Communication Challenges and Practices in AI-based Software Systems: An Exploratory Study

The integration of AI-based systems into software systems poses technical and organizational challenges, especially regarding communication between multidisciplinary teams. This qualitative study, grounded in the Socio-Technical Grounded Theory, investigates communication practices during the development and integration of AI-based systems. Conducted in two cycles with a total of 15 semistructured interviews, the study identifies five key communication challenges: lack of shared technical vocabulary, misaligned expectations and priorities, unstructured communication practices, and inadequate use of tools. These issues often lead to misunderstandings, rework, and miscoordination across teams. To address them, participants recommended strategies such as shared glossaries, regular alignment meetings, and standardized collaborative tools. These findings contribute to the understanding of socio-technical dynamics in ML-based software projects and offer practical recommendations to improve integration workflows and guide future Software Engineering practices.