Still just personal assistants? – A multiple case study of generative AI adoption in software organizations

Generative AI (GenAI) is argued to transform software engineering (SE) in various ways, and GenAI tools show promise for various SE tasks. Software organizations across the globe are currently exploring the use of GenAI for SE. While numerous studies have recently been published on GenAI, few studies have looked at the adoption of these tools and their usage from an organizational point of view, focusing instead on individual users. Our objective is to understand how organizations adopt these tools and what their impacts are in industrial contexts, with a focus on the European perspective. We conducted a multiple case study of seven European companies. We collected data through semi-structured interviews (n=15), as well as through longitudinal observation in one case company. All data were analyzed using thematic analysis. We analyzed 28 transcripts, resulting in 456 quotations and 557 code occurrences split between 66 individual codes that were categorized under 6 high-level themes. We identified 25 types of tasks GenAI was currently being used for in our case organizations. We identified 12 benefits for GenAI in SE and 10 adoption and use challenges. Key adoption challenges for organizations include data privacy and legislative concerns, the emerging and fast-moving market of GenAI tools, difficulty of measuring the positive impact of the tools, and potential change resistance. For individuals, the key challenges are related to prompting, such as understanding what a good prompt is, and how to write prompts for specific tasks. GenAI adoption is becoming widespread in SE, but good practices and use cases are still emerging. While GenAI can potentially produce various benefits in SE, companies and individual users are facing various challenges in making the most of GenAI in SE. Our results provide insights into the current state of practice. • Exploratory case study of 7 European companies; 1 more in-depth case supported by 6 other cases. • Provides insights into the current state of industrial practice on GenAI for software engineering. • We identify 25 tasks for which generative AI is currently used. • We identify challenges faced by both individual users and organizations when adopting GenAI tools. • Few organizations seem to currently use GenAI on a process level in software engineering.