Summary of Guardians of M365 Governance Ep.23
In Episode 23 of the Guardians of M365 Governance monthly webcast, Ragnar Heil (@ragnarh), Joy Apple (@JoyOfSharePoint), and I welcome guest Jay Leask, a Principal Technical Architect at Microsoft, working in the Washington DC Microsoft Technology Center (MTC). In this episode, we explore how to make AI genuinely useful for “everyday work” rather than just massive, high-profile projects. Using Jay’s new “AI for Average Intelligence” podcast as a backdrop, the discussion reframes AI as a tool for reducing routine friction in Microsoft 365: clearing noisy inboxes, surfacing missed commitments, and turning meeting recordings into accurate, actionable summaries. The hosts emphasize that some of the biggest productivity gains come from solving small, repeatable tasks at scale, not from chasing sci-fi scenarios.
A major theme is how Copilot and AI fit into governance and information management. We highlight scenarios such as asking Copilot to summarize months of Teams meetings, chats, and emails for performance check-ins, or generating a prioritized table of messages that still need responses. We also draw a clear parallel between good governance and good AI usage: if you let your governance framework and AI agents handle the bulk of routine workload, humans can focus their attention on high-priority, high-sensitivity activities. The episode also touches on modern search, contrasting traditional keyword search with Copilot’s more contextual, vector-based approach, and showing how conversational, voice-driven interaction helps users move beyond “keyword thinking.”
The conversation closes by addressing two key concerns: keeping up with the rapid pace of AI innovation, and managing the risk of over-connecting data through MCP servers. The consensus is that most users don’t need to follow every AI announcement; instead, they should focus on the value within their role, while admins and specialists track relevant platform changes. On the compliance side, more connected data increases what AI can do, but also raises governance and security questions around scope, access, and appropriate use. We wrap things up by underscoring that AI adoption works best when it’s practical, approachable, and a little bit fun.
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