Home › Cases
How do you make an organisation AI-ready with data governance?
By deciding who owns what before deciding which tools to buy. A regional water authority wanted to be ready for AI, and readiness turned out to mean definitions that hold, ownership that is assigned, and traceability that is arranged. An organisation-wide governance framework came first; the plans for Microsoft Copilot were built on top of it rather than beside it.
Water utility, public sector Microsoft Copilot, data catalogue
The challenge
The organisation wanted to be ready for AI across the business. That ambition was clear; what it required in practice was not. Definitions differed per department, ownership of data was implicit, and data quality was discussed but not measured.
Our approach
We started with what AI readiness actually demands: definitions that are recorded, data that is maintained, and owners who feel responsible. That work was set out as a governance roadmap tied to decisions the organisation was already facing, rather than as a separate programme.
Alongside that we contributed to the AI strategy: implementation plans for Microsoft Copilot and the design of an AI governance structure that can hold as the technology changes.
Results
Roles, responsibilities and procedures are recorded, and governance principles are anchored in daily operations rather than in a document. Collaboration improved because it became clear who decides what. The AI governance plans put the organisation in a position to scale Copilot responsibly, with a pilot as the next step rather than a launch on an untested foundation.
Expertise involved
Data governance, framework design and AI readiness, along DAMA DMBOK2 lines, combined with the change work needed to get ownership assigned and definitions agreed.
See also
Read on
Half an hour is enough to know whether we fit
No slide deck and no quote at the end. We walk through your sources, your definitions and your biggest frustration.
Book half an hourFrequently asked questions
What does AI-ready actually mean?
That your definitions are agreed, your data is maintained structurally and someone owns each data item. A model on messy data mostly produces wrong answers faster, so readiness is a data management question before it is a technology question.
Why start with governance rather than with a tool?
Because a tool applies rules and does not decide them. Somebody in the business has to say what a figure means and who maintains it. Buying the tool first means paying to postpone that conversation.
How do you get a governance framework to stick?
By tying it to decisions the organisation already faces and by handing it over properly: documentation, coaching and advice, so teams can carry it themselves. A framework that only lives with the person who wrote it disappears when that person leaves.