Summary of Guardians of M365 Governance Ep.22
In Episode 22 of the Guardians of M365 Governance monthly webcast, Ragnar Heil (@ragnarh), Joy Apple (@JoyOfSharePoint), and I welcome guest Sue Hanley—renowned information architect and Microsoft MVP—joins to explore the evolution of Information Architecture (IA) in the Microsoft ecosystem and how it’s being reshaped by AI and Copilot. Sue traces her professional roots from knowledge management and data modeling to intranet design, emphasizing that successful IA begins with people and processes, not technology. She notes that while classic IA principles like simplicity, mutual exclusivity, and clarity still apply, the role of IA has expanded alongside SharePoint’s growth from hierarchical site structures to more dynamic, search-driven and hub-based models.
The conversation dives into content governance and data hygiene, where Sue stresses that “cleaning before organizing” is essential in the AI era. She argues that accurate, reliable, and current content outweighs excessive tagging or complex taxonomies. Outdated and duplicated files—especially those stored in multiple locations or with poor naming conventions—undermine both search and AI effectiveness. Her practical recommendations include applying “Marie Kondo” and “Hillary Clinton” rules (“all content left behind”) during migrations, archiving old data below the search line, and allowing human review before automation. This approach ensures that organizations retain only relevant, high-value information, which in turn improves AI and Copilot outcomes.
Looking ahead, Sue highlights how AI will elevate IA’s importance rather than diminish it. Metadata, long the backbone of search and automation, remains vital for RAG (retrieval-augmented generation) and content classification—even if current AI tools use it imperfectly. She predicts that SharePoint agents and other AI-driven assistants will increasingly rely on well-structured metadata and clean architectures to manage, generate, and verify content at scale. Her closing advice is to start with the business problem: identify critical content, align IA with organizational goals, and maintain strong governance to ensure that AI enhances—not replaces—human intelligence in information management.
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