Industrial process modeling is a crucial step in designing and optimizing manufacturing systems. However, it often presents significant barriers due to its complexity and the expert knowledge required. The Models for Manufacturing (MfM) methodology provides a structured approach to process modeling, with the Scope Model as its foundational ontological layer. This paper explores the potential of Large Language Models (LLMs), specifically GPT-4 from OpenAI, to assist or facilitate the creation of the Scope Model within an industrial case study. Conducted within the ADAPTA research project—focused on flexible and reconfigurable human-robot collaboration in manufacturing—this study examines AI-driven cooperative modeling to streamline process modeling, reduce effort, and enhance accessibility. Findings indicate that LLMs can support structuring the Scope Model while maintaining consistency and traceability. However, challenges such as validation, explainability, and integration with existing modeling tools remain. The paper discusses these limitations and potential future developments in AI-assisted modeling within the MfM framework.