The management requirements part of ISO/IEC 5259 — specifying what an organisation needs to put in place to systematically manage data quality for AI.
The management requirements part of ISO/IEC 5259 — specifying what an organisation needs to put in place to systematically manage data quality for AI.
ISO/IEC 5259-3 draws on the PDCA quality management cycle and ISO 9001 principles to specify how organisations should establish and operate a DQMS. Key requirements include: data quality policy, roles and responsibilities, data quality planning and objectives, quality monitoring and measurement, corrective action processes, and management review. The standard applies to organisations developing or operating AI systems where data quality affects system performance, safety, or trustworthiness — directly supporting EU AI Act data governance requirements for high-risk systems.
Organisations implementing ISO/IEC 42001 should integrate DQMS requirements from Part 3 into their AI management system — creating a unified management framework for AI and data quality governance.
Like the quality management requirements in ISO 9001 applied to data: establishing the management cycle, accountability, and continuous improvement processes for data quality.
The management requirements part of ISO/IEC 5259 — specifying what an organisation needs to put in place to systematically manage data quality for AI.
ISO/IEC 5259-3 draws on the PDCA quality management cycle and ISO 9001 principles to specify how organisations should establish and operate a DQMS. Key requirements include: data quality policy, roles and responsibilities, data quality planning and objectives, quality monitoring and measurement, corrective action processes, and management review. The standard applies to organisations developing or operating AI systems where data quality affects system performance, safety, or trustworthiness — directly supporting EU AI Act data governance requirements for high-risk systems.
Organisations implementing ISO/IEC 42001 should integrate DQMS requirements from Part 3 into their AI management system — creating a unified management framework for AI and data quality governance.