EU AI Act Art. 13: transparency and information to deployers
Transparency and provision of information to deployers
AIGE-OBL-EUAIA-ART13. Drawn from chapter 08.
Text alternative
- Clause: EU AI Act, Art. 13.
- Duty holder: Provider.
- Applies from: 2027-12-02, Deferred.
- Artefact: Instructions for use….
- Layer: Layer 02 Inventory & Transparency.
- Evidence record: Instructions for use, +1 more.
- Record schemas: Instructions for use , Model card .
- The same topic in 19 other frameworks; the crosswalk section below links each clause.
- Id
AIGE-OBL-EUAIA-ART13- 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. 13
- 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
Instructions for use as code; model and data cards; capability and limitation notes.
Patterns that build it
- Model Card as Control Evidence (layer 2)
- Fairness Eval Suite (layer 3)
- Explanation Artefact (layer 4 and 5)
- Claims Substantiation Gate (layer 5 and 3)
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. 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)
- 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. 43 Conformity assessment
- 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
Explainability and right to explanation
- EU AI Act Art. 86 Right to explanation of individual decision-making (core)
- GDPR Art. 15(1)(h) Meaningful information about the logic involved (core)
- 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 (core)
- CSA AICM GRC-13 Explainability Requirement (core)
- CSA AICM GRC-14 Explainability Evaluation (core)
- Korea AI Act Art. 34(1)(2) Explanation plan: result, main criteria, training-data overview (core)
- UK DUAA UK GDPR Art. 22C Safeguards for automated decision-making (core)
- OECD AI Principles OECD 1.3 Transparency and explainability (core)
- GDPR Art. 13(2)(f) Existence of automated decision-making
- GDPR Art. 22(3) Right to obtain human intervention and to contest the decision
- ISO 42001 A.8.2 System documentation and information for users (clause not verified)
- NIST AI RMF MEASURE 2.8 MEASURE 2.8: Risks associated with transparency and accountability as identified in the MAP function are examined and documented
- UK ATRS ATRS 2.3.5 Appeals and review
- Singapore GenAI GenAI 3 Trusted Development and Deployment
- CoE Convention CoE Art. 14(2) Documentation sufficient to contest decisions; complaint to authorities
- China Algo. Rec. AlgoRec Art. 17 Explain where an algorithm significantly affects user rights
Open controls that evidence it
Draft controls in the open control profiles that map to this row: each states a requirement and the evidence it must leave behind.
-
AIGE-CTL-AGENT-009Approval log, bound to the call (Agent runtime profile) -
AIGE-CTL-AGENT-015Checkpoints on irreversible actions, failing closed (Agent runtime profile) -
AIGE-CTL-DEPLOY-002Instructions for use held and followed (Deployment and monitoring profile)
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-art13.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. 13: transparency and information to deployers (AIGE-OBL-EUAIA-ART13). 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-art13. CC BY 4.0
BibTeX
@misc{aige2026obligation,
author = {Jorge García Aibar},
title = {{EU AI Act Art. 13: transparency and information to deployers (AIGE-OBL-EUAIA-ART13)}},
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-art13},
note = {Version 0.5.0}
}