Why Data Sources Matter in AI Governance
AI systems learn from data. But not all data is created equal. Inaccurate, biased, incomplete, or improperly sourced data can lead to:
– Discriminatory algorithms
– Legal noncompliance (e.g. GDPR violations)
– Reputational damage
– Unsafe or misleading AI decisions
ISO/IEC 42001 recognises data as a foundational asset that must be governed through structured controls, from collection to processing to lifecycle management.
ISO/IEC 42001: Data Source Requirements
The standard requires organisations to establish processes to:
– Identify and document data sources
– Assess data quality and relevance
– Ensure lawful and ethical sourcing
– Monitor for bias and risk
– Maintain traceability and auditability
Data Governance in Practice
ISO/IEC 42001 doesn’t operate in a vacuum. It dovetails with other ISO standards like:
– ISO 27001 – for information security management
– ISO 27701 – for privacy information management
– ISO 9001 – for quality management and continual improvement
Together, these form an integrated management system approach where data responsibility is embedded into operations, not bolted on later.
For example, we’ve helped clients build data source registers that link datasets to risk assessments, consent logs, quality metrics, and version histories. This isn’t just for compliance — it’s for accountability and trust.
Challenges and Recommendations
Common data sourcing challenges include:
– Legacy datasets with unknown origins
– Third-party data lacking transparency
– Aggregated data obscuring individual rights
– Lack of internal ownership over datasets
Our advice at Thamer James Ltd:
1. Start with a data inventory – Know what data you have and where it came from.
2. Engage cross-functional teams – Legal, data science, compliance, and procurement all have a role.
3. Embed data due diligence into your AI lifecycle – Don’t treat data vetting as a one-off task.
4. Document everything – ISO/IEC 42001 expects traceability, and so will your stakeholders.
Final Thoughts
AI is only as ethical, accurate, and compliant as the data behind it. ISO/IEC 42001 offers a structured path for organisations to govern AI data sources in a transparent, risk-based way.
As with any ISO system, the standard doesn’t demand perfection — it demands accountability, consistency, and improvement. If your organisation is working with AI or preparing for ISO/IEC 42001 certification, now is the time to scrutinise your data sources.
For further information and to book your BS 1SO 42001 Artificial intelligence – management systems survey please contact: Marcus J Allen at Thamer James Ltd. Email: [email protected]
Marcus has twenty years’ experience in delivering Governance, Risk and Compliance solutions to over two hundred organisations within the UK. Marcus holds the respected Diploma in Governance, Risk and Compliance from the International Compliance Association and holds a master’s degree in Management Learning & Change from the University of Bristol. Marcus has attended various courses on AI development at Oxford University.