Data Protection Impact Assessment (DPIA)
An assessment, required under data-protection law (for example the GDPR, Regulation (EU) 2016/679, Article 35) where processing is likely to result in a high risk to individuals, of the risks a data-processing activity poses to people and the measures to address them. Systematic worker monitoring or automated performance evaluation typically requires one. It is a distinct duty from worker consultation, owed to the individual rather than the representative body, so completing it does not discharge a consultation or co-determination duty over the same system (see Topic 10.4).
Defined in 6 GAGE programs, which carry 11 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.
An assessment, required under data-protection law (for example the GDPR, Regulation (EU) 2016/679, Article 35) where processing is likely to result in a high risk to individuals, of the risks a data-processing activity poses to people and the measures to address them. Systematic worker monitoring or automated performance evaluation typically requires one. It is a distinct duty from worker consultation, owed to the individual rather than the representative body, so completing it does not discharge a consultation or co-determination duty over the same system (see Topic 10.4).
A written assessment documenting an organisation's data protection reasoning for a specific processing activity; the 2026 guidelines require a DPIA or equivalent written record wherever an organisation relies on the Publicly Available Exception despite a reasonably arguable digital barrier, and this topic recommends the same documentation discipline for the full decision sequence.
A structured, documented risk assessment, required under GDPR before deploying a system likely to pose high risk to individuals such as biometric recognition, that walks through what data is collected, why, and what mitigations apply, functioning as the formal record of the same reasoning the four-question check in Section 3F applies informally.
A Western-style internal risk-assessment record, required under frameworks like the GDPR for high-risk processing, that differs structurally from a China algorithm filing in that it is not typically a public-facing document and does not itself function as a gate to lawful operation the way a required China filing does.
The assessment required by Article 35 of Regulation (EU) 2016/679 (GDPR), to be conducted before processing that is likely to result in high risk to the rights and freedoms of natural persons, examining risks arising from personal data processing.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Privacy and Data Rights in AI Systems · Ethical and Responsible AI and Operational Governance, Certified AI Practitioner: Workplace Foundations
- PDPA for AI: What Singapore Actually Allows · Consent, Purpose, and the Law of Data, Certified AI Data Governance Professional (CADGP)
- The RAG corpus under Singapore's PDPA: access, correction, and what "delete" actually means · Feeding the Machines, Certified AI Data Governance Professional (CADGP)
- The retention decision: what you must keep, what you must destroy, and proving both · Data Reality, Certified AI Governance Professional (CAIGP)
- The provenance file: your data map an auditor could follow · Data Reality, Certified AI Governance Professional (CAIGP)
- The union question, the works council, and consultation done right · The Humans: Leading People Through AI Change, Certified AI Governance Professional (CAIGP)
- The DPIA and FRIA, run jointly: one assessment, two regimes, no duplicate work · Evidence Engineering, Certified AI Governance Professional (CAIGP)
- Lab: Mock Algorithm Filing · Algorithm Filing and Registration, Certified China AI Regulatory Professional (CCARP)
- Mock Filing Package · Capstone: Build a China Compliance Program, Certified China AI Regulatory Professional (CCARP)
- AI Act and GDPR: FRIA vs DPIA · Regulatory Interplay and Liability, EU AI Act Implementation Expert
Where it shows up at work
A definition is where Data Protection Impact Assessment (DPIA) 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.
Builds minimization, purpose limitation, de-identification, consent and retention into an AI system before launch, with tests that prove it.
2 lessons 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.
2 lessons 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.
- Chief Privacy Officer, AI privacy editionneeds it at depth
- AI Privacy Engineerneeds it at depth · 6 open postings this week
- Privacy Analystneeds working knowledge
- AI Regulatory Counselneeds it at depth · 14 open postings this week
- Chief Data Officer, data leadership editionneeds working knowledge
- AI Incident Response Leadneeds working knowledge · 1 open posting this week
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: ISO/IEC 27701; GDPR Article 25; IMDA Model AI Governance Framework; PDPA.
One interview question about it
How do you build privacy into an AI product from the design stage rather than checking it at the end?
Asked of candidates for privacy by design and privacy engineering. 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.
- Privacy and data protection carries it as work you can show: Privacy assessments and lawful-basis records are your work product.
- Legal and paralegal work carries it as a claim to back up: Privacy and consumer law are usually within reach.
- A law degree (JD, LLB or LLM), no AI work yet carries it as a claim to back up: Privacy and data protection law are usually a course, not yet a file.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.