EU AI Act Article 10: Data and data governance
Article 10 of the EU AI Act requires high-risk AI providers to govern training, validation, and testing data: quality criteria, examination for bias and protected attributes, and representativeness for the intended purpose. Datasets must be appropriate to the geographical, contextual, behavioural or functional setting in which the system is intended to be used (Art. 10(4)).
- Who
- Providers of high-risk AI systems that train, validate or test on data.
- From when
- 2 Dec 2027 (Annex III), 2 Aug 2028 (Annex I)
- Art. 113(c)(i), as amended
- Maximum fine
- €15M or 3%
- Art. 99(4), point (a), through the provider obligations in Art. 16
Quoted from EUR-Lex
What Article 10 says
1. High-risk AI systems which make use of techniques involving the training of AI models with data shall be developed on the basis of training, validation and testing data sets that meet the quality criteria referred to in paragraphs 2, 3 and 4 of this Article and in Article 4a(1) whenever such data sets are used.
2. Training, validation and testing data sets shall be subject to data governance and management practices appropriate for the intended purpose of the high-risk AI system. Those practices shall concern in particular:
(f) examination in view of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations;
(g) appropriate measures to detect, prevent and mitigate possible biases identified according to point (f);
3. Training, validation and testing data sets shall be relevant, sufficiently representative, and to the best extent possible, free of errors and complete in view of the intended purpose. They shall have the appropriate statistical properties, including, where applicable, as regards the persons or groups of persons in relation to whom the high-risk AI system is intended to be used. Those characteristics of the data sets may be met at the level of individual data sets or at the level of a combination thereof.
4. Data sets shall take into account, to the extent required by the intended purpose, the characteristics or elements that are particular to the specific geographical, contextual, behavioural or functional setting within which the high-risk AI system is intended to be used.
Selected paragraphs, quoted exactly. Read the whole article in Regulation (EU) 2024/1689 on EUR-Lex. Checked 4 Oct 2026.
Regulation (EU) 2026/1744 · in force 27 Jul 2026
What changed
Point (6) of the same Article 1 inserts Article 4a, "Processing of special categories of personal data for bias detection and correction". Removed and context lines quote Regulation (EU) 2024/1689 as adopted; added lines quote the amending Regulation.
Source: Regulation (EU) 2026/1744, Article 1, point (9), verified 4 Oct 2026
The context line is the second paragraph of Article 113, which set the date for Annex III systems before the change. Removed and context lines quote Regulation (EU) 2024/1689 as adopted; added lines quote the amending Regulation.
Source: Regulation (EU) 2026/1744, Article 1, point (40), verified 4 Oct 2026
In plain words
What you must produce
Records of how your training, validation and testing data sets are governed.
- 10(2)(a) to (c)Data governance and management practices: design choices, data collection and origin, data preparation
- 10(2)(f) and (g)An examination for possible biases, and the measures to detect, prevent and mitigate them
- 10(2)(h)The data gaps or shortcomings found, and how they are addressed
- 10(3)Evidence that the data sets are relevant, sufficiently representative and, to the best extent possible, free of errors and complete
A summary to help you plan. The quoted text above is the law.
Coverage: Partial
License Compliance Checker
License Compliance Checker partially addresses Article 10. It surfaces training-data licence and provenance risk via the dataset risk registry (top-50 known datasets flagged with critical / high / medium tiers). Full Article 10 coverage (dataset lineage across runs, bias examination, statistical-property characterisation) is the scope of TraceForge, which is not scheduled and is built on request. LCC covers the licence and provenance part today.
Install
bashpip install license-compliance-checkerWrites: OSS + model licence report (JSON)
From the fact register
Questions about Article 10
- When does Article 10 apply?
- It applies from 2 Dec 2027 for high-risk systems listed in Annex III (Art. 113(c)(i), as amended), and from 2 Aug 2028 for high-risk systems covered by Annex I (Art. 113(c)(ii), as amended). Before Regulation (EU) 2026/1744, the dates were 2 Aug 2026 and 2 Aug 2027.
- What is the maximum fine for breaching Article 10?
- Up to €15 million or 3% of total worldwide annual turnover for the preceding financial year, whichever is higher (Art. 99(4), point (a), through the provider obligations in Art. 16). For SMEs, including start-ups, the fine is capped at whichever of the two is lower (Art. 99(6)). Since 27 Jul 2026, the same lower cap applies to small mid-cap enterprises (Art. 99(6a)).
- Did the Digital Omnibus change Article 10?
- Yes. Regulation (EU) 2026/1744, in force since 27 Jul 2026, makes these changes. Article 10: paragraphs 1 and 6 replaced, paragraph 5 deleted. High-risk dates move to 2 Dec 2027 (Annex III) and 2 Aug 2028 (Annex I). The section "What changed" quotes the old and new text.
- Is there an AiExponent tool for Article 10?
- Partly. License Compliance Checker covers part of Article 10. It writes a OSS + model licence report (JSON).
Content verified 4 Oct 2026 · Not legal advice.