Glossary

AI Supervisory Authorities

What is AI Supervisory Authorities?

AI supervisory authorities are public bodies that monitor compliance with AI rules. At EU level, the European Commission's AI Office coordinates implementation of the AI Act and supervises general-purpose AI models. In Germany, the implementing act KI-MIG (in force since 29 July 2026) makes the Federal Network Agency (Bundesnetzagentur) the central market surveillance authority, while sector regulators such as BaFin remain responsible. Under the Digital Omnibus, high-risk obligations apply only from December 2027 or August 2028 (as of October 2026; not legal advice).

Topics

Regulation
EU AI Act
Supervision
Compliance

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Related terms

AI Regulatory Framework

An AI regulatory framework comprises the laws, standards and oversight structures governing how AI is developed and used. In the EU, the central law is the AI Act (Regulation (EU) 2024/1689), which takes a risk-based approach: prohibitions have applied since February 2025, obligations for general-purpose AI models since August 2025 and transparency duties since August 2026. Following the “Digital Omnibus” (Regulation (EU) 2026/1744), high-risk obligations apply from 2 December 2027 or 2 August 2028 (as of October 2026; not legal advice).

Regulation
EU AI Act
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AI Certification Processes

AI certification processes are procedures in which an independent body checks whether an organisation or an AI system meets defined requirements. A widely used example is certification to ISO/IEC 42001 (published 2023), which describes a management system for responsible AI use; requirements for the certifying bodies are set out in ISO/IEC 42006 (2025). Such a certificate is voluntary and does not replace the conformity assessment the EU AI Act requires for high-risk systems (as of October 2026).

Certification
ISO/IEC 42001
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Data protection regulations

Data protection regulations are legal rules governing the handling of personal data. In the EU the General Data Protection Regulation (GDPR) is the key framework; among other things it requires a legal basis for every processing activity, data minimisation, transparency towards data subjects and data processing agreements with service providers. When using AI, organisations need to clarify which data ends up in inputs, knowledge sources and logs, and where it is processed.

GDPR
data protection
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Data governance

Data governance comprises the rules, roles and processes by which an organisation determines who may collect, use, change and delete which data. It covers responsibility for data quality, access rights, retention periods and compliance with data protection requirements. It matters especially for AI projects, because models and agents are only as reliable as the data they draw on.

data management
compliance
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