Technical and organizational measures — often abbreviated as TOMs — are among the most cited concepts in data protection law. At the same time, they are frequently misunderstood.
In many organizations, TOM documentation either consists of generic legal language or highly technical descriptions that few outside the IT department can interpret. Neither approach fulfills the real purpose.
TOMs should clearly explain how data is protected — practically, transparently and in alignment with actual system architecture.
Between Templates and Technical Overload
Effective TOM documentation avoids both extremes. It does not rely solely on generic statements such as “state-of-the-art security measures,” nor does it overwhelm readers with technical jargon.
Instead, it explains how confidentiality, integrity and availability of data are safeguarded.
Technical Safeguards Explained Clearly
Typical technical measures include:
- Access control mechanisms
- Encryption during storage and transmission
- Logging and monitoring
- Backup and recovery strategies
- Network protection
Clear documentation focuses on purpose and effect rather than cryptographic detail.
Organizational Controls Matter
Organizational measures often determine whether technical safeguards are effective.
These include role-based permissions, documented approval workflows, training programs, deletion concepts and incident response procedures.
AI systems introduce additional considerations such as model oversight, monitoring and accountability mechanisms.
AI-Specific Considerations
With AI deployment, documentation should address:
- Model monitoring
- Decision traceability
- Human oversight mechanisms
- Data source transparency
Such elements complement traditional data protection safeguards.
From Static Document to Living Governance
TOMs should evolve alongside system architecture. Version control and regular reviews ensure that documentation reflects operational reality.
Tools like Fendriova help align technical measures with real software stacks, transforming static templates into structured, context-aware compliance documentation.
Conclusion
Clear and understandable TOMs strengthen governance, build trust and support sustainable AI adoption.
Effective documentation connects technical safeguards with organizational processes — making compliance both transparent and practical.
