AI Foundation Workshop
Follow-up Resources
Practical tools and guidance to help you put the right foundations in place before expanding AI use.
These resources were created as a follow‑up to the AI Foundation Workshop and reflect the same practical, business‑first approach discussed in the session.
Thank you again for participating in the AI Foundation Workshop. One of the recurring themes in our discussion was that AI adoption isn’t primarily a technology problem. It’s a clarity, control, and responsibility problem.
This page is a continuation of that conversation.
The resources below are designed to help you slow things down just enough to make good decisions, understand where AI is already influencing your organization, and put sensible guardrails in place before expanding usage further.
We’ll continue to update this page over time as guidance evolves
Start Here
AI Acceptable Use Policy - Starter Template
A practical place to begin - not a finished product.
During the workshop, many attendees asked for a starting point for an AI Acceptable Use Policy. This template is designed to help you begin internal conversations around expectations, responsibilities, and boundaries for AI use inside your organization.
This is not legal advice, and it’s not meant to be adopted without thought. Instead, it provides a practical foundation you can adapt to your business, your culture, and your risk tolerance.
This starter template is designed to:
Clarify what types of AI use are acceptable today
Set expectations for employee judgment and accountability
Reduce accidental data exposure or misuse
Create a shared baseline before broader AI adoption
Policies alone don’t create safety. But lack of clarity creates risk.
Supporting Resources
The resources below expand on themes we discussed during the workshop. They’re not meant to be completed all at once, but revisited as you think through how AI fits into your organization.
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Understanding Microsoft Copilot
Microsoft Copilot works within your existing Microsoft 365 environment, grounding responses in the data users already have access to. That makes it powerful. But also highly dependent on how well permissions, sharing, and data organization are managed.
Before expanding Copilot use, it’s important to understand how it surfaces information and why preparation matters more than feature lists.
Recommended reading:
Microsoft Copilot adoption resources →
https://adoption.microsoft.com/copilot -
Prompting: Art & Responsibility
Prompting is often framed as a creative skill, but it’s also a responsibility. The context people include in prompts, and how outputs are reviewed, can introduce real risk if expectations aren’t clear.
As AI use grows, prompting benefits from shared guidance and judgment, not just experimentation.
To support responsible use, we’ve included several reference guides that help structure prompts thoughtfully—focusing on clarity, restraint, and intent rather than tactics or shortcuts.
Prompting reference materials:
These are reference materials. Not a list of prompts or recommended applications.
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Security Fundamentals
AI doesn’t create new security problems. It exposes existing ones faster. Identity, permissions, data protection, and visibility all matter more once AI tools are in play.
Microsoft has published clear guidance on what a secure, governed foundation looks like before expanding Copilot or agent use.
Recommended guidance:
Secure & Govern Microsoft 365 Copilot – Foundational Deployment Guidance →
https://learn.microsoft.com/microsoft-365/copilot/secure-govern-copilot-foundational-deployment-guidanceSelf‑assessment:
Security for AI Assessment →
https://aka.ms/S4AIassessment -
Data Cleanup & Organization
AI surfaces data efficiently. That’s only an advantage if your data is organized intentionally.
Many organizations benefit from reviewing ownership, stale content, overshared files, and external links before expanding AI use. This isn’t about perfection, it’s about reducing unnecessary exposure and increasing confidence in what AI can access.
Think of this as basic hygiene, not a massive project.
A Thoughtful Next Step
If reviewing these resources raised more questions than it answered, that’s a good sign.
Responsible AI adoption takes more than tools or enthusiasm. It requires clarity around risk, ownership, data, and expectations—especially before expanding use or introducing generative AI more broadly across your organization.
Trailhead works with leadership teams who want to approach AI carefully, deliberately, and responsibly. With guardrails in place before problems arise, and without hype‑driven pressure to move faster than they’re ready to.
If you’d like help thinking through what this means for your organization, we’re happy to have a conversation.
No obligation. No sales pitch. Just perspective.
Start a conversation:
https://www.trailhead365.com/get-started
Sharing the Workshop
If you attended the AI Foundation Workshop and found the discussion valuable, you may know others on your team (or in your network) who would benefit from the same conversation.
We continue to host the AI Foundation Workshop in small, in‑person sessions designed for business leaders who want clarity and control before expanding AI use. Some attendees also choose to join again as their thinking evolves or new questions surface.