Do we need to perform a FRIA and how do we approach it?

education

Recidivism scoring in police work: when the assessment must be redone

A police service deploys an AI system that estimates the recidivism risk of a suspect, as an aid to the judgements later made by the prosecution service and the court. The model is subsequently retrained on newer investigative data and use is extended to a second region. The question is whether the assessment made for first use remains adequate.

Provenance: Article 27(1) requires deployers which are bodies governed by public law to perform, prior to deploying a high-risk AI system referred to in Article 6(2), an assessment of the impact on fundamental rights that its use may produce, with the exception of systems intended to be used in the area listed in point 2 of Annex III. That assessment consists of a description of the processes in which the system will be used, of the period and frequency of use, of the categories of natural persons and groups likely to be affected, of the specific risks of harm taking into account the information given by the provider pursuant to Article 13, of the implementation of human oversight measures according to the instructions for use, and of the measures to be taken if those risks materialise. Article 27(2) provides that the obligation applies to the first use, that previously conducted impact assessments or existing assessments carried out by the provider may be relied on in similar cases, and that a deployer who considers during use that any element listed in paragraph 1 has changed or is no longer up to date shall take the necessary steps to update the information. Article 27(3) provides that the results are notified to the market surveillance authority together with the filled-out template, and that in the case referred to in Article 46(1) an exemption from that notification duty may apply.

We read Article 27 as covering a police service as a body governed by public law under paragraph 1, and as an assessment that does not stop at first use: retraining on newer investigative data or extending use to a second region touches the elements of paragraph 1 and, on our reading, calls for updating the record. That retraining also raises a question Article 27 itself does not answer, namely whether the change goes far enough to count as a substantial modification, which would make you a provider in your own right under Article 25. Bear in mind as well that the exception in paragraph 3 concerns, on our reading, the notification and not the assessment itself. Finally, start that assessment only after establishing that the deployment as such is permitted, because Article 5 rules out certain predictive applications in criminal investigation.

Editorial example. The rule above is in the Regulation. The situation was written by us to show how that rule plays out in this sector, and is not taken from a worked case in official guidance.

Artikel 27, leden 1 tot en met 3

education

Selection at student admission: a DPIA is not yet a FRIA

A university of applied sciences has an AI system rank applications for a vocational programme, using the exam results of earlier students to calibrate that ranking. A data protection impact assessment already exists for this processing. The question the school asks is whether that also covers the fundamental rights side of admission.

Provenance: Article 27(1) provides that deployers which are bodies governed by public law, or private entities providing public services, and deployers of high-risk AI systems referred to in points 5(b) and (c) of Annex III, shall perform an assessment of the impact on fundamental rights prior to deploying a high-risk AI system referred to in Article 6(2), with the exception of systems intended to be used in the area listed in point 2 of Annex III. That assessment consists of a description of the deployer's processes in which the system will be used in line with its intended purpose, of the period and frequency of use, of the categories of natural persons and groups likely to be affected, of the specific risks of harm to those categories, of the implementation of human oversight measures, and of the measures to be taken if those risks materialise, including the arrangements for internal governance and complaint mechanisms. Article 27(2) provides that the obligation applies to the first use, that the deployer may in similar cases rely on previously conducted impact assessments or existing assessments carried out by the provider, and that a deployer who considers during use that any element listed in paragraph 1 has changed or is no longer up to date shall take the necessary steps to update the information. Article 27(4) provides that where an obligation under this Article is already met through the data protection impact assessment conducted pursuant to Article 35 of Regulation (EU) 2016/679 or Article 27 of Directive (EU) 2016/680, the assessment under paragraph 1 complements that data protection impact assessment.

We read Article 27 as placing the education institution that runs this selection itself in the deployer role, but that alone does not settle the duty. Paragraph 1 names bodies governed by public law and private entities providing public services, and whether a state-funded or a private university of applied sciences answers to either description is the question you have to settle first. If it does, an existing data protection impact assessment is on our reading the starting point rather than the last word: paragraph 4 has the fundamental rights assessment sit alongside it, and since Regulation (EU) 2026/1744 that assessment may incorporate or cross-refer to relevant parts of it, so the real question is which elements of paragraph 1 are still missing. For you that means recording which groups of students may be affected, how the admissions committee or the teacher can correct an outcome, and where a rejected applicant can lodge a complaint. If the selection rule or the assessment component underpinning the ranking changes, that is on our reading the moment to update the record, rather than the start of the next academic year.

Editorial example. The rule above is in the Regulation. The situation was written by us to show how that rule plays out in this sector, and is not taken from a worked case in official guidance.

Artikel 27, leden 1, 2 en 4

education

Health insurer using AI for risk assessment: public or private makes no difference

A health insurer uses AI for risk assessment and pricing of health and life insurance. The question is whether this falls under point 5(c) of Annex III, and with that whether the Article 27 FRIA duty comes into play.

Provenance: The Commission draft guidelines of 19 May 2026 state that the health and life insurance in point 5(c) may be offered on a private or a public basis: a health insurer governed by public law also falls within it, so long as the system is intended for risk assessment or pricing with regard to natural persons. Privately serviced health insurance counts as an essential private service, even in a Member State with a public healthcare system. Unlike point 5(b), point 5(c) provides no exception for fraud detection. The document is a consultation version: non-binding and not yet final.

For the FRIA question point 5(c) counts twice: it makes the system high-risk and it makes you, as deployer, one of the parties Article 27 names. A public-law form or a public healthcare system in your Member State changes nothing there. Do not count on the fraud-detection exception from point 5(b) either: it does not apply here, and a fraud feature alongside risk assessment does not take the system out.

Draft guidelines on high-risk AI classification, 19 May 2026, annex on Annex III, paragraphs (319) to (321)

education

Candidate recommendation that automatically becomes a decision

An employer uses a system that ranks applicants and recommends a candidate to hire. In one setup a recruiter weighs that recommendation in their own assessment; in the other the outcome is applied automatically and a candidate is rejected without anyone looking at it.

Provenance: The Commission draft guidelines of 19 May 2026 address this case when determining whether an application falls under Annex III. The document is a consultation version: non-binding and not yet final.

Assess a recruitment system on its intended purpose rather than on whether a recruiter reviews the output, because adding or removing human involvement does not change its high-risk classification.

Draft guidelines on high-risk AI classification, 19 May 2026, annex on Annex III

Article 6 has two separate routes to high-risk

The European Commission's draft guidelines on the classification of high-risk AI of 19 May 2026, which are expressly non-binding, state in paragraph (7) that an AI system is high-risk in two scenarios: first, where it is intended to be used as a safety component of a product, or is itself a product, covered by the Union harmonisation legislation listed in Annex I and required to undergo third-party conformity assessment; and second, where it falls within one of the use cases in the areas listed in Annex III. Paragraph (448) of those same draft guidelines notes that the Article 113 application dates have been postponed by the AI Omnibus to 2 December 2027 for the Article 6(2) route and 2 August 2028 for the Article 6(1) route.

Draft guidelines on high-risk AI classification (19 May 2026), General principles chapter, section II, paragraph (7); section V, paragraph (448)

Broadly positioned and general purpose AI systems: a disclaimer is not enough

According to the non-binding draft guidelines of 19 May 2026 on the classification of high-risk AI, paragraph (12) provides that where the instructions for use, contractual arrangements, terms of service, usage policy, promotional and sales materials or technical documentation present the AI system as broadly applicable across a generality of contexts and functions, and do not consistently limit its application or exclude high-risk uses, the system's intended purpose will be deemed to also encompass high-risk use cases and therefore qualify as high-risk. Under these draft guidelines this applies in particular where such uses are feasible and reasonably foreseeable given the system's functionalities and capabilities. The same paragraph states that merely asserting, for example in the terms of service, that high-risk uses are excluded is insufficient where the provider's overall presentation, examples or product positioning effectively provides for or promotes such uses, and that any limitations of use must be described clearly, concretely and coherently across all materials.

Draft guidelines on high-risk AI classification (19 May 2026), General principles chapter, section II.2, paragraph (12)

High-risk does not mean prohibited, and not high-risk does not mean permitted

The draft guidelines of 19 May 2026 on the classification of high-risk AI, which are not binding, state in paragraph (3) that the fact an AI system is listed as an example in these guidelines does not mean its use should automatically be considered lawful, since such use would still need to comply with other applicable legislation, and in paragraph (4) that the scope of these guidelines is limited to whether an AI system is high-risk or not. In the Annex III chapter of this draft, paragraph (68) states that classifying systems as high-risk under Article 6(2) does not mean their use is prohibited, but that those systems are subject to appropriate requirements. Paragraphs (82) and (83) of this draft explain the wording in so far as their use is permitted under relevant Union or national law and state that falling within a use case does not necessarily mean the system may lawfully be used in those cases, that in addition to the prohibitions other provisions of Union or national law may restrict use, and that under Article 2(9) the AI Act applies without prejudice to rules on consumer protection, product safety and data protection.

Draft guidelines on high-risk AI classification (19 May 2026), General principles chapter, paragraphs (3) and (4); Annex III chapter, paragraph (68) and section 2.6, paragraphs (82) and (83)

Split and agentic architectures are assessed as a whole

The non-binding draft guidelines of 19 May 2026 provide in paragraphs 75, 76 and 90 that where several AI systems form part of a more complex whole and their combined intended purpose or joint outputs materially influence an individual decision, that configuration is treated as a single AI system for classification. The draft expressly states that split architectures are assessed as a whole to prevent circumvention by system design, that exemptions for individual modules do not apply where the overall configuration influences key aspects of the decision, and that this also extends to complex interconnected setups such as agentic AI systems whose linked actions jointly serve a high-risk purpose. Under the same draft, strictly procedural or preparatory functions do remain eligible for exemption where they are genuinely separable from the system and do not structure or feed outputs that materially influence the examination of an individual case.

Section IV.2.3, paragraphs 75 and 76, and section IV.2.7.1 paragraph 90