Chapter III · Section 3 · Obligations of providers and deployers of high-risk AI systems and other parties
Article 17 — Quality management system
▼ Primary text, verbatim. Our annotations appear below, visibly separated.
1. Providers of high-risk AI systems shall put a quality management system in place that ensures compliance with this Regulation. That system shall be documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and shall include at least the following aspects:
(a) a strategy for regulatory compliance, including compliance with conformity assessment procedures and procedures for the management of modifications to the high-risk AI system;
(b) techniques, procedures and systematic actions to be used for the design, design control and design verification of the high-risk AI system;
(c) techniques, procedures and systematic actions to be used for the development, quality control and quality assurance of the high-risk AI system;
(d) examination, test and validation procedures to be carried out before, during and after the development of the high-risk AI system, and the frequency with which they have to be carried out;
(e) technical specifications, including standards, to be applied and, where the relevant harmonised standards are not applied in full or do not cover all of the relevant requirements set out in Section 2, the means to be used to ensure that the high-risk AI system complies with those requirements;
(f) systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data that is performed before and for the purpose of the placing on the market or the putting into service of high-risk AI systems;
(g) the risk management system referred to in Article 9;
(h) the setting-up, implementation and maintenance of a post-market monitoring system, in accordance with Article 72;
(i) procedures related to the reporting of a serious incident in accordance with Article 73;
(j) the handling of communication with national competent authorities, other relevant authorities, including those providing or supporting the access to data, notified bodies, other operators, customers or other interested parties;
(k) systems and procedures for record-keeping of all relevant documentation and information;
(l) resource management, including security-of-supply related measures;
(m) an accountability framework setting out the responsibilities of the management and other staff with regard to all the aspects listed in this paragraph.
2. The implementation of the aspects referred to in paragraph 1 shall be proportionate to the size of the provider’s organisation, in particular, if the provider is an SME, including a start-up, or an SMC. Providers shall, in any event, respect the degree of rigour and the level of protection required to ensure the compliance of their high-risk AI systems with this Regulation.
3. Providers of high-risk AI systems that are subject to obligations regarding quality management systems or an equivalent function under relevant sectoral Union law may include the aspects listed in paragraph 1 as part of the quality management systems pursuant to that law.
4. For providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services law, the obligation to put in place a quality management system, with the exception of paragraph 1, points (g), (h) and (i) of this Article, shall be deemed to be fulfilled by complying with the rules on internal governance arrangements or processes pursuant to the relevant Union financial services law. To that end, any harmonised standards referred to in Article 40 shall be taken into account.
This text is meant purely as a documentation tool and has no legal effect. The Union's institutions do not assume any liability for its contents. The authentic versions of the relevant acts, including their preambles, are those published in the Official Journal of the European Union and available in EUR-Lex.
Passages marked with the accent edge in the primary text were inserted or replaced by the amendment.
Show the text as adopted, before the amendment
The authentic 2024 text of this provision, shown for comparison. It no longer states the law.
1. Providers of high-risk AI systems shall put a quality management system in place that ensures compliance with this Regulation. That system shall be documented in a systematic and orderly manner in the form of written policies, procedures and instructions, and shall include at least the following aspects:
(a) a strategy for regulatory compliance, including compliance with conformity assessment procedures and procedures for the management of modifications to the high-risk AI system;
(b) techniques, procedures and systematic actions to be used for the design, design control and design verification of the high-risk AI system;
(c) techniques, procedures and systematic actions to be used for the development, quality control and quality assurance of the high-risk AI system;
(d) examination, test and validation procedures to be carried out before, during and after the development of the high-risk AI system, and the frequency with which they have to be carried out;
(e) technical specifications, including standards, to be applied and, where the relevant harmonised standards are not applied in full or do not cover all of the relevant requirements set out in Section 2, the means to be used to ensure that the high-risk AI system complies with those requirements;
(f) systems and procedures for data management, including data acquisition, data collection, data analysis, data labelling, data storage, data filtration, data mining, data aggregation, data retention and any other operation regarding the data that is performed before and for the purpose of the placing on the market or the putting into service of high-risk AI systems;
(g) the risk management system referred to in Article 9;
(h) the setting-up, implementation and maintenance of a post-market monitoring system, in accordance with Article 72;
(i) procedures related to the reporting of a serious incident in accordance with Article 73;
(j) the handling of communication with national competent authorities, other relevant authorities, including those providing or supporting the access to data, notified bodies, other operators, customers or other interested parties;
(k) systems and procedures for record-keeping of all relevant documentation and information;
(l) resource management, including security-of-supply related measures;
(m) an accountability framework setting out the responsibilities of the management and other staff with regard to all the aspects listed in this paragraph.
2. The implementation of the aspects referred to in paragraph 1 shall be proportionate to the size of the provider’s organisation. Providers shall, in any event, respect the degree of rigour and the level of protection required to ensure the compliance of their high-risk AI systems with this Regulation.
3. Providers of high-risk AI systems that are subject to obligations regarding quality management systems or an equivalent function under relevant sectoral Union law may include the aspects listed in paragraph 1 as part of the quality management systems pursuant to that law.
4. For providers that are financial institutions subject to requirements regarding their internal governance, arrangements or processes under Union financial services law, the obligation to put in place a quality management system, with the exception of paragraph 1, points (g), (h) and (i) of this Article, shall be deemed to be fulfilled by complying with the rules on internal governance arrangements or processes pursuant to the relevant Union financial services law. To that end, any harmonised standards referred to in Article 40 shall be taken into account.
Recital 81 — interpretive context
The provider should establish a sound quality management system, ensure the accomplishment of the required conformity assessment procedure, draw up the relevant documentation and establish a robust post-market monitoring system. Providers of high-risk AI systems that are subject to obligations regarding quality management systems under relevant sectoral Union law should have the possibility to include the elements…
Recital 146 — interpretive context
Moreover, in light of the very small size of some operators and in order to ensure proportionality regarding costs of innovation, it is appropriate to allow microenterprises to fulfil one of the most costly obligations, namely to establish a quality management system, in a simplified manner which would reduce the administrative burden and the costs for those enterprises without affecting the level of protection and…
What this means for you
In your terms · Quality management system
The quality management system reaches into how you build. Article 17(1)(b) and (c) name design control, design verification and the testing procedures by name: if the written system is not how the team actually works, it is a document that will not survive being checked.
- Design control and verification procedures
- Test and validation records
In your terms · Quality management system
Your runbooks and change-management practice will be exhibits in it.
In your terms · Quality management system
The quality management system governs how a change reaches production, modifications to an already assessed system included. It sets the pace at which you can ship.
In your terms · Quality management system
The QMS is where the other obligations get operationalized as written policies and procedures with named owners.
- Documented QMS with named owners
Failure smells likeCompliance lives in the heads of three people, and how a change reaches production depends on which of them you ask.
Obligations derived from this article
If you would rather not read the law
The basics page explains the Regulation's own categories in order: scope, role, tier, date. The engineering view groups the obligations by the platform capability they demand.