Regulatory Context
The EU AI Act imposes binding AI governance obligations on providers and deployers of high-risk AI systems — covering risk management (Article 9), training data governance (Article 10), decision logging (Article 12), and post-market documentation (Article 19).
- •High-risk AI obligations apply from August 2026 — organizations building or deploying systems in covered categories must begin compliance now.
- •Article 12 requires automatic, tamper-evident logging throughout the operational lifetime of high-risk AI systems.
- •Article 10 requires training data to meet governance and quality standards with documented provenance — certified synthetic datasets satisfy this.
- •Decision logging, audit trails, and artifact provenance are the three governance mechanisms that directly map to Articles 12, 19, and 10 respectively.
Sub-Hub
EU AI Act — AI Governance
EU AI Act obligations through an AI governance lens: from Article 12 decision logging and Article 10 training data to compliance infrastructure.
EU AI Act as AI Governance
The EU AI Act is not just a compliance checklist — it is a codified AI governance framework. Its core obligations map directly onto the governance mechanisms that responsible AI organizations should already be building: risk management, training data provenance, decision logging, and post-deployment accountability.
Organizations that implement robust AI governance infrastructure — particularly decision logging, audit trails, and training data governance — will satisfy the EU AI Act's Article 12, 10, and 19 requirements as a direct consequence.
Cryptographic infrastructure is the connective tissue. CertifiedData.io provides SHA-256 hashing, Ed25519 artifact signing, and tamper-evident decision records that directly satisfy EU AI Act logging and provenance requirements while serving broader AI governance obligations.
Key Article Obligations
Four articles drive the majority of technical AI governance obligations for high-risk AI systems.
Article 9 — Risk Management
Mandatory risk management systems for high-risk AI: identification, estimation, evaluation, and mitigation.
Article 10 — Training Data Governance
Provenance, quality controls, and how certified synthetic datasets satisfy Article 10 requirements.
Article 12 — Decision Logging
Automatic logging obligations — log content, retention periods, and tamper-evident architecture.
Article 19 — Post-Market Documentation
Post-market monitoring, incident reporting, and documentation obligations.
Governance Mechanism → Article Mapping
Each AI governance mechanism satisfies one or more EU AI Act articles.
Tamper-evident, automatic logs of AI system decisions throughout operational lifetime.
Provenance documentation, quality controls, and bias evaluation for training datasets.
Technical file requirements — model cards, capability descriptions, and evaluation records.
Risk identification, estimation, evaluation, and mitigation — continuous monitoring required.
Full-lifecycle logs supporting post-market monitoring and incident reporting obligations.
Cryptographic fingerprinting and signing of datasets and model artifacts.
Compliance Resources
EU AI Act Compliance Guide
Risk classification, high-risk AI obligations, implementation timeline, and compliance strategy.
Compliance Checklist
Practical checklist for providers and deployers covering Articles 9, 10, 12, 14, and 19.
AI Compliance Infrastructure
Technical architecture for Articles 10, 12, and 19 — the three pillars every high-risk AI org must build.
AI Artifact Certification
Cryptographic certification of AI datasets and models for regulatory compliance.
AI Decision Logging Platform
Technical architecture for Article 12-compliant logging — cryptographic logs, retention, and audit access.
Synthetic Data Compliance
How certified synthetic datasets satisfy Article 10 training data requirements.