Between Policy and Practice: GenAI Adoption in Agile Software Development Teams

Abstract Context: The rapid emergence of generative AI (GenAI) tools has begun to reshape software engineering practice. 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, role-specific 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 usage patterns or organizational constraints, leading to systematic policy-practice gaps and shadow IT behavior. Conclusion: GenAI offers significant potential to augment agile roles but requires alignment across TOE dimensions, including pragmatic policies, data protection measures, and user training to ensure responsible and effective integration.