Building Information Architecture for AI Compliance

This white paper presents a comprehensive guide for IT and data leaders in regulated industries on establishing an effective information architecture to support compliance in AI systems. It outlines the critical need for structured content and metadata governance to ensure transparency, traceability, and control in AI outputs. The document discusses the challenges faced by organizations in maintaining compliance, particularly in sectors such as life sciences, financial services, and energy, where regulatory bodies require clear audit trails and explainability. Key topics include the importance of metadata, taxonomy, and content models in creating a reliable foundation for AI initiatives. The paper also highlights the risks associated with unstructured content and provides design patterns for building compliant Retrieval-Augmented Generation (RAG) systems. By emphasizing the necessity of a governed information foundation, the white paper aims to equip organizations with the tools needed to navigate the complexities of AI compliance effectively.