Two assessments, and one rule that ties them together.
Six areas, five levels, one score at the end. Data first, AI second — the other way round ends in outages and a discouraged team.
AIM6™ AI Maturity · AIMS
- A1AI Strategy & Vision
- A2AI Leadership & Talent
- A3AI Use Cases & Value
- A4AI Technology & Platform
- A5AI Data & Knowledge
- A6AI Governance & Responsible AI
DM6™ Data Maturity · DMS
- D1Strategy & Leadership
- D2People & Data Culture
- D3Data & Architecture (Fabric, Lakehouse)
- D4Analytics & AI
- D5Governance & Privacy (GDPR, AI Act, NIS2)
- D6Adoption & Value
AI maturity must never run more than one level ahead of data maturity.
That is why I run both assessments together, and from the two results I derive a single number showing how far one has outrun the other. There is also a date that focuses the mind: EU AI rules start applying to high-risk uses on December 2, 2027, and to AI built into products covered by EU product-safety law on August 2, 2028.How long does it take? Anywhere from six months to two years — and company size is not what decides it. Scope decides it, along with the skills of the team that will take the solution over, and the organization’s readiness for change: whether leadership is actively driving it, and whether there are people inside ready to champion the new way of working. That last one usually settles it — without them a rollout ends at technical acceptance rather than daily use. So we don’t start with a big project: we build the smallest version that genuinely works, hand it to people, and add the next piece every few weeks. The first result shows in 6–8 weeks, and if something is off, you find out in a month rather than a year.Lean Startup · MVP · MVA · Value Stream Mapping · Scrum · change management · 2–4 week increments