This paper presents a framework for structuring Human-AI teams in learning factories, focusing on the AI’s role as an instructor and knowledge facilitator. As learning factories evolve into key training grounds for Industry 4.0, the integration of AI systems that guide human participants has the potential to enhance training efficiency and operational effectiveness. The framework emphasizes the AI’s ability to instruct human participants using a pre-structured knowledge base comprising documents, videos, and images, supported by a semantic ontology for precise interpretation and delivery of information. By acting as a knowledge facilitator, the AI not only instructs new participants but also adapts its communication style based on individual and group needs, ensuring that all team members benefit from personalized guidance. This architecture includes essential components such as intuitive interfaces for seamless AI-human interaction, explainability tools to ensure transparency in AI decisions, and automated decision-making processes to manage routine tasks. Human participants maintain oversight of critical decision points, fostering trust within the team. The framework is applied to a specific scenario in the WERK 150 learning factory at Reutlingen University, demonstrating how Human-AI teams can be established to optimize training, communication, and efficiency. By focusing on AI’s role as an instructor, this approach provides a structured method for implementing AI-driven training systems in real-world manufacturing environments.