---
title: "Art. 10 AI Act: Data and data governance"
canonical: "https://dposchool.com/ai-act/article/10"
source: "https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02024R1689-20260727#art_10"
source_note: "Source: Regulation (EU) 2024/1689, OJ L, 2024/1689, 12.7.2024; articles and annexes from the consolidated text 02024R1689-20260727. Only the text published in the Official Journal is authentic. © European Union, https://eur-lex.europa.eu"
text_as_of: "2026-07-27"
language: "en"
publisher: "DPO School"
---

Art. 10 AI Act · Chapter III: HIGH-RISK AI SYSTEMS · Section 2: Requirements for high-risk AI systems

# Article 10 AI Act: Data and data governance

Consolidated text of 27 July 2026. Retrieved 30 October 2026.

## Official text

### Article 10(1)

**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.

### Article 10(2)

**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:

#### Article 10(2)(a)

**(a)** the relevant design choices;

#### Article 10(2)(b)

**(b)** data collection processes and the origin of data, and in the case of personal data, the original purpose of the data collection;

#### Article 10(2)(c)

**(c)** relevant data-preparation processing operations, such as annotation, labelling, cleaning, updating, enrichment and aggregation;

#### Article 10(2)(d)

**(d)** the formulation of assumptions, in particular with respect to the information that the data are supposed to measure and represent;

#### Article 10(2)(e)

**(e)** an assessment of the availability, quantity and suitability of the data sets that are needed;

#### Article 10(2)(f)

**(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;

#### Article 10(2)(g)

**(g)** appropriate measures to detect, prevent and mitigate possible biases identified according to point (f);

#### Article 10(2)(h)

**(h)** the identification of relevant data gaps or shortcomings that prevent compliance with this Regulation, and how those gaps and shortcomings can be addressed.

### Article 10(3)

**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.

### Article 10(4)

**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.

### Article 10(6)

**6.** For the development of high-risk AI systems not using techniques involving the training of AI models, paragraphs 2, 3 and 4 of this Article and Article 4a(1) shall apply only to the testing data sets.

## Source

Source: Regulation (EU) 2024/1689, OJ L, 2024/1689, 12.7.2024; articles and annexes from the consolidated text 02024R1689-20260727. Only the text published in the Official Journal is authentic. © European Union, https://eur-lex.europa.eu

[Article 10 on EUR-Lex](https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02024R1689-20260727#art_10)

Consolidated text of 27 July 2026. Retrieved 30 October 2026.

This is reference material, not legal advice.

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