ISO 42001 A.7.3: Data Provenance for AI Systems
Data provenance is the foundation of trustworthy AI systems. ISO 42001 A.7.3 requires you to document and maintain detailed records of where your training data comes from, how it was collected, what processing it underwent, and whether proper consent was obtained. Without clear provenance records, you cannot demonstrate responsible AI governance or meet regulatory audit requirements.
What this means
This control mandates that your organization create and maintain comprehensive documentation tracking the complete lifecycle of datasets used in AI systems. You must record the original source of each dataset, the methods used to collect it, every processing or transformation step applied, and the consent status of all training data. These records must be preserved for the entire operational lifetime of each AI system, enabling you to trace any data back to its origin and justify its use in your AI models.
How to comply
- 1.Establish a data inventory that captures source origin, collection methodology, and consent documentation for all training datasets before deployment
- 2.Document the complete processing pipeline, including cleaning steps, feature engineering, sampling, and augmentation applied to raw data
- 3.Obtain and retain written consent records from data subjects where required by applicable regulations (GDPR, CCPA, etc.)
- 4.Define and implement retention policies that align with the operational lifetime of each AI system
- 5.Create audit trails that link processed datasets back to their original sources for traceability
- 6.Schedule regular reviews of provenance records to ensure completeness and accuracy as systems evolve
Evidence auditors look for
- Data provenance ledger showing source URL, collection date, collection method (API, manual, third-party), and data owner for each dataset
- Data processing documentation detailing transformation steps, algorithms applied, and quality checks performed pre-deployment
- Consent management records including signed agreements, opt-in confirmations, or legal basis justifications for data use
- Dataset versioning logs mapping each AI system version to specific training data versions with full lineage
- Third-party data agreements showing licensing terms, usage rights, and compliance certifications from vendors
- Retention schedule matrix defining how long provenance records will be kept based on system lifecycle and regulatory requirements
Frequently asked questions
When will FAQs be available?
The FAQ for this control is currently being prepared.
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