Your organization is not as AI-ready as your last strategy meeting suggested.
Fourteen questions. Seven dimensions. One honest score out of 100 — covering the things vendor assessments skip: your data reality, your workforce exposure, your security posture, and whether your leadership actually agrees on what AI is for.
15Minutes
7Dimensions
100Point scale
48hReviewed brief
What this is not: a sales funnel for software. No vendor is behind this instrument. It was built by a practitioner — CISSP, CISA, PMP, 18 years across enterprise technology and workforce development — to give you the answer consultants take six weeks to bill you for.
Dimension 1 · Data Readiness · 18 pts
Is your data usable, or just abundant?
Every AI initiative inherits the state of your data. Most fail here first — quietly, months after the budget is committed.
Which best describes your organization's core operational data?
Scattered across systems, spreadsheets, and inboxes — no single source of truth
Centralized in places, but quality is inconsistent and ownership is unclear
Largely centralized with defined owners, though documentation lags
Governed, documented, and accessible — teams can find and trust the data they need
If a team wanted to pilot an AI use case next month, could they legally and practically access the data it requires?
No — access, privacy, or format barriers would stall it indefinitely
Eventually — after months of negotiation between departments
Mostly — some datasets are ready, others would need cleanup
Yes — clear access processes exist and have been used before
Dimension 2 · Use-Case Clarity · 16 pts
Can you name the process AI will change?
"We should be doing something with AI" is not a use case. Named processes with measurable baselines are.
How specific are your organization's current AI ambitions?
General direction only — leadership says AI matters but nothing is named
A brainstormed list exists, but nothing is prioritized or owned
Two or three candidate use cases are named with rough owners
Specific processes are named, baselined, and prioritized by expected impact
For your leading AI candidate use case, do you know the current cost or cycle time of the process it would improve?
No — we have never measured the process as it runs today
We have rough anecdotal estimates, nothing documented
Partial measurements exist for some steps
Yes — a documented baseline exists, so improvement would be measurable
AI adoption fails on people before it fails on technology. Exposure without preparation produces resistance, attrition, and quiet sabotage.
Has your organization identified which roles are most exposed to AI-driven change?
No formal analysis — we assume we'll handle it when it arrives
Informal conversations have happened, nothing documented
A role-exposure review has been done for parts of the organization
Yes — exposure is mapped by role, with reskilling priorities identified
What AI training or upskilling actually exists today — not planned, running?
None — employees are experimenting on their own, unguided
Ad-hoc lunch-and-learns or shared articles, no structure
A structured program exists for some teams or functions
Role-based training is running with completion tracked and tied to real workflows
Dimension 4 · Security & Risk Posture · 16 pts
What is leaving your building right now?
Employees are already pasting sensitive material into public AI tools — at most organizations, today, unmonitored. This dimension is where readiness assessments built by vendors look away.
Do you know — with evidence, not assumption — what company data is entering public AI tools?
No visibility at all — we genuinely don't know
We suspect it's happening and have asked people to be careful
Partial monitoring or approved-tool policies exist, enforcement is thin
Yes — monitored, with sanctioned tools that meet our data handling requirements
Has AI been incorporated into your security and risk management processes — vendor review, incident response, access control?
No — our security program predates AI and hasn't been updated for it
It's on the roadmap but nothing has changed yet
Some processes updated — AI vendors get reviewed, gaps remain elsewhere
Yes — AI-specific risks are integrated into our security framework and reviewed regularly
Dimension 5 · Governance & Compliance · 12 pts
If a regulator asked tomorrow, what would you show them?
AI governance is moving from optional to expected across sectors. Organizations without documented policy are accumulating invisible liability.
Does your organization have a written, communicated AI acceptable-use policy?
No policy exists
Drafted or borrowed from a template, never formally rolled out
Published, but most employees couldn't tell you what it says
Published, trained on, and referenced when new tools are evaluated
Who is accountable for AI decisions in your organization?
No one — decisions happen wherever enthusiasm happens
IT inherits it by default, without a mandate
A named individual or committee exists, with limited authority
Clear ownership with authority, budget influence, and executive access
Dimension 6 · Leadership Alignment · 12 pts
Does your leadership team agree on what AI is for?
Three executives with three private definitions of "AI strategy" will fund three incompatible initiatives — and blame the technology when none of them land.
If you asked each member of your leadership team what AI should do for the organization, how similar would the answers be?
Wildly different — cost cutting vs. growth vs. "we have to be seen doing it"
Some overlap, but priorities visibly compete
Broadly aligned in conversation, not documented anywhere
Aligned and written down — a shared position guides investment decisions
How does AI appear in your organization's actual planning documents — strategy, budget, board materials?
It doesn't, or only as a buzzword in a vision slide
Mentioned with no owners, timelines, or dollars attached
Named initiatives exist in plans with partial funding
Specific initiatives with owners, milestones, and budget lines
Dimension 7 · Financial Discipline · 10 pts
Is this investment, or FOMO spending?
The difference between an AI strategy and an AI expense is whether anyone can say what the money is supposed to return — and would notice if it didn't.
How is AI spending decided in your organization today?
Reactively — tools get bought when someone senior gets excited
Small experiments funded informally, no tracking of what they return
A defined budget exists, loosely tied to expected outcomes
Budgeted with ROI logic — each initiative has an expected return and a review date
Could your organization say, today, what its current AI tools have actually returned?
No — nobody is measuring, and licenses renew automatically
Anecdotes only — "people seem to like it"
Usage is tracked; business impact is not
Yes — usage and impact are reviewed, and tools that don't perform get cut
Your AI Readiness Index
0
out of 100
—
Your Readiness Profile
Your reviewed briefing is next.
This preliminary score is calculated from your answers alone. Within 48 hours, a practitioner review of your dimension profile — including the two gaps most likely to cost you money this year — is delivered to your inbox. Enter your details to receive it.
Want evidence instead of self-report? See the AI Readiness Deep Assessment — a two-week, interview-based engagement with transparent pricing.
Reviewed briefing · 48 hours
Where should the briefing go?
Thank you — we're on it.
Your AI Readiness Index has been recorded and someone will be in contact within one business day. Your practitioner-reviewed briefing — including the two dimensions most likely to cost you money this year — follows by email.
1
Within one business day — a member of the Best Entrust team reaches out to confirm receipt and answer any immediate questions.
2
Within 48 hours — your reviewed briefing lands by email, with dimension-by-dimension commentary and the two priority gaps identified.
3
Keep going — explore the AI Readiness Deep Assessment: a two-week, evidence-based engagement that turns your score into a defensible roadmap, with transparent pricing.