AI Readiness Assessment
Know if your data and governance are ready for AI — before you deploy it.

Find out what Copilot will see — before it sees it

Copilot will surface exactly what your permissions allow: the overshared folders, the stale access, the unlabelled sensitive documents. This assessment tells you what that picture looks like today, what to fix before deployment, and what a safe rollout sequence is. It is the assessment that prevents the pilot that stalls in a security review.

You leave with a remediation plan sequenced before deployment, a governance design for Copilot, and a clear go / no-go recommendation with evidence.

Why boards are asking — and why IT leaders are cautious

Every board is asking about AI, and the pressure to deploy is real. But IT leaders who have lived through a data exposure know the other side of the story: Copilot is honest. It does not invent access; it uses the access that already exists. Years of broken inheritance, sharing links that outlived their purpose, and sensitive content with no label are not Copilot problems — they are estate problems that Copilot makes visible to everyone, instantly. The first time someone asks Copilot a question and gets an answer drawn from a document they should never have seen, the project goes into a security review and rarely comes out.

The readiness assessment exists to prevent that sequence. It measures the exposure before deployment, in terms leadership can act on: what is overshared, where the sensitive content sits without protection, and what needs to change before a single license is assigned. It turns a political question — deploy or delay — into an evidence question with a sequenced answer.

How the assessment works

The assessment examines the estate Copilot will actually touch: SharePoint and OneDrive permissions and sharing patterns, Teams and group access, guest and external sharing, sensitivity label coverage, DLP policies and their enforcement state, retention posture, and the identity and access controls underneath it all. Findings are tied to business impact, not just technical severity — an overshared folder of board papers matters differently than an overshared folder of lunch menus, and the assessment says so.

The work also covers the governance side: who owns Copilot decisions, what acceptable use looks like, how prompts and outputs are handled, and what controls need to exist before rollout. The result is not a pass/fail verdict. It is a remediation plan sequenced by risk, a governance design, and a rollout recommendation — pilot group, use cases, success criteria, and expansion sequence — so that when you do deploy, you deploy with confidence and with security and compliance already onside.

What you walk away with

A clear answer to the board's question, backed by evidence: here is what our data estate looks like, here is what we fix first, here is the sequence, and here is when Copilot can safely go live. If the estate is in better shape than expected, the assessment says that too — and the rollout can proceed without unnecessary remediation. Either way, the decision is made on evidence, not on optimism or fear.

  • Permissions and sharing review — what Copilot would surface today, and where the exposure sits. This is the core finding: a concrete picture of oversharing, stale access, and broad sharing links across the content Copilot will reason over, rated by business impact so remediation starts where the risk actually is.
  • Sensitivity and DLP gap analysis — labels, policies, and coverage measured against what AI deployment requires. It shows where labelling is missing, where DLP is in audit-only mode, and where controls exist on paper but are not enforced — the gaps that matter most once AI is in play.
  • Remediation plan — prioritized fixes sequenced before deployment, with effort ranges. Fixes are ordered by risk reduction per unit of effort, so the highest-exposure items come first and the estate reaches a safe deployment state as fast as possible.
  • Copilot governance design — controls, ownership, and acceptable-use framing. This covers who decides who gets Copilot, what data it can reach, how prompts and outputs are handled, and who owns the ongoing governance — so the deployment has an operating model from day one, not just a launch date.
  • Rollout recommendation — pilot group, use cases, success criteria, and expansion sequence. The recommendation gives leadership a concrete path: who goes first, what success looks like, and how expansion is decided — turning deployment from an open-ended commitment into a staged, evidence-based program.
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