to ensure responsible and effective integration.