PIPC (Personal Information Protection Commission)
South Korea's data-protection regulator, which in April 2021 applied the country's Personal Information Protection Act to an AI system for the first time in the Scatter Lab case.
Defined in 2 GAGE programs, which carry 3 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.
South Korea's independent data protection authority, responsible for enforcing the country's Personal Information Protection Act, referenced in this topic as an example of data-first enforcement logic outside the EU and US.
South Korea's data-protection regulator, which in April 2021 applied the country's Personal Information Protection Act to an AI system for the first time in the Scatter Lab case.
South Korea's data protection regulator, an active enforcer in 2024 and 2025 across breach cases and cross-border transfer notice failures.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Why the data person just became the most consequential role in the building · Taking the Data Chair, Certified AI Data Governance Professional (CADGP)
- The records of processing: the register a regulator reads first · Consent, Purpose, and the Law of Data, Certified AI Data Governance Professional (CADGP)
- Consent archaeology: what this data was collected for versus what you want to do · Data Reality, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where PIPC (Personal Information Protection Commission) 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.
Keeps the living record: each risk with a named owner, rating, treatment, residual risk, monitoring metric, threshold and review date.
One lesson on this page teach it as a primary outcome.
Classifies information, applies least privilege, sets retention and acceptable-use rules, and controls what may enter a prompt, a log or an embedding.
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.
- Chief Risk Officer, AI risk editionneeds it at depth
- AI Risk Managerneeds it at depth · 2 open postings this week
- Cybersecurity Risk Analystneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
- Model Risk Managerneeds working knowledge
- AI Governance Managerneeds working knowledge
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.
Where the frameworks place it: NIST AI RMF MANAGE; ISO/IEC 42001 Clause 6; EU AI Act Article 9; ISO/IEC 27001.
One interview question about it
How do you keep an AI risk register from becoming a list nobody reads? What makes a risk entry actionable?
Asked of candidates for ai risk register and treatment tracking. 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.
- Internal audit and IT audit carries it as a claim to back up: Remediation tracking is familiar from follow-up work.
- Privacy and data protection carries it as a claim to back up: Classification and retention rules are familiar territory.
- Cybersecurity and IT carries it as work you can show: Access governance and classification are implemented, not described.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.