Quick answerAn AI use-case register is the structured, live inventory of where AI is used inside an organisation – what the AI does, who owns it, what data it uses, what oversight applies, and what risks have been assessed. It is the foundational artefact for AI governance: you cannot govern what you have not catalogued.
Why a use-case register matters
Most organisations underestimate their AI footprint. AI use cases proliferate informally – a salesperson using ChatGPT for outreach, an HR team running CV-screening AI, a marketing team A/B-testing AI-generated copy, an engineering team coding with Copilot, a customer-service team auto-summarising tickets. A typical mid-sized organisation has 50-500 active AI use cases. Without a register, governance is theoretical.
What each entry contains
- Use case name and business purpose
- Owner (named accountable person)
- AI system(s) used (ChatGPT, Copilot, internal model, vendor tool)
- Data sources and outputs – including categories of personal data
- Stakeholders affected
- Human-oversight model – how decisions are reviewed
- Risk classification (typically a 3- or 4-tier scheme)
- Linked policies and assessments
- Status (in development, live, deprecated)
- Review date
Risk classification
Prohibited / unacceptable
AI use that violates the organisation’s policies, regulator rules (EU AI Act prohibited practices), or ethical baseline. Stop and remediate.
High-risk
Significant consequences for individuals – employment decisions, credit, healthcare, education access, law enforcement. Requires full governance: DPIA, human oversight, monitoring, audit.
Limited-risk
Customer-facing AI with disclosure requirements – chatbots, AI-generated content. Requires transparency obligations and basic oversight.
Minimal-risk
Internal productivity uses with limited blast radius – drafting emails, summarising documents. Lightweight governance: covered by acceptable-use policy.
How to build a register from scratch
Three patterns work:
- Departmental discovery – workshops with each department (Sales, HR, Marketing, IT, Legal, Customer Service, Engineering) typically surface 5-20 use cases each
- Tool-led discovery – start from the AI tools you’ve procured (Copilot, ChatGPT Enterprise, vendor AI features) and work outwards to use cases
- Risk-led discovery – start from high-stakes decision domains (hiring, credit, customer access) and ask ‘is AI involved here’
Keeping the register current
Use-case registers decay faster than ROPAs because AI use cases spread informally. The operational fix:
- Tie new-use-case registration to existing approval processes (procurement, security review, change management)
- Run a quarterly departmental refresh – quick survey, not a deep audit
- Monitor AI tool adoption telemetry where available
- Make the register the prerequisite for any executive-level AI conversation – boards stop sponsoring ungoverned use cases
How PrivIQ supports the AI use-case register
PrivIQ AI Governance ships a structured AI use-case register with risk classification, owner assignment, policy linkage and assessment workflow. The register feeds the rest of the AI governance programme – controls, oversight records, vendor assessments – so the register is the single source of truth, not an isolated spreadsheet.
- Most organisations have 50-500 active AI use cases. Without a register, governance is theoretical.
- Each entry needs an owner, a risk classification, oversight model, and linked policies.
- Registers decay – keep them current by tying registration to existing approval processes.
- The register is the prerequisite for board-level AI conversations.
PrivIQ helps organisations and consultants put this into practice — with policies, controls, evidence, tasks, registers and reporting that survive audit.
More on AI Governance.
Is an AI use-case register the same as a model inventory?
They overlap but aren’t identical. A model inventory tracks the AI systems themselves – their versions, lineage, performance. A use-case register tracks the business applications of those systems. One AI system might support multiple use cases; one use case might use multiple systems.
Do I need to register internal-only use cases like ’employees using Copilot’?
Yes – at least at the policy level. The register entry might be ‘Microsoft Copilot, organisation-wide, governed by acceptable-use policy X’, not individual user-level entries. The point is to make every form of AI use traceable, not to track every prompt.
How granular should entries be?
One entry per business use case, not per system. ‘CV screening for engineering hires’ is one entry, even if it uses two AI tools.
What’s the EU AI Act connection?
The EU AI Act applies risk-tiered obligations to deployers and providers. A use-case register categorised against Act risk tiers (prohibited / high-risk / limited / minimal) directly supports the Act’s documentation and oversight obligations.
Who should own each entry?
The accountable business owner – typically the department head or product owner using the AI. The privacy or AI governance team curates the register; they don’t own individual use cases.