EU AI Act
EU AI Act - High-Risk Operator Obligations

EU AI Act EUAI-Art.17: Quality management system

Providers must put in place a quality management system that ensures compliance with the Regulation, documented systematically in written policies, procedures and instructions, covering at least: a regulatory compliance strategy including conformity assessment and management of modifications; design, design control and design verification techniques; development, quality control and quality assurance techniques; examination, test and validation procedures before, during and after development and the frequency at which they run; technical specifications and standards to be applied and, where harmonised standards are not applied in full, the means used instead; data management systems and procedures spanning acquisition, collection, analysis, labelling, storage, filtration, mining, aggregation and retention; the Art.9 risk management system; the Art.72 post-market monitoring system; Art.73 serious incident reporting procedures; handling of communication with authorities, notified bodies, other operators and customers; record-keeping; resource management including security of supply; and an accountability framework setting out the responsibilities of management and staff for every one of those aspects. Implementation is proportionate to the size of the provider's organisation, but the degree of rigour required to make the systems compliant is not reducible.

Maintained by Gerard BlokdykVerified against the published standard Control text last updated

What else in your programme already covers this

This control maps to 52 controls across 9 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.

ISO/IEC 42001:2023 · 12 controls

  • A.2.2 AI policy
  • A.2.3 Alignment with other organizational policies
  • A.2.4 Review of the AI policy
  • A.3.2 AI roles and responsibilities
  • A.4.2 Resource documentation
  • A.4.3 Data resources
  • A.6.1.2 Objectives for responsible development of AI system
  • A.6.1.3 Processes for responsible design and development of AI systems
  • A.6.2.2 AI system requirements and specification
  • A.6.2.4 AI system verification and validation
  • A.7.2 Data for development and enhancement of AI system
  • A.7.6 Data preparation

ISO 27001:2022 · 9 controls

  • 5.1 Policies for information security
  • 5.2 Information security roles and responsibilities
  • 5.24 Information security incident management planning and preparation 
  • 5.31 Legal, statutory, regulatory and contractual requirements
  • 5.36 Compliance with policies, rules and standards for information security
  • 5.37 Documented operating procedures
  • 5.4 Management responsibilities
  • 8.25 Secure development life cycle
  • 8.32 Change management

NIST SP 800-53 Rev 5 · 9 controls

Cloud Security Alliance Cloud Controls Matrix (CCM) v4.0.1 · 6 controls

  • CCM-AIS-01 Application and Interface Security Policy and Procedures
  • CCM-AIS-04 Secure Application Design and Development
  • CCM-CCC-01 Change Management Policy and Procedures
  • CCM-GRC-01 Governance Program Policy and Procedures
  • CCM-GRC-06 Governance Responsibility Model
  • CCM-HRS-09 Personnel Roles and Responsibilities

SOC 2 · 6 controls

  • SOC2-CC1.3 CC1.3 Structures, reporting lines, authorities and responsibilities (COSO principle 3)
  • SOC2-CC1.5 CC1.5 Accountability for internal control responsibilities (COSO principle 5)
  • SOC2-CC2.2 CC2.2 Internal communication of objectives and control responsibilities (COSO principle 14)
  • SOC2-CC3.4 CC3.4 Identifying and assessing significant changes (COSO principle 9)
  • SOC2-CC4.1 CC4.1 Ongoing and separate evaluations of control (COSO principle 16)
  • SOC2-CC5.3 CC5.3 Deploying controls through policies and procedures (COSO principle 12)

NIST AI Risk Management Framework (AI RMF 1.0) · 4 controls

  • AIRMF-GV-1.2 The characteristics of trustworthy AI are integrated into organizational policies, processes, and procedures
  • AIRMF-GV-2.1 Roles and responsibilities and lines of communication related to mapping, measuring, and managing AI risks are documented and are clear to individuals and teams throughout the organization
  • AIRMF-MP-1.6 System requirements are elicited from and understood by relevant AI actors, and design decisions take socio-technical implications into account to address AI risks
  • AIRMF-MS-2.13 Effectiveness of the employed TEVV metrics and processes in the MEASURE function are evaluated and documented

NIS2 Directive · 3 controls

  • Art.20.1 Management body approves the cybersecurity risk-management measures and oversees their implementation
  • Art.21.2.a Policies on risk analysis and on information system security
  • Art.21.2.e Security in acquisition, development and maintenance, including vulnerability handling and disclosure

DORA · 2 controls

  • DORA-Art.24 General requirements for the performance of digital operational resilience testing
  • DORA-Art.6 ICT risk management framework

GDPR · 1 control

Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.

Other controls in EU AI Act - High-Risk Operator Obligations

You are reading one control. How much of EU AI Act have you already done?

EU AI Act EUAI-Art.17 is one control. If you already hold one of the frameworks below, a reviewed crosswalk already says how much of EU AI Act your existing evidence covers. Hold ISO/IEC 42001:2023 and 17 of 43 EU AI Act controls already carry evidence.

If you hold ISO/IEC 42001:202339.5% covered · 26 gapsIf you hold NIST AI Risk Management Framework (AI RMF 1.0)25.6% covered · 32 gaps

Each report names every control your existing framework evidences, every one it does not, the reasoning behind each claim, and the claims that were argued against and rejected. 0 were rejected on the ISO/IEC 42001:2023 pair alone.

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The graph holds this control, the 52 it maps to, and the evidence behind each claim, over MCP and REST.

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