How Usage Register works
A practical process for discovering how AI is being used, building the register, and deciding what needs to change next.
From unknown AI use to a clear action plan
Most businesses do not have a neat AI inventory waiting to be documented. Staff try tools, share shortcuts, use personal accounts, and create client-facing work before policy catches up. Usage Register helps you find out what is happening and turn it into a practical record.
By the end of the process, you'll have:
The process
Discovery call
We start with a short call to understand your business, team size, departments, AI tools you already know about, and any client, data, or governance concerns.
Survey setup
We configure the confidential staff AI usage survey for your organisation, including departments, role groups, invite tracking, and context for your team.
Staff discovery
Employees complete a short survey about the AI tools they use, what they use them for, what data is involved, and whether outputs are reviewed. Individual answers are not shown to management by name.
Use-case mapping
Survey responses are turned into structured AI tool and use-case records, so you can see what is being used, where, and why.
Risk classification
Each use case is classified using practical risk indicators such as data type, account type, client impact, decision impact, and human review.
Register setup
We build your AI Register so tools, use cases, risks, controls, owners, and review status can be tracked in one place.
Current-State Review
You receive a clear Current-State Review covering AI usage, risk hotspots, data exposure, review gaps, and policy and action priorities.
Action plan
We define practical next steps for the next 30 and 90 days, including what to approve, restrict, review, or fix first.
Optional managed support
If you want ongoing oversight, we can help keep the register current as new tools, teams, and use cases appear.
Optional — Managed plan
Staff guidance and evidence records
Where the review identifies awareness or knowledge gaps, targeted staff guidance can be assigned based on what was actually found. Not generic — based on your real usage picture.
What makes this different
It starts with actual usage
A register is only useful if it reflects what people are really doing. Usage Register starts with discovery, not assumptions.
It is practical, not theoretical
The output is an AI Register, risk picture, current-state summary, and action plan. Not a generic policy document pretending the work is done.
It supports better decisions
You can see which tools should be approved, restricted, reviewed, or fixed first.
Before you can show responsible AI use externally, you need to know what is happening internally.
Ready to get a clearer picture of AI use in your business?
Book a discovery call and we'll talk through your current AI usage, risk areas, and whether Usage Register is a fit.
Book a discovery call