EmergingResponsible AI governance and risk

AI Inventory and Governance Analyst

Also called AI Governance Analyst

An AI Inventory and Governance Analyst keeps a current record of every AI system a company builds or buys, who owns it and what it must comply with. That record lets leaders manage risk with facts.

What they do

They find AI systems across the business, including ones teams bought or switched on without telling anyone. They record each one in the inventory with a clear owner, purpose, data use and risk class. They map each system to the policies, contracts and regulatory duties that apply. They chase owners for updates when a model changes, a vendor shifts terms or a use case grows. They check that evidence exists and is stored. They report gaps to risk, legal and engineering leads in plain terms.

What a strong hire delivers

In the first months, a strong hire gives the company one inventory that people trust. Shadow and third-party AI use is found and logged. Every system has a named owner and a risk classification. Obligations are mapped to systems, and a simple change process shows who altered what and when. Leaders can answer an audit or customer question quickly.

How you can tell they are good

Ask them to walk through an inventory they built or improved. Good candidates explain how they classified systems, how they found unlisted ones and how they kept records current. Ask how they handled an owner who ignored requests. Look for judgement on data quality and traceability. Be wary of people who talk only about policy and never about records.

Why it is hard to fill

Few companies have a job with this title, so candidates rarely advertise it. The work often sits inside risk, compliance, audit or a responsible AI team under another name. The mix is unusual: governance discipline, enough technical grasp to classify systems, and patience with messy data. Strong people are often not looking, and CVs undersell the relevant work.

Where to find them

Look at risk analysts, compliance and audit professionals, technology governance and model risk teams, and responsible AI programmes. Many come from financial services, insurance, healthcare and other regulated sectors, where inventories and evidence trails are routine. Some come from data governance or privacy teams. AI companies with enterprise customers also grow these people internally.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Inventory and Governance Analyst

  1. Describe an inventory of systems or models you built or took over. How did you decide what it should record?

    A strong answer covers fields chosen for decisions, not completeness for its own sake: owner, purpose, data, risk class, status. They explain who used it and how it stayed current. Worry if it was a one-off spreadsheet nobody maintained.

  2. How would you find AI systems in a company that nobody has told you about?

    Good answers use several routes: procurement and finance records, vendor and security reviews, software access logs, team interviews and amnesty-style requests. They accept the list will never be perfect. Worry if they rely only on a survey.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are hiring an AI Inventory and Governance Analyst to keep an accurate record of the AI systems we build and use. You will make ownership, risk and obligations clear, so teams can ship with confidence and leaders can answer hard questions quickly.

What you will do

  • Maintain a current inventory of internal, third-party and embedded AI systems
  • Find unlisted AI use and bring it into the record
  • Classify systems by risk using agreed criteria
  • Map each system to applicable policies, contracts and regulatory duties
  • Track changes and keep an auditable history of who changed what
  • Work with owners to keep records and evidence up to date
  • Report gaps and trends to risk, legal and engineering leads

What you will bring

  • Demonstrated work building or running an inventory, register or similar control record
  • Experience in risk management, compliance, audit, technology governance or responsible AI
  • Ability to classify technical systems and judge data quality
  • Clear written and spoken communication with technical and non-technical colleagues
  • Working knowledge of AI risk and assurance practices
  • Track record of getting busy owners to keep records accurate

Nice to have

  • Experience with fairness or impact assessments
  • Familiarity with model inventories or evidence management systems
  • Background in a regulated sector

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • AI risk managementAdvancedIdentify, assess, treat and monitor AI risks
  • AI governance and assuranceAdvancedAssign accountability and verify lifecycle controls
  • Fairness and impact assessmentWorkingAssess unequal errors, access and downstream impacts
  • Technical communicationWorkingExplain evidence and limitations to relevant readers

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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