Art. 26.9 EU AI Act: DPIA obligation for high-risk AI
Art. 26.9 links the EU AI Act to the GDPR: where a data protection impact assessment (DPIA) is required under GDPR Art. 35, deployers of high-risk AI must use the information from the provider's documentation to support that assessment.
Updated: June 2026
Introduction: two frameworks, one impact assessment
Art. 26.9 creates an explicit link between the EU AI Act and the GDPR: "Deployers who are subject to obligations regarding data protection impact assessments under Regulation (EU) 2016/679 shall integrate the information relevant to the high-riskriskIn the EU AI Act's terms, the combination of the probability that a harm occurs and the severity of it if it does. The link between a principle (via the harm that would breach it) and a control (the measure that reduces it). Naming the harm and assessing its risk is required by Art. 9 before any mitigation measure is chosen. See harm, control, residual risk.Open full entry → AI systemAI systemA machine-based system that, for explicit or implicit objectives, infers from input how to generate outputs — predictions, content, recommendations or decisions — that can influence physical or virtual environments. The OECD-style definition followed by the EU AI Act.Open full entry → into such impact assessmentimpact assessmentA structured evaluation, carried out in the plan-and-design stage, of the harms an AI system could cause and the risk those harms carry, before the system is built. The first place the governance chain is run, and the cheapest point in the life cycle to reduce risk. The anchor artifact of the planning stage; under the EU AI Act, a fundamental-rights impact assessment is required for certain high-risk deployers. See harm, risk, life cycle.Open full entry →."
This provision does not create a new standalone obligation, it extends the existing GDPR Art. 35 DPIADPIAData Protection Impact Assessment — required before likely-high-risk processing (systematic profiling with significant effects, large-scale special categories, public monitoring); AI development triggers it constantly.Open full entry → framework to encompass the AI-specific elements required by the EU AI Act. For organizations already conducting DPIAs for AI-related processing, this means expanding the scope of those assessments.
When is a DPIA required?
Under GDPR Art. 35, a DPIA is required when processing is likely to result in "high risk" to individuals' rights and freedoms. The EDPB has identified specific types of processing that always require a DPIA, including:
- Systematic and extensive profilingprofilingAutomated processing of personal data to evaluate or predict aspects of a person, such as performance, behavior or location, as defined in the GDPR.Open full entry → with significant effects
- Large-scale processing of special categories of data
- Systematic monitoring of publicly accessible areas
High-risk AI systems under the EU AI Act will frequently trigger DPIA obligations under one or more of these criteria. A CV screening AI (Annex IIIAnnex IIIThe EU AI Act's list of high-risk use-case areas — biometrics, critical infrastructure, education, employment, essential services, law enforcement, migration, justice.Open full entry →, point 4) involves systematic profiling with significant effects on employment. A credit scoring system involves profiling with significant financial effects.
What to include in the integrated DPIA
An AI Act-integrated DPIA should cover, in addition to the standard GDPR elements:
- AI system classification: Risk class and classification rationale (Art. 6)
- Technical characteristics: System architecture, training datatraining dataThe data used to fit an AI model's parameters; its quality, lawful rights and representativeness are central governance concerns.Open full entry → provenanceprovenanceThe documented origin and history of data or content, used to establish where it came from and whether it can be trusted or lawfully used.Open full entry →, performance metrics
- Oversight arrangements: How human oversighthuman oversightDesigned-in human ability to monitor, intervene in, override or shut down an AI system — meaningful only when the human has authority, information and time to act.Open full entry → is implemented (Art. 26.2)
- Bias risk assessment: Analysis of potential demographic disparities in AI outputs
- Input data quality measures: Data quality controls (Art. 26.4)
- Retention of AI logs: Log retention policy (Art. 26.6)
- Fundamental rights impact: For systems also requiring a FRIAFRIAFundamental Rights Impact Assessment — required of public bodies and certain private deployers before using some high-risk AI systems under the EU AI Act.Open full entry → under Art. 27, the analyses may be combined
Relationship with the FRIA
For public sector deployers of high-risk AI, Art. 27 also requires a Fundamental Rights Impact Assessmentfundamental rights impact assessmentAn assessment that certain deployers of high-risk AI must perform to identify and mitigate the system's risks to people's fundamental rights.Open full entry → (FRIA). The DPIA and FRIA overlap significantly. Best practice is to conduct a combined DPIA/FRIA that satisfies both requirements simultaneously, with clearly labelled sections for each framework.
Compliance checklist
- Have you identified all high-risk AI systems that also process personal data (triggering GDPR jurisdiction)?
- Has a DPIA been conducted for each such system?
- Does the DPIA include the EU AI Act-specific elements listed above?
- Has the DPO been consulted in the DPIA process?
- Is the DPIA reviewed and updated when the AI system or its use case changes?
- Is the DPIA documented and accessible for supervisory review?