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Across 10 modules • Updated May 17, 2026
Author
Sorena AI
Published
May 9, 2026
Updated
May 17, 2026
EU AI Act GPAI and Systemic-Risk Duties: Article 53 and 55

When is a GPAI model classified as having systemic risk?

Article 51 classifies a general-purpose AI model as a GPAI model with systemic risk if it has high-impact capabilities, or if the Commission designates it after an ex officio assessment or a qualified alert from the scientific panel using Annex XIII criteria.

The Act creates a compute-based presumption: a GPAI model is presumed to have high-impact capabilities when the cumulative computation used for training is greater than 10^25 floating point operations. Article 52 then requires notification to the Commission without delay and in any event within two weeks after the requirement is met or it becomes known that it will be met.

  • Record the model's training compute estimate, methodology, and supporting evidence before market placement decisions.
  • Escalate if training compute exceeds 10^25 FLOP or if model reach, modalities, autonomy, scalability, tools, user base, or training data suggest Annex XIII significance.
  • If relying on the Article 52 exception argument, keep objective evidence for why the model does not present systemic risk despite meeting the high-impact presumption.
  • Track Commission designation and reassessment decisions because systemic-risk status changes the provider duty set.
Citations
EU AI Act GPAI and Systemic-Risk Duties: Article 53 and 55

What extra duties apply under Article 55 for GPAI models with systemic risk?

Article 55 duties apply in addition to Articles 53 and 54. Providers of GPAI models with systemic risk must evaluate the model with state-of-the-art protocols and tools, conduct and document adversarial testing, assess and mitigate systemic risks at Union level, track and report serious incidents, and protect the model and its physical infrastructure with adequate cybersecurity.

The Article 55 work should be continuous across development, placing on the market, and use. It should cover sources of systemic risk, post-market learning from incidents and misuse, corrective measures, and security risks such as model leakage, unauthorised releases, circumvention of safety measures, unauthorised access, and model theft.

  • Model evaluation file: protocols, benchmarks or other methodologies, evaluation criteria, metrics, results, known limitations, and who performed the evaluation.
  • Adversarial testing file: internal or external testing plan, test scope, model adaptations, red-team findings, mitigation decisions, and unresolved risk rationale.
  • Systemic-risk file: Union-level risk sources, affected public interests, likelihood and severity, mitigation measures, residual risk, and post-market monitoring triggers.
  • Serious-incident file: incident facts, model version, affected use or integration, known or likely harm, corrective measures, reporting route to the AI Office and, where appropriate, national competent authorities.
  • Cybersecurity file: controls for weights, algorithms, servers, datasets, access management, physical security, leak prevention, vulnerability handling, and attack response.
Citations
EU AI Act GPAI and Systemic-Risk Duties: Article 53 and 55

How do copyright policy, training summaries, open-source models, and the Code of Practice fit together?

The Article 53 copyright policy and public training-content summary are separate duties. The copyright policy is an internal compliance policy for Union copyright and related-rights law. The public summary is a transparency artifact about the content used for model training, published according to the AI Office template.

Open-source status can reduce some Article 53 documentation duties only when the licence and public availability conditions are met, and it does not remove the copyright-policy or training-summary duties. It also does not exempt GPAI models with systemic risk from the transparency-related obligations.

  • Copyright policy: identify and comply with rights reservations under Article 4(3) of Directive (EU) 2019/790, including through state-of-the-art technologies where relevant.
  • Training-content summary: publish a sufficiently detailed summary using the AI Office template, generally comprehensive in scope while protecting trade secrets and confidential business information.
  • Open-source caveat: Article 53(2) excludes only Article 53(1)(a) and (b) for qualifying open-source GPAI models, and not for GPAI models with systemic risk.
  • Code of Practice caveat: providers may rely on approved codes of practice to demonstrate compliance until harmonised standards are published, but providers outside an approved code or standard must show alternative adequate means to the Commission.
  • Copyright Code caveat: the GPAI Copyright Chapter helps demonstrate Article 53(1)(c) implementation, but it does not itself decide compliance with Union copyright law.
Citations
EU AI Act GPAI and Systemic-Risk Duties: Article 53 and 55

What staged application and enforcement points are supported for GPAI duties?

The Commission guidelines state that Chapter V obligations for GPAI model providers apply from 2 August 2025. They also state that Commission enforcement powers for these obligations enter into application on 2 August 2026, and that providers of GPAI models placed on the market before 2 August 2025 must take necessary compliance steps by 2 August 2027.

The same guidance says the guidelines are not legally binding and that authoritative interpretation of the AI Act is for the Court of Justice of the European Union. Treat the dates above as implementation milestones grounded in the cited Commission guidance, not as a complete enforcement calendar for every AI Act duty.

  • From 2 August 2025: Chapter V GPAI provider obligations enter into application according to the Commission guidelines.
  • From 2 August 2026: the Commission says its enforcement powers for GPAI provider obligations enter into application, including fines under Article 101.
  • By 2 August 2027: providers of GPAI models placed on the market before 2 August 2025 must take necessary steps to comply, according to the guidelines and Article 111(3) reference.
  • Do not use this GPAI FAQ to infer deadlines for unrelated high-risk AI system, prohibited-practice, transparency, product-law, or national-authority obligations.
Citations
EU AI Act post-market monitoring FAQ for high-risk AI systems

What does Article 72 require for EU AI Act post-market monitoring?

Article 72 requires providers of high-risk AI systems to establish and document a post-market monitoring system that is proportionate to the AI technologies and risks of the system. The system must actively and systematically collect, document, and analyse relevant data on the high-risk AI system's performance throughout its lifetime.

The monitoring system should be tied to a post-market monitoring plan that forms part of the Annex IV technical documentation. That means the plan should be maintained with the product file, not kept as an informal support-process note.

  • Define the monitored high-risk AI system, intended purpose, deployed versions, integrations, and known interaction points with other AI systems.
  • Specify which performance, safety, fundamental-rights, robustness, cybersecurity, anomaly, complaint, and incident signals are collected after deployment.
  • Explain how deployer feedback and other external sources are triaged, documented, analysed, and fed into risk management and technical documentation updates.
  • Link monitoring outputs to Article 20 corrective action and Article 73 serious-incident reporting so risk signals do not stop at product support.
  • Keep the monitoring plan with the technical documentation and update the lifecycle change record when provider-made changes affect the system.
Citations
EU AI Act post-market monitoring FAQ for high-risk AI systems

How should deployer feedback, serious incidents, logs, and corrective action connect?

Deployers are not the Article 72 plan owner, but Article 26 makes them important monitoring inputs. Deployers must monitor high-risk AI systems on the basis of the instructions for use and, where relevant, inform providers under Article 72.

If a deployer has reason to consider that use in accordance with the instructions may present a risk under Article 79(1), the deployer must inform the provider or distributor and the relevant market surveillance authority without undue delay and suspend use. If the deployer identifies a serious incident, it must immediately inform the provider first, then the importer or distributor and the relevant market surveillance authorities; if the provider cannot be reached, Article 73 applies mutatis mutandis.

Provider handling should therefore separate ordinary performance feedback from nonconformity, risk, and serious-incident paths. Article 20 requires providers that consider or have reason to consider their high-risk AI system is not in conformity to immediately take corrective action to bring it into conformity, withdraw it, disable it, or recall it as appropriate.

  • Deployer feedback intake: capture the system, version, use context, instruction-for-use step, observed output, affected persons or groups, operator action, and available logs.
  • Risk escalation: if the deployer reports an Article 79(1)-type risk, record the suspension status, market-surveillance authority notice, and provider response owner.
  • Serious-incident escalation: link the record to Article 73 reporting analysis, causal-link assessment, authority routing, investigation, risk assessment, and corrective action.
  • Corrective action: document whether the provider brought the system into conformity, disabled it, withdrew it, recalled it, or informed distributors, deployers, authorised representatives, or importers.
  • Log handling: use Article 12 and Article 19 provider logs and Article 26 deployer-controlled logs to reconstruct the event, but check privacy, sector, and law-enforcement limits before requesting or transferring data.
Citations
EU AI Act post-market monitoring FAQ for high-risk AI systems

What evidence should a high-risk AI provider keep for Article 72?

The evidence should show that monitoring is systematic enough to evaluate continuing compliance, not just that incidents were logged. Keep the plan, the monitored signals, the analysis records, the outcomes, and the technical-documentation updates together so a reviewer can trace why a risk signal did or did not trigger corrective action, a conformity update, or a serious-incident report.

Annex IV also expects technical documentation to describe relevant lifecycle changes and the post-market performance-evaluation system, including the Article 72 monitoring plan. That makes change history part of the post-market monitoring evidence set.

  • Post-market monitoring plan: scope, data sources, deployer-feedback channels, signal taxonomy, analysis cadence, escalation paths, and responsible roles.
  • Signal records: complaints, anomalies, performance drift, bias or discrimination indicators, cybersecurity issues, human-oversight failures, misuse patterns, and interaction issues with other AI systems.
  • Log evidence: provider-controlled automatically generated logs, deployer-controlled logs when shared lawfully, retention basis, access controls, and integrity checks.
  • Decision records: root-cause analysis, continued-compliance assessment, serious-incident determination, corrective-action decision, and authority communication status.
  • Lifecycle records: versions, configuration changes, model or data changes, intended-purpose changes, integration changes, and any substantial-modification or new conformity-assessment trigger considered.
Citations
EU AI Act post-market monitoring FAQ for high-risk AI systems

Which changes should reopen the post-market monitoring review?

Reopen the Article 72 review when the real-world system no longer matches the monitoring plan, instructions for use, technical documentation, or risk-management assumptions. The strongest triggers are changes that affect intended purpose, high-risk classification, performance, affected groups, human oversight, logs, integration context, or risk controls.

A distributor, importer, deployer, or other third party can become the provider for a high-risk AI system if it puts its name or trademark on the system, makes a substantial modification while the system remains high-risk, or modifies the intended purpose of a non-high-risk AI system so it becomes high-risk. Those lifecycle changes should not be treated as ordinary backlog items.

  • New or changed intended purpose, user population, deployment context, country rollout, or affected group.
  • Substantial modification to a high-risk AI system after placement on the market or putting into service.
  • Integration with another AI system, model, data source, workflow, or product that changes performance or risk assumptions.
  • Observed performance drift, repeated anomalies, serious-incident indicators, or unresolved deployer feedback.
  • Changes to logs, human oversight, instructions for use, cybersecurity controls, or maintenance processes that affect traceability or safe operation.
Citations
Regulation (EU) 2024/1689 (EU AI Act)

Primary legal text for Article 25 value-chain responsibility changes, Article 43 substantial-modification conformity assessment, and Annex IV lifecycle-change documentation.

EU AI Act provider vs deployer role boundaries: Article 3 and Article 25

What is the core provider-versus-deployer test under Article 3 of the EU AI Act?

A provider is the actor that develops an AI system or general-purpose AI model, or has one developed, and places it on the market or puts the AI system into service under its own name or trademark. That test is about development control, commissioning, market placement, service launch, and branding, not only technical authorship.

A deployer is the actor using an AI system under its authority, except for personal non-professional use. A company can therefore be a deployer of a supplier system even when the supplier remains the provider, because the company controls the concrete use context, users, operating process, input data under its control, and internal oversight.

  • Treat name, trademark, market-placement records, commissioning contracts, technical documentation, and launch materials as provider evidence.
  • Treat business-process ownership, user instructions, access controls, input-data procedures, monitoring records, and logs under the organisation's control as deployer evidence.
  • Do not use 'owner' as a substitute role. The AI Act uses defined actors such as provider, deployer, importer, distributor, authorised representative, product manufacturer, and operator.
  • Classify each system and model separately. A party can be the deployer of one AI system, the provider of a modified high-risk system, and a downstream provider integrating a GPAI model in another product.
Citations
EU AI Act provider vs deployer role boundaries: Article 3 and Article 25

How do importer, distributor, authorised representative, product manufacturer, and operator roles fit around provider and deployer roles?

The AI Act uses 'operator' as an umbrella term that includes provider, product manufacturer, deployer, authorised representative, importer, and distributor. It is useful for scoping the full value chain, but it is not enough for assigning concrete duties because the named roles have different triggers.

An authorised representative is a Union-based person with a written mandate from a provider to carry out obligations and procedures on the provider's behalf. An importer places on the Union market an AI system bearing the name or trademark of a third-country person. A distributor is a supply-chain actor, other than provider or importer, that makes an AI system available on the Union market.

A product manufacturer can become the provider of a high-risk AI system when the high-risk AI system is a safety component of a product covered by listed Union harmonisation legislation and is placed on the market or put into service under the product manufacturer's name or trademark.

  • For authorised representatives, keep the written mandate and the provider identity; the mandate does not erase the provider role.
  • For importers, keep evidence of the third-country name or trademark on the AI system and the first Union market placement route.
  • For distributors, keep supply-chain records showing the system was made available without the distributor being the provider or importer.
  • For product manufacturers, keep the product-law file showing whether the AI system is a safety component and whether it is marketed or put into service under the manufacturer's name or trademark.
  • For operators, map every concrete actor to one of the named Article 3 roles before assigning obligations.
Citations
EU AI Act provider vs deployer role boundaries: Article 3 and Article 25

When does Article 25 shift a deployer or other third party into provider status?

Article 25 is the role-shift rule for high-risk AI systems. A distributor, importer, deployer, or other third party is treated as the provider, and is subject to provider obligations, when one of three triggers is met: it puts its name or trademark on an already placed or put-into-service high-risk AI system; it makes a substantial modification to an already placed or put-into-service high-risk AI system so that it remains high-risk; or it changes the intended purpose of an already placed or put-into-service AI system, including a GPAI system, so that the system becomes high-risk.

When an Article 25 shift occurs, the initial provider is no longer considered the provider of that specific AI system for AI Act purposes, but must closely cooperate with the new provider and provide necessary information, technical access, and other reasonably expected assistance. That cooperation rule does not apply where the initial provider clearly specified that its AI system must not be changed into a high-risk system.

  • Rebranding evidence: trademark, UI branding, packaging, app-store listing, customer contract, and public materials showing whose name is attached to the high-risk AI system.
  • Substantial-modification evidence: change request, architecture or operating-system change, model or software change, conformity-impact analysis, and whether the modification was foreseen in the initial conformity assessment.
  • Intended-purpose evidence: original instructions for use, technical documentation, sales materials, new use case, deployment context, and why the changed use brings the system within Article 6 high-risk classification.
  • Cooperation evidence: information requests to the initial provider, technical-access records, assistance received, refusals or limitations, and trade-secret handling.
Citations
EU AI Act provider vs deployer role boundaries: Article 3 and Article 25

How should teams classify GPAI model providers, AI system providers, and downstream providers?

A GPAI model provider is not automatically the provider of every AI system that later integrates the model. The legal text defines a general-purpose AI model separately, and Annex XII requires transparency information for downstream providers that integrate the model into their AI systems.

Commission GPAI guidance gives practical examples: the actor that develops and places a GPAI model on the Union market is the provider; an actor that has a model developed on its behalf and places it on the market is the provider; and a downstream actor integrating a GPAI model into an AI system may be the provider of that AI system.

For downstream modifications, the Commission guidance says not every modification makes the modifier a GPAI model provider. The modifier becomes the provider of the modified GPAI model only where the modification leads to a significant change in the model's generality, capabilities, or systemic risk, with the guidance giving an indicative training-compute criterion for that assessment.

  • Keep separate records for the GPAI model provider, the AI system provider, and the deployer that uses the system in a concrete process.
  • Ask for downstream-provider information listed in Annex XII, including model tasks, integration types, acceptable-use policies, release and distribution methods, licence, input and output modalities, and technical means for integration.
  • If a team fine-tunes or otherwise modifies a GPAI model, record who controlled the modification, what changed, the additional training data or compute evidence available, and whether the change affects generality, capabilities, or systemic risk.
  • If the GPAI model is integrated into a high-risk AI system, preserve the chain from model documentation to system technical documentation, instructions for use, human oversight, monitoring, and conformity evidence.
Citations
EU AI Act provider vs deployer role boundaries: Article 3 and Article 25

What evidence should prove a provider/deployer boundary decision?

The evidence should prove the legal role, the factual trigger, and the boundary of responsibility. Avoid one generic AI owner record. Instead, keep a role matrix for each AI system and GPAI model version, because the same supplier relationship can involve several actors at different layers of the value chain.

For deployer duties, preserve records showing use according to instructions, human oversight assignment, monitoring based on instructions for use, incident escalation to provider/importer/distributor and authorities where relevant, logs under deployer control, worker information where workplace use is involved, and any required fundamental-rights impact assessment for covered high-risk deployments.

  • Role matrix: provider, deployer, importer, distributor, authorised representative, product manufacturer, GPAI model provider, AI system provider, and downstream provider for each model or system version.
  • Market and service evidence: first Union market availability, putting into service, brand or trademark, product bundle, app or API release, and customer-facing materials.
  • Intended-purpose evidence: provider instructions, technical documentation, sales materials, deployment use case, affected user groups, and any changed purpose assessment.
  • Change evidence: modification description, whether the change was foreseen in the initial conformity assessment, impact on high-risk requirements, new conformity-assessment need, and provider cooperation records.
  • GPAI integration evidence: Annex XII-style downstream information, model dependencies, distribution channel, licence, integration means, acceptable-use policy, and modification or fine-tuning record.
  • Deployer operation evidence: oversight assignment, input-data controls, monitoring notes, log-retention rationale, worker or affected-person notices where applicable, and escalation records.
Citations
EU AI Act technical documentation

What does Article 11 require for EU AI Act technical documentation?

For a high-risk AI system, Article 11 makes technical documentation a pre-market or pre-service requirement. The file must be drawn up before the system is placed on the market or put into service, kept up to date, and written to demonstrate compliance with the high-risk requirements in Chapter III, Section 2.

The documentation should let a national competent authority or notified body understand the system without reverse-engineering the product. A usable file therefore starts with system identity and intended purpose, then shows how design, data, testing, risk controls, human oversight, cybersecurity, conformity, and post-market monitoring support that intended purpose.

  • Identify the AI system, provider, version, deployment form, intended purpose, and relevant software, firmware, hardware, API, or embedded-product context.
  • Explain the system architecture, development process, algorithms, design choices, assumptions, expected outputs, output quality, and any third-party pre-trained systems or tools used.
  • Document training, validation, and testing data where relevant, including provenance, scope, main characteristics, selection, labelling, cleaning, and data-governance choices.
  • Include validation and testing procedures, metrics for accuracy and robustness, discrimination-impact checks where relevant, test logs, and dated reports signed by responsible persons.
  • Tie the file to the Article 9 risk-management system, Article 14 human-oversight measures, cybersecurity measures, conformity evidence, and post-market monitoring plan.
Citations
European Commission - AI Act regulatory framework

Commission overview confirming that high-risk AI providers must address documentation, human oversight, robustness, cybersecurity, conformity assessment, registration, declaration of conformity, and CE marking.

EU AI Act technical documentation

Which Annex IV sections should product and engineering teams populate?

Treat Annex IV as a technical-file table of contents. The first section identifies what the system is and how it is supplied. The second section explains how it was built. Later sections show how it is monitored, controlled, tested, changed, and assessed against the AI Act requirements.

The strongest documentation is traceable: every claim about system purpose, data, model behavior, oversight, cybersecurity, performance, and residual risk points to a controlled artifact such as a requirements record, architecture diagram, dataset sheet, test report, risk-control register, release note, user instruction, or conformity file.

  • System identity: provider name, system name, version, relation to prior versions, intended purpose, deployment form, user interface, instructions for use, and hardware or software interactions.
  • Architecture and development: software components, model or algorithm logic, design choices, assumptions, optimization targets, expected output quality, computational resources, third-party systems, and integration or modification decisions.
  • Data: training methodologies and techniques, training datasets, provenance, scope, main characteristics, collection and selection methods, labelling, cleaning, and data-quality gaps that affect compliance.
  • Validation and testing: procedures, validation and test data, metrics for accuracy and robustness, checks against Chapter III Section 2 requirements, discriminatory-impact assessment, signed reports, and test logs.
  • Controls: human-oversight measures, interpretability support for deployers, input-data specifications, cybersecurity measures, risk-management description, lifecycle changes, and post-market performance evaluation.
Citations
EU AI Act technical documentation

How do standards, conformity, and post-market monitoring fit the file?

Annex IV does not stop at design-time evidence. It asks for the harmonised standards applied in full or in part when their references have been published in the Official Journal of the European Union. If no such harmonised standards have been applied, the file must describe the solutions adopted to meet the high-risk requirements and list other relevant standards and technical specifications applied.

The same file should include a copy of the EU declaration of conformity and a detailed description of the post-market system used to evaluate performance. Article 72 makes the post-market monitoring plan part of the Annex IV technical documentation.

  • Standards register: list Official Journal-referenced harmonised standards used in full or in part, and map each one to the AI Act requirement it supports.
  • Alternative solutions: where no harmonised standard is used, document the technical or organisational solution adopted for the relevant Chapter III, Section 2 requirement.
  • Conformity file: include the EU declaration of conformity and keep it aligned with system identity, provider identity, applicable Union law, and any standards or common specifications cited.
  • Post-market plan: describe how performance data, deployer feedback, incidents, lifecycle changes, and interactions with other AI systems will be collected and analysed to evaluate continued compliance.
  • Change control: record relevant lifecycle changes and reassess whether the technical documentation, conformity route, or notified-body assessment needs an update.
Citations
FAQ: EU AI Act conformity assessment procedures and notified body selection

When does Article 43 require a notified body?

Article 43 uses different routes for different high-risk AI systems. For high-risk systems listed in point 1 of Annex III, the provider may use Annex VI internal control only when it demonstrates compliance by applying harmonised standards under Article 40 or, where applicable, common specifications under Article 41.

For that same Annex III point 1 category, Annex VII notified-body assessment is required when harmonised standards and common specifications are not available, when the provider has not applied the relevant harmonised standard or has applied only part of it, when available common specifications have not been applied, or when a harmonised standard has been published with a restriction for the restricted part.

For high-risk AI systems in points 2 to 8 of Annex III, Article 43 says providers follow Annex VI internal control, with no notified-body involvement. For high-risk AI systems covered by the Union harmonisation legislation listed in Section A of Annex I, the provider follows the conformity assessment required by that product law, and the AI Act Section 2 requirements become part of that assessment.

  • Start with the legal basis for high-risk classification: Annex III point 1, Annex III points 2-8, or Annex I Section A product legislation.
  • Record which harmonised standards or common specifications were applied in full, applied in part, unavailable, or published with restrictions.
  • Use Annex VII when Article 43 makes notified-body assessment mandatory for the route, not simply because the system is high risk.
  • Treat a substantial modification after an assessment as a trigger for a new conformity assessment unless the change was pre-determined in the initial technical documentation.
Citations
FAQ: EU AI Act conformity assessment procedures and notified body selection

What evidence supports Annex VI internal control?

Annex VI internal control is still a formal conformity assessment. The provider verifies that its quality management system complies with Article 17, examines the technical documentation to assess compliance with Chapter III Section 2 requirements, and verifies that design, development, and post-market monitoring are consistent with the technical documentation.

The evidence should therefore be more than a checklist. Article 11 requires technical documentation to be drawn up before placing the high-risk AI system on the market or putting it into service, kept up to date, and written so competent authorities and notified bodies can assess compliance. Annex IV lists expected content, including intended purpose, system versions, development methods, data requirements, human oversight, validation and testing, cybersecurity, risk management, standards used, the EU declaration of conformity, and post-market monitoring.

  • Maintain Article 17 quality-management records covering regulatory strategy, design control, development, validation, standards, data management, risk management, post-market monitoring, serious-incident reporting, authority communications, record keeping, resources, and accountability.
  • Keep Article 11 and Annex IV technical documentation current with the system version, intended purpose, interfaces, data, testing, human oversight, cybersecurity, risk management, standards, declaration of conformity, and post-market monitoring plan.
  • Retain the Article 18 evidence set for 10 years after the high-risk AI system is placed on the market or put into service.
  • Link release gates to the provider duties in Article 16: conformity assessment, EU declaration of conformity, CE marking, and Article 49 registration before market placement or service.
Citations
FAQ: EU AI Act conformity assessment procedures and notified body selection

What changes when Annex VII applies?

Annex VII adds notified-body review of both the provider's quality management system and the technical documentation for the AI system. The provider's application includes provider identity, the AI systems covered by the same quality management system, technical documentation for each system, quality-management documentation covering Article 17, procedures to keep the system adequate and effective, and a declaration that the same application was not lodged with another notified body.

The notified body examines whether the quality management system satisfies Article 17 and examines the technical documentation. Where needed, it may require further evidence or tests, carry out tests itself, and, after other reasonable means are insufficient, request access to training and trained models subject to applicable protection for intellectual property and trade secrets. If the system conforms, the notified body issues a Union technical documentation assessment certificate; if not, it refuses and gives reasons.

After approval, Annex VII creates an ongoing change and surveillance track. Intended changes to the approved quality management system, the covered system list, or an AI system change that could affect compliance or intended purpose must be brought to the notified body. The notified body carries out surveillance of the approved quality management system, including periodic audits.

  • Prepare one package for the quality management system and one for the AI system technical documentation.
  • Do not lodge the same Annex VII application with multiple notified bodies at the same time.
  • Plan how the provider will supply further evidence, testing, data-set access, or model access if the notified body requests it within the limits of Annex VII.
  • Track certificate conditions, supplements, refusal reasons, surveillance audit reports, and notified-body change decisions as controlled release records.
Citations
FAQ: EU AI Act conformity assessment procedures and notified body selection

What happens after a successful assessment?

The conformity assessment route should close into release evidence. Article 47 requires the provider to draw up a written, machine-readable, physical, or electronically signed EU declaration of conformity for each high-risk AI system, keep it available to national competent authorities for 10 years, identify the system, state conformity with the Section 2 requirements, include Annex V information, translate it for relevant national competent authorities, and keep it up to date.

Article 48 requires CE marking for high-risk AI systems. For digital high-risk AI systems, a digital CE marking can be used only when it is easily accessible through the system interface or through an accessible machine-readable code or other electronic means. Where a notified body was responsible for the Article 43 conformity assessment, its identification number follows the CE marking and is also indicated in promotional material that mentions CE conformity.

Article 49 registration is separate from CE marking and must be checked before release. Providers or authorised representatives register themselves and Annex III high-risk AI systems in the EU database before placing them on the market or putting them into service, except for point 2 of Annex III. Providers also register systems they concluded are not high risk under Article 6(3). Public authorities, Union institutions, bodies, offices, agencies, and persons acting on their behalf have deployer registration duties for covered Annex III systems before use.

  • Attach the Article 47 declaration to the system record and include Annex V content such as system identification, provider identity, responsibility statement, conformity statement, standards or common specifications, notified-body details where applicable, and signature information.
  • Confirm the CE mark location: interface, machine-readable code, packaging, or accompanying documentation, depending on the system form.
  • When a notified body was involved, include its identification number after the CE marking and in CE-conformity promotional material.
  • Submit and maintain Article 49 and Annex VIII registration information where the system or deployer falls within the registration rules.
Citations
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