We use AI in recruitment and selection. Is that high risk?

recruitment and selection

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

recruitment and selection

A CV filter that ranks applicants

An employer has an external recruitment system score and rank every incoming application, after which recruiters only review the top twenty percent by hand. The vendor puts the system on the market under its own name, and the employer uses it in its own selection process.

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.

Recruiters keeping the final say does not help you, because once the system scores or ranks applicants and thereby shapes the shortlist it stays high-risk and no exemption applies.

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

recruitment and selection

Chatbot answering factual questions from a benefits case handler

A chatbot answers a case handler's factual questions relating to the evaluation of a natural person's application for healthcare benefits, for instance the applicant's age. The case handler can grant or deny the benefits based on those answers.

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.

A chatbot that only returns existing facts in structured form falls under the exemption, but once it answers case-specific legal questions it steers the decision and is high-risk.

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

recruitment and selection

AI helping candidates tailor their CV to a vacancy

The system analyses the candidate's CV together with the job description supplied by the candidate and recommends changes to increase the likelihood of being selected for an interview. Those recommendations are shared exclusively with the candidate.

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.

Who initiates the tool decides the outcome here, because an aid started by the candidate whose results reach only the candidate falls outside the recruitment use case.

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

EN 18286:2026: quality management system for EU AI Act regulatory purposes

EN 18286:2026 (Artificial intelligence: Quality management system for EU AI Act regulatory purposes) was drafted by CEN/CLC/JTC 21 under standardisation request M/613 and approved by CEN-CENELEC on 12 July 2026. It is the first JTC 21 deliverable to reach publication. According to a published coverage statement accompanying the standard, not yet confirmed by a second independent source, it addresses Article 17(1) points (a) to (m) and Article 11(1) first sentence, and expressly not Article 17(2) to (4) or Article 72. The standard is NOT currently cited in the Official Journal. The Article 40 presumption of conformity only attaches after that citation.

EN ISO/IEC 42001: artificial intelligence management system

ISO/IEC 42001:2023 is the first certifiable international standard for an AI management system, published on 18 December 2023 and structured on the plan-do-check-act cycle. The text was adopted unchanged as EN ISO/IEC 42001:2026, approved by CEN on 13 March 2026, with national implementation by the member standards bodies. This adoption is not a deliverable under standardisation request M/613: the standard is not cited in the Official Journal and therefore confers no presumption of conformity under Article 40. For Article 17, the designated deliverable under M/613 is EN 18286:2026; that standard is likewise not cited in the Official Journal.

ISO/IEC 23894: guidance on risk management for AI

ISO/IEC 23894:2023 (Information technology: Artificial intelligence: Guidance on risk management) was published in February 2023 and is the first international standard dealing specifically with risk management for AI. It is non-prescriptive and built on the ISO 31000 structure. The text was adopted by CEN-CENELEC as EN ISO/IEC 23894:2024. It is not cited in the Official Journal and therefore confers no presumption of conformity under Article 40 of the AI Act. The deliverable intended to do so for Article 9 is prEN 18228.

ISO/IEC 5259 series: data quality for analytics and machine learning

The ISO/IEC 5259 series (Artificial intelligence: Data quality for analytics and machine learning) comprises five parts: part 1 (overview, terminology and examples), part 2 (data quality measures), part 3 (data quality management requirements and guidelines) and part 4 (data quality process framework), all published in 2024, plus part 5 (data quality governance framework), published in February 2025. CEN-CENELEC has adopted parts as European standards, including EN ISO/IEC 5259-4:2025 and EN ISO/IEC 5259-3:2025. No part is cited in the Official Journal, so no presumption of conformity under Article 40 arises. The deliverable intended to do so for Article 10 is prEN 18284.