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Owner

The one named person or role accountable for a priority. Committees and "the team" are not owners, because shared ownership means no one is answerable at review time. Ownership is about having a single person to ask "what happened?", not about assigning blame.

Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).

How each discipline defines it

The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.

Certified AI Governance Professional (CAIGP)

The one named person or role accountable for a priority. Committees and "the team" are not owners, because shared ownership means no one is answerable at review time. Ownership is about having a single person to ask "what happened?", not about assigning blame.

Certified Agentic AI Governance Professional (CAAGP)

The specific role inside the organization responsible for actually sending a given notification once its trigger fires. A row with no named owner is a notice that will not get sent on time, because no one has been assigned the task.

Certified Enterprise Governance, Risk and Compliance Professional (CEGP)

The role with the standing duty to keep an instrument current, answer questions about it, and bring it back for review. Assigned to a role, never to a person.

Certified AI Governance Professional (CAIGP)

The named human accountable for a specific AI system. Ungoverned systems are almost always unowned systems, so an explicitly unowned entry in the inventory is a high-value finding that forces a deliberate ownership decision.

Where it is taught

The exact lessons this term appears in. The first module of every program is free with a free account.

Where it shows up at work

A definition is where Owner starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.

AI inventory and use-case intakeGovernance and Oversight

Finds every AI system in use, records owner, purpose, data and risk tier, and keeps the record alive as tools change.

One lesson on this page teach it as a primary outcome.

Measures whether governance works: inventory coverage, owners named, overdue reviews, incidents, approval times, not how busy the committee is.

One lesson on this page teach it as a primary outcome.

AI policy and standards writingGovernance and Oversight

Writes policies with scope, responsibilities, requirements, exceptions and evidence, so people can follow them and auditors can test them.

One lesson on this page teach it as a primary outcome.

Roles that hire for it

Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.

How job descriptions say it

Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.

“ai inventory”“model inventory”“use case intake”“register of ai systems”“catalog ai”“shadow ai”

Where the frameworks place it: NIST AI RMF MAP 2; ISO/IEC 42001 Annex A; ISO/IEC 42001 Clause 9; ISO/IEC 42001 Clause 5.2.

One interview question about it

How would you find every AI system in use across an organization, including the ones nobody registered, and keep that inventory current?

Asked of candidates for ai inventory and use-case intake. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.

If you come from another field

Some backgrounds already carry this competency, and the readiness check gives credit for it.

Terms it appears with

Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.