The AI Act's Hardest Requirement Is About Data, Not Algorithms
The EU Artificial Intelligence Act entered application for high-risk AI systems in August 2026. Most enterprise compliance teams are focused on the risk classification system, the conformity assessments, and the transparency obligations.
Fewer have grappled with what Article 10 actually requires.
Article 10 of the EU AI Act mandates that training, validation, and testing datasets for high-risk AI systems must be subject to 'appropriate data governance and management practices.' This includes relevance, representativeness, freedom from errors, and completeness - but the key requirement that most enterprises are underestimating is the obligation to have documented, auditable practices for data quality assurance.
In practice, this means being able to demonstrate - to a regulator - that your training data was accurate, unmodified, and appropriate at the time it was used. Not just at the time of a compliance audit. At the time the model was trained.
What 'High-Risk AI' Means for Your Data
The EU AI Act classifies AI systems as high-risk if they are used in sectors or applications listed in Annex III. These include:
- Critical infrastructure - energy, water, transport
- Education and vocational training - systems that determine access or outcomes
- Employment and HR - recruitment, performance evaluation, task allocation
- Essential private and public services - credit scoring, insurance risk assessment
