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High-risk AI or not? classification guide for deployers

By Michel Venniker· · Aligned with the consolidated EU AI Act, including the 2026 Omnibus amendments.

Whether an AI system is high-risk depends on Art. 6: it is high-risk if it is a safety component under Annex I or falls within an Annex III use case (such as employment, credit, or essential services). The Art. 6.3 exception can apply where the system performs only a narrow, non-decisive task.

Updated: June 2026

Introduction: why classification matters

The EU AI Act creates fundamentally different compliance obligations depending on risk classification. High-risk AI triggers the full Art. 26 deployerdeployerAn organization using an AI system under its own authority in its activities — carrying operator duties: use per instructions, oversight, input relevance, monitoring, notices.Open full entry → obligations: usage instructions compliance, 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 →, data quality controls, post-market monitoringpost-market monitoringProvider-side duty to systematically collect and act on experience from systems in use — the product-regulation half of continuous monitoring.Open full entry →, log retention, individual transparencytransparencyOpenness about the fact that AI is used and how it operates in general: disclosures, documentation, notices. Pairs with explainability, which addresses individual outcomes.Open full entry →, and in some cases 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 → and 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 →. Non-high-risk AI, depending on type, may require only transparency disclosures or nothing at all.

The classification decision is therefore one of the most consequential compliance choices an organisation makes. This guide walks through the classification methodology step by step.

Step 1: is the system an "AI system" under the EU AI Act?

Art. 3.1 defines an 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 → as "a machine-based system that is designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment, and that, for explicit or implicit objectives, infers, from the input it receives, how to generate outputs such as predictions, content, recommendations, or decisions that can influence real or virtual environments."

Key exclusions from the AI definition:

  • Pure rule-based systems without any machine learningmachine learningThe dominant approach to AI: algorithms that improve at a task by learning patterns from data rather than following rules a human wrote.Open full entry → or inference component
  • Statistical tools that apply fixed mathematical formulas without inference
  • Traditional software automation that follows explicit programming

If your system is not an AI system under Art. 3.1, the EU AI Act does not apply.

Step 2: is the system prohibited under Art. 5?

Before assessing risk class, check against the eight prohibitions of Art. 5. If the system constitutes a prohibited AI practice, no risk classification exercise is needed, it must not be used.

Step 3: does the system fall under Annex i (safety-critical products)?

Check whether the AI system is a safety component of a product regulated by EU harmonisation legislation listed in Annex I (machinery, medical devices, vehicles, etc.). If yes, the system is high-risk under Art. 6.1.

Step 4: does the system fall under Annex III?

Check the system against all eight categories of 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 →. The most commonly relevant for Dutch private-sector deployers:

Annex III categoryExamples
Point 1: Biometric IDFacial recognition for access control (note: some uses removed post-Omnibus)
Point 2: Critical infrastructureAI managing power grid, water systems, banking systems
Point 3: EducationAI affecting admission decisions, exam proctoring with significant impact
Point 4: Employment/HRCV screening, performance evaluation, promotion decisions
Point 5: Essential servicesCredit scoring, insurance underwriting, benefit eligibility
Point 8: Democratic processesVoter registration, election integrity tools

Step 5: does the Art. 6.3 exception apply?

Even if the system falls within Annex III categories, the Art. 6.3 exception may remove it from the high-risk classification if the providerproviderThe actor who develops an AI system (or has it developed) and places it on the market or into service under its own name — carrying manufacturer-style duties: design controls, documentation, conformity.Open full entry → can demonstrate: (1) the system does not make decisions with significant impact on natural persons or supports easily overridable human decisions; (2) no sensitive profiling; (3) limited potential harm.

Request the provider's Art. 6.3 documentation if they claim this exception. Verify it against your actual use case.

Step 6: is your use case adding risk?

Classification depends on how you use the system, not just what the system is capable of. A general-purpose language model used as the sole basis for credit decisions is high-risk in that deployment, even if the model itself is not specifically classified as a credit scoring system. Assess your specific use case against the Annex III categories, not just the system in the abstract.

Borderline cases

  • HR scheduling software with AI: Scheduling AI that generates rosters a planner can freely modify, probably not high-risk. AI that determines working hours or contract terms, potentially high-risk under Annex III, point 4.
  • Customer service chatbots: Limited risk AI (Art. 50 transparency). If the chatbot makes decisions about credit limits or contract changes, high-risk.
  • Marketing recommendation engines: Not high-risk unless targeting vulnerable groups with exploitative techniques (Art. 5.1.b territory).

Compliance checklist

  1. Have you confirmed each AI system meets the Art. 3.1 definition?
  2. Have you assessed each system against Art. 5 before considering risk class?
  3. Have you checked against both Annex I and all eight Annex III categories?
  4. For potential Art. 6.3 systems: have you obtained the provider's written assessment?
  5. Have you assessed your specific use case (not just the abstract system) against the classification criteria?
  6. Is the classification rationale documented for each AI system?
  7. Is there a re-classification process for when use cases change?
Legal referencesArt. 6Art. 5

More on Accountability

Art. 10 EU AI Act: data and data governance for high-risk AI

Reference

Art. 10 requires that the training, validation, and testing data for high-risk AI systems meets quality criteria: relevant, sufficiently representative, and as free of errors and complete as possible for the intended purpose. It also requires documented data governance practices covering collection, preparation, bias examination, and gap mitigation, and it permits the limited processing of special-category data where strictly necessary to detect and correct bias, under safeguards.

Art. 12 EU AI Act: record-keeping and logging for high-risk AI

Reference

Art. 12 requires high-risk AI systems to technically allow for the automatic recording of events (logs) over their lifetime. The logging must enable traceability of the system's functioning at a level appropriate to its intended purpose, support post-market monitoring, and help identify situations that may lead to risk or substantial modification. It is a design obligation on the provider that makes the system auditable by construction.

Art. 19 EU AI Act: keeping the automatically generated logs

Reference

Art. 19 requires providers of high-risk AI systems to keep the logs that the system automatically generates (under Art. 12) for as long as they control them, for a period appropriate to the intended purpose and at least six months unless other law requires longer. It is the retention counterpart to the Art. 12 logging capability, and it works alongside the deployer retention duty in Art. 26.6.

Art. 26.1 EU AI Act: following provider instructions as a deployer

Reference

Art. 26.1 requires deployers to use high-risk AI systems strictly in accordance with the provider's instructions for use. This means using the system only for its intended purpose, within its specified technical configuration, and by qualified users, and documenting that compliance. Deviating from the instructions can shift liability entirely to the deployer.

More on Safety & reliability

Art. 14 EU AI Act: designing high-risk AI for human oversight

Reference

Art. 14 requires providers to design and build high-risk AI systems so that they can be effectively overseen by humans during use. The system must let an overseer understand its capabilities and limits, watch for anomalies, resist automation bias, correctly interpret outputs, decide not to use the system, and intervene or stop it through a kill switch (Art. 14(4)(e)). It is the design obligation that makes the deployer oversight duty of Art. 26.2 possible.

Art. 26.4 EU AI Act: input data quality for deployers

Reference

Art. 26.4 requires deployers of high-risk AI to ensure that input data is relevant and sufficiently representative for the system's intended purpose. The deployer is responsible for data quality in operation, even though the provider sets the specifications under Art. 10.

Art. 26.5 EU AI Act: post-market monitoring for deployers

Reference

Art. 26.5 requires deployers of high-risk AI to monitor the system's operation against the provider's instructions and to report risks and serious incidents. Monitoring is the early-warning mechanism that connects to incident reporting under Art. 73.

Art. 5 EU AI Act: all 8 prohibited AI practices explained

Reference

Art. 5 lists the eight prohibited AI practices, including subliminal manipulation, exploitation of vulnerable groups, social scoring, and untargeted facial-recognition scraping. These prohibitions are absolute, apply to every organisation regardless of size, and have been in force since 2 February 2025.