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Data localization

A regulatory requirement, or a practical consequence of one, that certain categories of data remain physically stored or processed within a specific jurisdiction's borders, examined in Section 3K as the clearest evidence that the three paradigms are inherited governance architectures rather than purpose-built AI frameworks.

Defined in 2 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in Certified China AI Regulatory Professional (CCARP).

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 China AI Regulatory Professional (CCARP)

The general regulatory practice, seen across several Chinese instruments, of requiring certain categories of data (particularly data connected to critical information infrastructure or collected within China) to be stored on servers located inside China unless a lawful cross-border transfer mechanism is used. (see Topic 5.4) covers this topic's full mechanics.

Certified AI Governance Professional (CAIGP)

A requirement that certain personal data remain within a jurisdiction's borders. Where it applies, an AI feature that centralizes training data abroad cannot operate as built and must process locally or exclude the jurisdiction.

Certified China AI Regulatory Professional (CCARP)

The requirement that certain categories of data, tied to critical information infrastructure operator status or important-data classification, be stored physically within China, with cross-border export permitted only as a narrow, security-assessed exception rather than a routine transfer choice.

Certified China AI Regulatory Professional (CCARP)

A regulatory requirement, or a practical consequence of one, that certain categories of data remain physically stored or processed within a specific jurisdiction's borders, examined in Section 3K as the clearest evidence that the three paradigms are inherited governance architectures rather than purpose-built AI frameworks.

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 Data localization 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.

Compares the EU AI Act, NIST AI RMF, ISO/IEC 42001 and sector rules by intent and control objective, and says where they do not overlap.

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

Applies IMDA's Model AI Governance Framework, AI Verify and the PDPA alongside Western frameworks for organizations operating across Asia.

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

Applies GDPR, CCPA and sector rules to training data, inference, automated decisions, lawful basis, individual rights and cross-border transfer.

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.

“map requirements”“framework alignment”“multiple frameworks”“unified control framework”“ai verify”“model ai governance framework”

Where the frameworks place it: EU AI Act; NIST AI RMF; ISO/IEC 42001; IMDA Model AI Governance Framework.

One interview question about it

Map one control to the EU AI Act, NIST AI RMF and ISO/IEC 42001 at once, and tell me where the mapping breaks.

Asked of candidates for framework crosswalking without false equivalence. 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.