Where does your organisation stand on the AI maturity scale?

AI maturity quick diagnostic

12 questions, 6 dimensions, 4 levels. Answer online at /en/express-diagnostic; the result prints on one page.

1. 1. What place does AI hold in the organisation’s strategy?

   1. 1. No formal place: uses arise from individual initiatives.
   2. 2. A few projects are supported, without an overall roadmap.
   3. 3. A prioritised roadmap exists, sponsored by a member of the executive team.
   4. 4. AI shapes the strategy: every department has quantified objectives tied to it.

2. 2. How are AI projects chosen and funded?

   1. 1. Case by case, with no dedicated budget or criteria.
   2. 2. By each department, on one-off budgets and by its own criteria.
   3. 3. By shared criteria (value, feasibility, risk), from an identified budget.
   4. 4. As a managed portfolio: gains are measured and budgets reallocated continuously.

3. 3. Where is the data your use cases would need?

   1. 1. Scattered across files and messaging tools, hard to find.
   2. 2. In a few business tools, loosely connected to each other.
   3. 3. Centralised for the key domains, with an owner per domain.
   4. 4. Governed end to end: controlled access, monitored quality, reusable from one case to the next.

4. 4. How much do you trust the quality of that data?

   1. 1. Little: errors are discovered when the data is used.
   2. 2. It varies: some teams check, others do not.
   3. 3. Good on the key domains, thanks to regular checks.
   4. 4. Measured continuously, with alert thresholds and tracked corrections.

5. 5. How do teams use AI day to day?

   1. 1. A few curious people, on a personal basis, with no framework.
   2. 2. Pilot teams, without shared training.
   3. 3. Most of the teams concerned, trained and equipped.
   4. 4. All teams, with upskilling paths maintained over time.

6. 6. Who holds the AI skills?

   1. 1. No one in particular.
   2. 2. One or two specialists, in demand from all sides.
   3. 3. An identified team that supports the business lines.
   4. 4. Go-to people in every business line, backed by a central team.

7. 7. Are your processes described in a usable way?

   1. 1. Little or not at all: know-how stays in people’s heads.
   2. 2. Partly, in documents that are rarely up to date.
   3. 3. Key processes are mapped and kept up to date.
   4. 4. They are measured continuously and redesigned when an agent is built into them.

8. 8. What place does AI hold in those processes?

   1. 1. None, or peripheral uses (copy-pasting into an assistant).
   2. 2. Local automations, without an overall view.
   3. 3. AI supports core processes, with human review.
   4. 4. Agents execute at scale; teams validate and arbitrate.

9. 9. Which AI tools do teams have?

   1. 1. Consumer tools, used without a framework.
   2. 2. Tools chosen by each team, with no overall consistency.
   3. 3. A shared platform, approved by the IT department.
   4. 4. A shared platform, connected to business systems and supervised.

10. 10. How do these tools connect to your systems (ERP, CRM, messaging)?

    1. 1. They do not connect to them.
    2. 2. Through manual exports and imports.
    3. 3. Through connectors on the main systems.
    4. 4. Through standardised, documented and monitored integrations.

11. 11. Are there rules for using AI?

    1. 1. No: everyone does as they see fit.
    2. 2. General guidelines, little known to the teams.
    3. 3. A charter known to all, with clear prohibitions (sensitive data, decisions).
    4. 4. Active governance: uses are reviewed and the rules kept up to date.

12. 12. How are AI-related risks monitored (confidentiality, bias, regulatory obligations)?

    1. 1. They are not monitored.
    2. 2. Case by case, when a problem arises.
    3. 3. Through a review before each release to production.
    4. 4. Continuously: register of uses, regular checks, obligations kept up to date.