Towards a Domain-Specific Modeling Language for Streamlined Change Management in AI Systems Development

Requirements in AI systems, like in traditional software systems, are rarely fixed at the start of a project, as changes are often necessary and difficult to avoid. However, AI software systems face unique challenges, including constant adaptation to evolving data patterns, uncertainty and ambiguity in requirements due to the involvement of multidisciplinary teams, and the frequent need for model retraining. These distinctive sources of requirement changes, combined with current development practices, further complicate the process. Current practices in AI system development often separate machine learning (ML) and non-ML module development, leading to a lack of systematic coordination during changes. To address the challenges in Requirement Change Management (RCM) arising from this lack of co-development, this paper proposes leveraging process modeling within a Model-Driven Engineering (MDE) approach to streamline RCM in AI development. Specifically, we introduce a Domain-Specific Modeling Language (DSL) tailored for the AI engineering process. This DSL aims to enhance traceability, standardize terminology across multidisciplinary teams, and provide the flexibility needed to manage the dynamic nature of requirement changes effectively.