Is Your Data Actually Ready for AI? A Six-Dimension Self-Check

The six dimensions behind every readiness score, turned into a self-check your leadership team can run in one meeting.

Illustration of a six-sided radar chart with one dimension flaring beyond the others in bright sunset gradient

Before anyone sells you an AI roadmap — including us — your leadership team can learn a lot in one honest meeting. Below are the six dimensions we score in every readiness assessment, converted into a self-check you can run around a conference table. Score each dimension 1 (nowhere) to 5 (strong), and be ruthless: flattering scores produce failed pilots.

1. Strategy

Can anyone in the room state, in one sentence, what AI is for at your company — tied to a margin, revenue, or risk number? Is there a named owner? Does AI appear in your annual plan as anything more specific than a bullet? If the answers are "sort of," score accordingly. Strategy is the dimension everyone claims and few can evidence.

2. Data

Where does your most valuable operational data live — and could a new system actually reach it? Is your file storage organized, or is it twenty years of "Final_v3_FINAL" folders? Do you know which data is customer-owned, regulated, or contractually restricted? Data is the most common constraint we find, and the most under-scored in self-assessments — if the room hesitates here, the honest score is a 2.

3. Technology

Is identity clean — one account per human, MFA everywhere, offboarding that actually offboards? Are your core systems cloud-reachable with APIs, or air-gapped by age? Could you name every system that would need to talk to an AI workflow? This dimension is where an existing well-run IT foundation quietly pays off — and where its absence taxes everything downstream.

4. People

Who in the company is already using AI well — do you know their names? Is there appetite or anxiety in the middle management layer? Has anyone been trained, or is everyone self-taught on consumer tools? Adoption is a people problem wearing a technology costume; a 5 here can carry a 3 elsewhere.

5. Governance

Is there a written AI policy — with approved tools, data rules, and consequences — or a vague memo? Could you answer your insurer's AI questions today, in writing? Does anyone maintain a risk register? Most rooms score themselves a 1 or 2 here, and that's fine — governance is the fastest dimension to improve, and the one with the most immediate external payoff.

6. Security

Do you know what AI tools are actually in use (not just sanctioned)? Have vendor AI clauses been reviewed in your key contracts? Would an AI-related data leak be detected, or discovered by a customer? If shadow AI hasn't been looked for, assume it's there — every organization that looks, finds. (And if this dimension made you nervous, the shadow AI findings post explains why.)

Reading your score

Total the six. Under 12: don't pilot anything yet — fix the two lowest dimensions first, or the pilot will fail and salt the ground for the next attempt. 12–20: you're typical mid-market — ready for governed quick wins in your strongest areas while the weak dimensions get remediated in parallel. Over 20: your constraint is prioritization, not readiness — the question is which use cases pay first.

A self-check tells you the shape of the truth; it can't cite evidence, model ROI on your numbers, or survive a board's follow-up questions. When you need the version that can, that's the assessment — fixed fee, published on the pricing page, delivered remotely in 2–4 weeks. Run the meeting first, though. It's free, and it's clarifying.