Quick answer

AI data governance covers: data quality standards, consent management, retention periods, cross-border transfer rules, and data subject rights. Align with GDPR and sector regulations.

Updated June 2026 · MmowW AI Compliance

AI Data Governance Policy: What to Include

The Short Answer

AI data governance covers: data quality standards, consent management, retention periods, cross-border transfer rules, and data subject rights. Align with GDPR and sector regulations.

This guidance applies to organisations of all sizes using AI tools in a professional context.

What You Need to Know

Understanding the regulatory landscape is the first step. The EU AI Act, GDPR, and sector-specific regulations create a framework of obligations that vary based on how you use AI and what decisions it influences.

Most businesses using off-the-shelf AI tools face manageable compliance requirements. The key is documentation: record what AI tools you use, how you use them, and what safeguards you have in place.

Practical Steps

1. Review your current AI use against the requirements discussed above.

2. Document your findings and any gaps identified.

3. Implement necessary safeguards (human oversight, data protection, transparency).

4. Train relevant staff on AI capabilities, limitations, and compliance requirements.

5. Establish regular review cycles to maintain compliance as regulations evolve.

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This article is for informational purposes only and does not constitute legal advice. Regulatory requirements change frequently — verify current rules with official sources. Built by Sawai Gyoseishoshi Office, Hiroshima, Japan.