Everyone wants to “do AI”, few know where to start. An AI maturity audit tells you where you stand, which use cases will pay off and what a realistic roadmap looks like.
Five dimensions
- Data: location, reliability, access, structure
- Processes: repetitive, high-volume, document- or rule-based tasks
- Tools: APIs, automation readiness
- Skills: owners, current usage, training needs
- Governance: usage rules, confidentiality, hosting, human validation, EU framework
Maturity levels
Exploration, experimentation, industrialisation, integration.
AI maturity is measured by processes actually improved, not tools tried.
What the audit delivers
A baseline, costed use cases, two or three priority projects including a quick win, prerequisites, and a 6–12-month roadmap.
Common quick wins
Supplier invoice automation, an internal assistant with enterprise RAG, and our document automation use cases.
AI maturity audit: FAQ
How long does it take?
Usually two to four weeks.
Do we need perfect data?
No — but you need to know where it is and what it is worth.
Take stock
Start with our 2-minute audit; we then run the full assessment and deploy first use cases such as supplier invoice OCR. Let’s talk.