The AI Readiness Assessment
A structured, five-dimension scorecard that tells you exactly where you stand — before you commit to a seat, a platform, or a strategy. Board-ready output, not a generic checklist.
What actually gets scored
Most "AI readiness" checklists measure enthusiasm. This measures the five things that actually determine whether an AI investment survives past pilot.
1. Strategy & Use Case Clarity
Is there a prioritised, funded use case roadmap — or a collection of enthusiasm-driven pilots with no common thread?
2. Data Foundation & Infrastructure
Can your data actually support the use cases you want to run, or does every initiative start with a data-cleanup project nobody budgeted for?
3. Governance & Regulatory Risk
EU AI Act risk-tier exposure, board oversight structure, and whether anyone could actually answer an auditor's question today.
4. Talent & Culture
Is AI literacy built into the organisation at every level it needs to be, or concentrated in a handful of enthusiasts fighting institutional inertia?
5. Vendor & Technology Portfolio
Is your tool and vendor estate coherent and governed, or an accumulation of individually-justified point solutions?
Scored 0–100 per dimension
Each dimension gets a defensible score, not a traffic-light guess — with the evidence behind it shown, not just asserted.
Three steps, one board-ready output
1. Structured Workshop
A half-day, facilitated session across operations, data, talent and governance stakeholders — not a survey link nobody reads properly.
2. Scoring & Evidence
Each dimension is scored against a documented rubric, with the evidence behind every score captured, not just the number.
3. Board-Ready Report
A scorecard, an opportunity map prioritised by real ROI potential, and an EU AI Act applicability view — built to be presented, not decoded.
Where most organisations actually sit
The assessment places you on a five-stage maturity ladder — most organisations discover they're a stage or two behind where their AI spend suggests they should be.
| Stage | What It Looks Like |
|---|---|
| 1 · Ad Hoc | Individual tools adopted by enthusiasts. No strategy, no governance, no shared view of what's even in use. |
| 2 · Aware | Leadership knows AI matters and has funded some pilots. No board-level owner, no way to compare initiatives against each other. |
| 3 · Defined | A strategy and roadmap exist. Governance is documented but not consistently followed. Most organisations plateau here. |
| 4 · Managed | A named accountable owner, active governance committee, and use cases tracked against real ROI — not just activity. |
| 5 · Optimised | AI investment is continuously reviewed and reprioritised against outcomes, with failed initiatives shut down as readily as successful ones are scaled. |
The assessment is a diagnosis, not a sales pitch
If the honest answer is "you're not ready for a seat yet, fix these three things first" — that's what you'll hear. If the roadmap points to a Fractional CAIO, that's a conversation for after you've seen your own scorecard, not before.
See where you actually stand
Structured, evidence-based, and yours to keep — whatever it shows.