Copilot readiness · Data · Governance
AI Readiness Check for Microsoft 365
Before you roll out AI, understand what it will work with. Here's how I review the evidence, the risks and the open questions with Raidiness.
By Ziggy Itjoejaree · Updated
What is an AI Readiness Check?
An AI Readiness Check is an assessment of the technical setup, data access, governance and organizational decisions behind an AI rollout. For Microsoft 365, the aim is to understand what is ready, what needs attention and what still needs evidence before you introduce Copilot or agents.
When I look at readiness, I start with the use case. Who will use AI? Which information should it work with? Who owns the decisions? Those answers give the technical findings meaning.
I built Raidiness to help with the evidence collection and assessment. The tool supports the review; I still need to connect the results to how the organization works.
Why check before a Copilot rollout?
Microsoft 365 Copilot works within the user's existing permissions. If people already have more access than they need, that matters when AI helps them find and use information. Microsoft's Copilot security guidance explains this relationship between permissions, oversharing and risk.
That is why I want the data and governance conversation early. Buying licenses is one step. Understanding the information people can reach, and agreeing how they should use AI, takes a wider review.
My Microsoft 365 AI readiness checklist
1. Scope and intended use
Agree which experience you are assessing: Copilot Chat, Microsoft 365 Copilot or agents. Identify the intended users, business tasks, data sources and owner of the rollout. Different scenarios need different evidence; a tenant-wide measurement does not automatically describe a particular pilot group.
2. Identity, access and licensing
Review relevant identity and access configuration, users, groups and licensing evidence. Check that the selected users and workloads meet the requirements for the intended scenario. Record access gaps in the assessment itself so missing permissions do not look like a healthy result.
3. Data access and SharePoint governance
Look at sharing settings, site ownership and the places where sensitive content is stored. Use available inventory and permission evidence to identify where a closer review is needed. Sampling does not prove that every file in the tenant has the right permissions.
4. Information protection and audit
Review the available Purview evidence: sensitivity labels, DLP, retention and audit settings. Then check whether the policies apply to the relevant information and users. A policy appearing in an inventory is the beginning of that conversation; its effectiveness needs validation.
5. Teams, agents and connector governance
Bring in the workloads that the rollout will use. Teams meeting policies and Power Platform environment and connector policies can add useful context. Broader agent inventories and shadow AI visibility may require additional evidence from other tools and a manual review.
6. People, ownership and follow-up
Ask who owns AI policy, training, support and the pilot's success criteria. Use intake answers to capture those decisions. Agree who will investigate each relevant finding, what a sensible next step is and how you will verify the change.
How I use Raidiness in the assessment
- Define the scope. Choose the AI scenarios, intended users and relevant workloads.
- Collect evidence. Run Raidiness with approved access and provide the available intake context.
- Review findings and gaps. Separate measured results from checks that could not be evaluated.
- Agree the next steps. Validate the findings with the relevant owners and turn them into a practical plan.
- Check again after changes. Collect fresh evidence to verify what has changed. Re-exporting an old report does not create a new measurement.
The output I want is a clear view of the findings, the open questions and the decisions needed for a pilot. Raidiness provides the technical evidence. The organization and its engineers own the priorities and rollout decision.
Questions I often get
Is this a Microsoft 365 Copilot readiness assessment?
Yes. Microsoft 365 Copilot is a central use case for Raidiness. The assessment should be scoped to the AI capabilities you intend to use, including relevant chat or agent scenarios. It is an independent project, not a Microsoft certification or deployment approval.
Can a scan prove that we are ready for AI?
No. A scan can evaluate the evidence it collects. It cannot prove that every permission is appropriate, that employees understand the policy or that a use case will deliver value. Those questions need validation with people who know the organization.
Does Raidiness detect all shadow AI?
No. It does not provide a complete inventory of every AI tool or agent in use. Include other discovery sources and organizational input when shadow AI is part of your assessment scope.
Can I run the check myself?
Yes, if you have the required technical knowledge and approved access. Start with my Raidiness installation guide. If you want to discuss your scope or findings, contact me.
Further reading
Start with your use case
Have a question about Raidiness or preparing your organization for AI? Tell me what you want to introduce and where you need more clarity.
Talk to me about AI readiness