Direct answer
We use AI in education or assessment. Is that high risk?
This falls under Annex III: high-risk AI. That obligation applies from 2 December 2027. There is one exception you have to assess yourself.
This could go the other way
- A listed Annex III system may fall outside high-risk under the strict conditions in Article 6(3), except where it profiles. The assessment and registration must be documented.
First step: Justify the Article 6(3) exception against each individual condition.
You describe: AI for admission, evaluation, level determination or exam proctoring in education or vocational training. Likely role: provider (you place the system on the market or into service).
This applies now
- Article 4: AI literacyApplicable
- Article 50: transparencyApplicable
Coming up
- Annex III: high-risk AIfrom 2 December 2027
Then you are the provider. The design and documentation duties sit with you: you build the requirements into the system, record how it works and what it rests on, and declare before deployment that it meets the regulation. Note that you can become a provider without building anything: substantially modifying a purchased system or placing it under your own name takes over that role.
Your first actions
- Justify the Article 6(3) exception against each individual condition. Name which of the four Article 6(3) conditions you invoke, with facts, and separately justify why the system poses no significant risk of harm to health, safety or fundamental rights and does not materially influence the outcome of decision making.
- Take role- and context-specific AI literacy measures. Determine for each role, system and context which combination of instruction, guidance, practice or training is appropriate.
- Implement the applicable disclosure, marking or label. First determine which paragraph of Article 50 applies, then implement the specific transparency measure.
Record this
- Article 49(2) registration record for the system assessed as not high-risk
- AI literacy measures record
- Test report per touchpoint: disclosure visible, timely and accessible
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
education
Application file handling at an educational institution
An educational institution uses AI for application file handling: indexing, searching, text and speech processing, translation of documents submitted with applications, and extracting, transforming and organising the collected data into a usable format.
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.
Indexing, searching, translating and reorganising application files remains preparatory work, as long as the system leaves the substantive judgment on the application entirely to the institution.
Draft guidelines on high-risk AI classification, 19 May 2026, annex on Annex III
education
Customs risk assessment of goods at the external border
An AI system is used by customs authorities to assess the risk that goods entering the EU do not comply with legislation applicable at the border, based on information about the economic operators concerned, such as container number, description of goods, routing, transport and payment method.
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.
Determine what your risk model actually targets, because if it concerns consignments and goods flows rather than personal aspects of individuals, there is no profiling to block the exemption.
Draft guidelines on high-risk AI classification, 19 May 2026, annex on Annex III
education
Automated school assignment by municipalities
Municipalities or regional authorities automatically assign pupils to public schools based on structured data such as home address, school catchment boundaries and available capacity, also factoring in sibling attendance and parental status to keep families together or minimise commuting distance.
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.
Even an assignment on seemingly objective data such as address and capacity counts as profiling here, so as a public body you cannot rely on the Article 6(3) exemption.
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
General interpretation, not legal advice. Checked against Regulation (EU) 2024/1689 and the Digital Omnibus (EU) 2026/1744; the official source remains authoritative.
Full map for your situationExecution
Record the classification in an AI register
A classification without a register and ownership is not demonstrable. Embed AI guides classification, register and reassessment in a fixed approach.
See the Embed AI approach