EU AI Act Art. 43: conformity assessment
Conformity assessment before placing on the market (internal control, or a notified body for Annex III point 1 biometrics)
AIGE-OBL-EUAIA-ART43. Drawn from chapter 08.
Text alternative
- Clause: EU AI Act, Art. 43.
- Duty holder: Provider.
- Applies from: 2027-12-02, Deferred.
- Artefact: Conformity-assessment workflow.
- Layers: Layer 01, Layer 05.
- Evidence record: Go/no-go decision.
- Record schemas: Go/no-go decision .
- The same topic in 23 other frameworks; the crosswalk section below links each clause.
Data table: the dates
| Date | Step | Detail |
|---|---|---|
| 2027-12-02 | Deferred | Annex III |
| 2028-08-02 | High-risk (Annex I) | Applies to Annex I embedded (product safety-component) systems |
| 2030-08-02 | Later step | Deadline for legacy high-risk systems intended for use by public authorities (Art. 111(2)) |
- Id
AIGE-OBL-EUAIA-ART43- Instrument
- EU AI Act (post-Omnibus) law
- Compared side by side
- ISO 42001 vs EU AI Act · NIST AI RMF vs EU AI Act
- Clause
- Art. 43
- Duty holder
- Provider
- Authority
- National MSA
- Applies from
- Deferred · Annex III
- Later dates
-
- Applies to Annex I embedded (product safety-component) systems
- Deadline for legacy high-risk systems intended for use by public authorities (Art. 111(2))
- System class
- High-risk (Annex III) · High-risk (Annex I)
The artefact that evidences it
Conformity-assessment workflow; internal-control or notified-body evidence pack; traceability to Annex IV documentation.
Data table: every relation
| Family | Item | Relation |
|---|---|---|
| Same crosswalk topic | AI Verify 1.1.6, 1.7.2, 1.1.1, 9.4.1, 5.14.1, 6.5.1, 4.6.1 | Core clause |
| Same crosswalk topic | CSA AICM MDS-03, MDS-04, A&A-02, A&A-04, AIS-06, CCC-01, DSP-02 | Core clause |
| Same crosswalk topic | China AI Labelling Label Art. 4, Label Art. 5 | Core clause |
| Same crosswalk topic | China Deep Synthesis DeepSyn Art. 16, DeepSyn Art. 17 | Core clause |
| Same crosswalk topic | China GenAI Measures GenAI Art. 12, GenAI Art. 19, GenAI Art. 17 | Core clause |
| Same crosswalk topic | CoE Convention CoE Art. 14(2), CoE Art. 15(2), CoE Art. 16(2)(g) | Core clause |
| Same crosswalk topic | EU AI Act Art. 11, Art. 13, Art. 53, Art. 50, Art. 86, Art. 18, Art. 53(1)(d), Art. 50(2), 50(4), Art. 47, Art. 48, Art. 40, Art. 26, Art. 25, Art. 20, Art. 79 | Core clause |
| Same crosswalk topic | G7 Code G7 Action 3 | Core clause |
| Same crosswalk topic | GAO AI Accountability 1.9, 3.5, 1.7, 1.8, 4.4, 4.5 | Core clause |
| Same crosswalk topic | GDPR Arts. 13–14, Art. 30, Art. 42 | Core clause |
| Same crosswalk topic | GPAI Code Transparency 1.1, Transparency 1.2 | Core clause |
| Same crosswalk topic | ISO 42001 7.5, A.6, A.8, 9.2, A.6.2.5, A.6.2.6, A.9 | Core clause |
| Same crosswalk topic | ISO 42006 ISO/IEC 42006 | Core clause |
| Same crosswalk topic | Korea AI Act Art. 31, Art. 34(1)(2), Art. 33 | Core clause |
| Same crosswalk topic | NIST AI RMF MAP 1, MEASURE 2.8, MAP 1.6, MEASURE 2.9, MEASURE 1.3, MANAGE 2.4, MANAGE 4.1, GOVERN 1.7 | Core clause |
| Same crosswalk topic | OECD AI Principles OECD 1.3, OECD 1.4 | Core clause |
| Same crosswalk topic | Singapore GenAI GenAI 3, GenAI 5 | Core clause |
| Same crosswalk topic | UK ATRS ATRS Tier 1, ATRS 2.2 | Core clause |
| Same crosswalk topic | China Algo. Rec. AlgoRec Art. 16 | Related clause |
| Same crosswalk topic | EN 18286 EN 18286 | Related clause |
| Same crosswalk topic | GB/T 45654 GB/T 45654 Content labelling | Related clause |
| Same crosswalk topic | Singapore Agentic Agentic 2.3.3 | Related clause |
| Same crosswalk topic | TC260 Framework 3.0 TC260 5.3, TC260 5.3.19 | Related clause |
Patterns that build it
No pattern in the catalogue names this clause on its "Maps to" line yet; the artefact above is the engineering answer.
The same topic in other frameworks
From the topic crosswalk: the clauses filed under the same topics as this one. Mappings are illustrative, not a claim of conformity.
Documentation and transparency
- EU AI Act Art. 11 Technical documentation (core)
- EU AI Act Art. 13 Transparency and provision of information to deployers (core)
- EU AI Act Art. 53 Obligations for providers of general-purpose AI models (core)
- ISO 42001 7.5 Documented information (core)
- ISO 42001 A.6 AI system life cycle (core)
- ISO 42001 A.8 Information for interested parties (core)
- China AI Labelling Label Art. 4 Explicit labels for generated content (core)
- China AI Labelling Label Art. 5 Implicit (metadata) labels (core)
- China GenAI Measures GenAI Art. 12 Labelling of generated content (core)
- China Deep Synthesis DeepSyn Art. 16 Implicit technical labels (core)
- China Deep Synthesis DeepSyn Art. 17 Conspicuous labels for confusable content (core)
- GPAI Code Transparency 1.1 Drawing up and keeping up-to-date model documentation (core)
- GDPR Arts. 13–14 Information to be provided to the data subject (core)
- CSA AICM MDS-03 Model Documentation (core)
- Korea AI Act Art. 31 Transparency: prior notice, output labelling, realistic synthetic content (core)
- UK ATRS ATRS Tier 1 Summary information (core)
- Singapore GenAI GenAI 3 Trusted Development and Deployment (core)
- CoE Convention CoE Art. 14(2) Documentation sufficient to contest decisions; complaint to authorities (core)
- OECD AI Principles OECD 1.3 Transparency and explainability (core)
- G7 Code G7 Action 3 Publicly report capabilities, limitations and domains of use (core)
- GAO AI Accountability 1.9 Transparency: enable external stakeholders to access information on the design, operation, and limitations of the AI system (core)
- GAO AI Accountability 3.5 Documentation: document the methods for assessment, performance metrics, and outcomes of the AI system (core)
- AI Verify 1.1.6 Transparency: publicly report accuracy, intended use cases, limitations, risk assessment and mitigations to stakeholders (core)
- AI Verify 1.7.2 Transparency: make model or system cards publicly available where warranted by public interest (core)
- EU AI Act Art. 50 Transparency obligations for providers and deployers of certain AI systems
- NIST AI RMF MAP 1 MAP 1: Context is established and understood
- NIST AI RMF MEASURE 2.8 MEASURE 2.8: Risks associated with transparency and accountability are examined and documented
- China GenAI Measures GenAI Art. 19 Disclosure to regulators
- China Algo. Rec. AlgoRec Art. 16 Notice that recommendation is used
- GB/T 45654 GB/T 45654 Content labelling Generated-content labelling requirements (clause not verified)
- EU AI Act Art. 86 Right to explanation of individual decision-making
- EU AI Act Art. 18 Documentation keeping
- EU AI Act Art. 53(1)(d) Public summary of the content used for training
- EU AI Act Art. 50(2), 50(4) Machine-readable marking of synthetic content; disclosure of deep fakes
- GPAI Code Transparency 1.2 Providing relevant information
- GDPR Art. 30 Records of processing activities
- NIST AI RMF MAP 1.6 MAP 1.6: System requirements are elicited from and understood by relevant AI actors. Design decisions take socio-technical implications into account to address AI risks
- NIST AI RMF MEASURE 2.9 MEASURE 2.9: The AI model is explained, validated, and documented, and AI system output is interpreted within its context as identified in the MAP function to inform responsible use and governance
- CSA AICM MDS-04 Model Documentation Requirements
- Korea AI Act Art. 34(1)(2) Explanation plan: result, main criteria, training-data overview
- UK ATRS ATRS 2.2 Description and rationale
- CoE Convention CoE Art. 15(2) Notification of interaction with an AI system
- GAO AI Accountability 1.7 Specifications: establish and document technical specifications
- AI Verify 1.1.1 Transparency: design an in-house policy on communication to consumers that articulates the principles for transparency
Conformity assessment and certification
- ISO 42006 ISO/IEC 42006 Requirements for bodies providing audit and certification of AI management systems (core)
- CSA AICM A&A-02 Independent Assessments (core)
- EU AI Act Art. 47 EU declaration of conformity
- EU AI Act Art. 48 CE marking
- EU AI Act Art. 40 Harmonised standards and standardisation deliverables
- GDPR Art. 42 Certification (clause not verified)
- ISO 42001 9.2 Internal audit (clause not verified)
- NIST AI RMF MEASURE 1.3 MEASURE 1.3: Internal experts who did not serve as front-line developers for the system and/or independent assessors are involved in regular assessments and updates
- CSA AICM A&A-04 Requirements Compliance
- Korea AI Act Art. 33 Confirmation of high-impact AI
- Singapore GenAI GenAI 5 Testing and Assurance
- EN 18286 EN 18286 Quality management system for EU AI Act regulatory purposes
- China GenAI Measures GenAI Art. 17 Security assessment and algorithm filing
- GAO AI Accountability 1.8 Compliance: ensure the AI system complies with relevant laws, regulations, standards, and guidance
Deployment, change and decommissioning
- EU AI Act Art. 26 Obligations of deployers of high-risk AI systems (core)
- ISO 42001 A.6.2.5 AI system deployment (core) (clause not verified)
- ISO 42001 A.6.2.6 AI system operation and monitoring (core) (clause not verified)
- NIST AI RMF MANAGE 2.4 MANAGE 2.4: Mechanisms are in place and applied, and responsibilities are assigned and understood, to supersede, disengage, or deactivate AI systems that demonstrate performance or outcomes inconsistent with intended use (core)
- NIST AI RMF MANAGE 4.1 MANAGE 4.1: Post-deployment AI system monitoring plans are implemented, including mechanisms for capturing and evaluating input from users and other relevant AI actors, appeal and override, decommissioning, incident response, recovery, and change management (core)
- NIST AI RMF GOVERN 1.7 GOVERN 1.7: Processes and procedures are in place for decommissioning and phasing out AI systems safely and in a manner that does not increase risks or decrease the organization's trustworthiness (core)
- CSA AICM AIS-06 Secure Application Deployment (core)
- AI Verify 9.4.1 Accountability: a policy to deactivate, decommission and phase out AI systems safely (core)
- AI Verify 5.14.1 Security: proper and secure disposal of data and models (core)
- AI Verify 6.5.1 Robustness: review changes in code, input data and output data to decide when a new robustness review is due (core)
- EU AI Act Art. 25 Responsibilities along the AI value chain
- EU AI Act Art. 20 Corrective actions and duty of information
- EU AI Act Art. 79 Procedure at national level for dealing with AI systems presenting a risk
- EU AI Act Art. 86 Right to explanation of individual decision-making
- ISO 42001 A.9 Use of AI systems
- CSA AICM CCC-01 Change Management Policy and Procedures
- CSA AICM DSP-02 Secure Disposal
- Singapore Agentic Agentic 2.3.3 When deploying, continuously monitor and test
- CoE Convention CoE Art. 16(2)(g) Testing before first use and when significantly modified
- OECD AI Principles OECD 1.4 Robustness, security and safety
- TC260 Framework 3.0 TC260 5.3 Operators' safety guidelines
- TC260 Framework 3.0 TC260 5.3.19 Re-assessment on material change
- GAO AI Accountability 4.4 Ongoing assessment: assess the utility of the AI system to ensure its relevance to the current context
- GAO AI Accountability 4.5 Scaling: identify conditions, if any, under which the AI system may be scaled or expanded beyond its current use
- AI Verify 4.6.1 Safety: deployment strategies such as blue-green and canary deployments
Source
Chapter 08, section EU AI Act, post-Omnibus, checked against its sources on the review date above.
Machine-readable
- This obligation:
/api/v1/obligations/aige-obl-euaia-art43.json - The register:
/api/v1/obligations.json· CSV - Schema and stability promise: open data and API
Cite this obligation
García Aibar, J. (2026). EU AI Act Art. 43: conformity assessment (AIGE-OBL-EUAIA-ART43). In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0). https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/obligations/aige-obl-euaia-art43. CC BY 4.0
BibTeX
@misc{aige2026obligation,
author = {Jorge García Aibar},
title = {{EU AI Act Art. 43: conformity assessment (AIGE-OBL-EUAIA-ART43)}},
howpublished = {In AI Governance Engineering: The Thesis \& Body of Knowledge},
year = {2026},
version = {0.5.0},
doi = {10.5281/zenodo.22956197},
url = {https://aigovernanceengineer.com/obligations/aige-obl-euaia-art43},
note = {Version 0.5.0}
}