Hey all, I recently added a section in the DLP part of the classroom for a workbook with all of my DLP standard templates. The workbook contains: -DLP Templates by workload (Email, Files, Endpoint, AI, etc.) -The concept I created called "Protection Packs" which bundles the DLP policies by dataset/business outcomes -Discovery Questions you can use with customers -Accessibility by license. The key here is that I try to name and position these in a way that allows you to describe business outcomes with customers. DLP is one of the hardest things to rollout in any company in my opinion. What have your DLP projects been going like lately? What other content would you like to see?

hey All! I recently made a new script that is in the classroom that allows you to audit site permissions across all sites in a tenant. I usually do this as part of an AI readiness effort to look for overpermissioned sites, stale access, and a bunch of direct assignments that can be cleaned up. Let me know if you have any questions on it! About - SharePoint Advanced Management · Tminus365

AI automation workflows can get out of hand quick. I see companies building these highly complex flows all of the time now and they break quite frequently. It brings up a good point of truly understanding the ROI for your time and the ongoing maintenance for what you build before you dive in.

Hey everyone, I added a few new resources to the classroom. AI Usage Policy Template - This is a AI Usage policy template you can leverage for Copilot for an organization. It could be repurposed for other AI frontier models like Claude or GPT as well. AI Readiness Checklist and Hardening Guide - This is a technical checklist of controls to harden in Microsoft 365 specifically around AI usage in the organization. There is a natural progression path that can be followed over time. This derives an overall AI readiness score for a business. AI Executive Summary Template- Use this template after you fill out the AI readiness checklist to summarize the key findings to share with business leaders. I will be iterating these over time but wanted to share the initial control checks that I would recommend.

- · Skills and confidence. Only 27% of small businesses feel confident adopting AI effectively, versus 82% of mid-sized firms. - · Not knowing where to start. 62% of non-adopting small businesses cite a lack of understanding of AI's benefits, separate from skill, as their reason for staying out, and among the smallest firms 82% of those under five employees believe AI is not applicable to their business, which points to an awareness gap rather than a real incompatibility - · No strategy, just dabbling. Only about 8% of businesses reach advanced adoption; most invest in one or two use cases with no broader strategy, and 51% describe themselves as AI explorers testing tools without full commitment. Much usage is ad hoc with few policies behind it. - ·Wasted spend and tool sprawl. Small businesses spent an average of $2,340 on AI subscriptions in 2025, but roughly 31% of those tools went unused within 90 days, per Gartner. - ·Data readiness. Fragmented, siloed, inconsistent data weakens AI performance, and data quality and governance have become among the largest adoption barriers, with three of four organizations admitting their governance has not kept pace with adoption. - · Trust, security, and measurement. Security and risk concerns are the top barrier to scaling agentic AI, with inaccuracy and cybersecurity the most cited risks, data security is the leading AI concern for 44% of owners, followed by cost of implementation at 41%, and AI is uniquely hard to measure because it sits inside larger workflows rather than running as a standalone process.