Why this object hangs off that object

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.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

Assess Article 5, Article 6 and Annex III in that order and document purpose, context and any Article 6(3) exception.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

Establish as the first question whether the system performs profiling of natural persons; if yes, the Article 6(3) route falls away and the system remains high-risk, regardless of the four conditions.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

The Commission draws the line between software that does and does not fall under the regulation.

Hangs off: Annex III: high-risk AI, Article 4: AI literacy

Placed against the official source | scope

The Commission explains in consultation when a system falls under Annex I or Annex III.

Hangs off: Annex III: high-risk AI, Articles 43-49: conformity assessment, CE and registration

Placed against the official source | high-risk

The amended application date has been binding law since 27 July 2026.

Hangs off: Annex III: high-risk AI

Placed against the official source | high-risk

AI as a safety component of products under Annex I follows on 2 August 2028.

Hangs off: Annex III: high-risk AI, Articles 43-49: conformity assessment, CE and registration

Placed against the official source | high-risk, timeline

Reopen classification when intended purpose, use context or system functionality changes materially.

Hangs off: Annex III: high-risk AI

Editorially reviewed | control, high-risk

Block signature of an AI contract until the supplier has answered in writing which Annex III point the intended purpose falls under, whether it relies on Article 6(3), and whether the system profiles natural persons.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

Proof that the system for which you invoke the Article 6(3) exception is registered as Article 49(2) requires, with the registration number linked to the underlying assessment.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

The written assessment with date, author and rationale, drawn up before the system is placed on the market or put into service, ready to be provided to the national competent authority on request.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk

Traceable rationale covering intended purpose, Annex III category, Article 6(3) assessment and registration decision.

Hangs off: Annex III: high-risk AI

Editorially reviewed | evidence, high-risk

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An automated border gate uses biometric facial recognition to compare a traveller’s face with the photo in the passport chip. The same camera could technically also compare against a law-enforcement database, and exactly that difference decides whether this biometrics is high-risk.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system checks a decision, plan or construction made by a human and then provides a substantially different solution.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An accounting firm deploys an AI system that detects money laundering, in order to comply with its own obligations under EU anti-money laundering legislation.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A provider develops a system assessing the creditworthiness of companies by evaluating their company data, balance sheets and financial statements. In a variant, the owner of a legal entity is assessed to back a company loan.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A provider develops an AI system that assesses the creditworthiness of companies using company data, balance sheets and financial statements. The situation where the owner of a legal entity is assessed as backing for a company loan is also addressed.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A provider develops an AI system that establishes the credit score of the owner of a small business or of a company that is not a legal entity. The system uses only business or company data.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system detects and flags incompletely filled-in forms so that they can be returned to the applicant to be completed correctly.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A system audits completed hiring decisions by analysing anonymised recruitment data, including CV scores, interview notes and hiring outcomes, using statistical modelling to detect potential bias or inconsistencies. It plays no role in ongoing recruitment and does not assess identified or identifiable recruiters or applicants.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

The system coordinates appointments with applicants by combining calendars and stated availability, proposes time slots based on logistical constraints such as time zones and maximum daily meetings, sends reminders, and processes accessibility needs such as sign language interpretation, extended interview duration or alternative communication formats.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system is used in assessing data relevant to a decision, for example on public benefits, and provides the human operator with references to the relevant legal provisions, information on jurisdiction and possibly existing internal guidelines relevant to the decision-making process.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system analyses previously completed eligibility checks by public administrators to detect decision-making patterns or deviations, for quality assurance and reporting. It does not propose outcomes on live cases and does not evaluate the performance of staff members, for example in the annual appraisal.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A consultancy firm uses an AI writing assistant to refine managers' promotion reports after evaluations are fully completed. Managers have already recorded the recommendation, justification and ratings; the system improves clarity of language, ensures consistency with corporate style and flags potentially biased wording, after which the manager is required to double-check the revised text.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

Three kinds of auxiliary systems: systems that flag errors or contradictions in finalised human work as a quality-assurance function, systems that map conclusions to evidentiary records to strengthen the traceability of a decision without substituting human judgment, and systems that convert human-validated content for interoperability or accessibility purposes.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A system identifies deviations from previous recruitment decision-making patterns before recruitment is completed, to detect inconsistencies with corporate recruitment policy, while evaluating the personal characteristics of the recruiters conducting the interviews.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

The system aggregates official records, employment history, social network history and, where legally permissible, financial data, plus open-source information, and returns composite risk scores or categories such as low, medium and high risk with alerts such as unexplained employment gaps. In high-volume hiring, candidates flagged as high risk are deprioritised before a caseworker reviews the file.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system is used in the recruitment of employees. It identifies deviations from previous recruitment decision-making patterns to detect potential inconsistencies with corporate recruitment policies, and in doing so also evaluates the personal characteristics of the recruiters conducting the job interviews. The system runs before recruitment is completed.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

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.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A system evaluates written or oral responses given by job applicants in an online assessment, assigns a numerical score based on linguistic and substantive criteria, and generates a ranking used to determine who is invited to the interview stage.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system sorts incoming applications for admission to a school or university by the grade or educational level applied for, placing them into predefined categories such as primary, secondary or specific grades, based on information supplied in the application.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A system in migration and border management scans each submitted visa file, converts scanned documents into text for indexing, automatically files items into fixed, predefined folders such as identity documents, travel itinerary, supporting evidence and translations, and detects exact duplicate attachments and marks them as duplicates.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system in the migration and border management context scans each submitted visa file, converts scanned documents into text for indexing, automatically files items into fixed predefined folders such as identity documents, travel itinerary, supporting evidence and translations, and detects exact duplicate attachments and marks them as duplicates.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A lender uses a model that gives individual applicants a score on which the acceptance decision rests. The same institution also runs a separate model that flags suspicious transactions for fraud investigation.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A university of applied sciences uses software during online exams that flags possible cheating from webcam images and mouse movement. A flag triggers an automatic notification to the exam board.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A police force uses a model that estimates, per suspect, the likelihood of committing another offence, based on the case file and previously established behaviour. That outcome feeds into the prioritisation of ongoing investigations.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A software company supplies a SaaS platform that monitors network traffic at an operator of critical digital infrastructure and reports anomalous patterns to that customer's security team. Its developers see that use at such an operator may fall under point 2 of Annex III and wonder whether their own product therefore becomes a high-risk AI system.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A hospital uses AI to prioritise incoming patients at the emergency department. The question is not whether the system is high-risk but by which route: as a medical device under product legislation, or directly under Annex III.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

A grid operator uses an AI model that automatically balances load and disconnects parts of the electricity network to prevent outages. The same organisation also runs a chatbot that helps customers with billing questions.

Hangs off: Annex III: high-risk AI

Placed against the official source | examples

An AI system can be high-risk in two ways. Either it is itself a product, or a safety component of a product, covered by the Annex I product legislation and that product must undergo third-party conformity assessment (Article 6(1)). Or it falls within one of the use cases listed in Annex III (Article 6(2)). The two routes have their own criteria and their own application dates.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

If you market a system broadly without consistently limiting its application, high-risk use cases will be read into its intended purpose. Merely stating in the terms of service that high-risk uses are excluded is insufficient where the rest of your presentation in fact enables or promotes such uses.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Classification answers one question: which Chapter III obligations apply. It says nothing about whether the use itself is lawful. Prohibited practices, data protection, consumer law, product safety and national law continue to apply in full.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

You cannot avoid classification by splitting a high-risk function into separate modules. The draft assesses the combined configuration.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

A system that falls within an Annex III use case can still escape high-risk classification if it meets one of four conditions. The draft guidelines make clear this is not a broad escape route.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Human involvement does not change the intended purpose and therefore has no effect on classification under Article 6(2). Human oversight is a compliance requirement for high-risk systems, not an escape from the classification.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Human oversight is a compliance requirement for high-risk systems, not a way to escape classification. Human involvement only counts when determining what task the system performs.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

The second condition requires a completed human activity with a result that the system only refines. A materially different outcome does not qualify.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Intended purpose determines whether a system is high-risk. That purpose is set not only by the technical documentation but also by the instructions for use, promotional materials, sales materials and statements by the provider. Reasonably foreseeable misuse falls by definition outside the intended purpose.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Before classification comes into play, the system must meet the definition of an AI system in Article 3(1). Not every software application and not every automated decision-making system falls within the AI Act.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Systems assessing only legal persons fall outside the relevant Annex III use cases. Self-employed people and sole traders do count as natural persons, however.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

The preparatory task under Article 6(3)(d) precedes the assessment. Once the system evaluates the specific case or makes a recommendation, the exception is gone.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

As soon as the system profiles, the Article 6(3) exemption is ruled out. The draft guidelines give three cumulative elements against which you test this.

Hangs off: Annex III: high-risk AI

Placed against the official source | guidance

Classification route for standalone high-risk AI systems under Article 6(2) and Annex III.

Placed against the official source | high-risk

Public classifier for the high-risk use cases in Annex III.

Hangs off: Annex III: high-risk AI

Editorially reviewed | high-risk, template