Data governance and quality: AI obligations

Practical requirements extracted from policy instruments, with the source article, the actors they bind, evidence examples and original framework mappings. Legal requirements are marked; everything else is voluntary guidance.

category: data_governance ×

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2 results

Legal requirement data governance European Union

Apply data governance and quality criteria to training, validation and testing data

EU AI Act · Article 10

High-risk AI systems that use data-driven techniques must be developed on training, validation and testing data sets meeting quality criteria: appropriate governance practices covering design choices, data collection and origin, preparation, assumptions, availability and suitability, examination for possible biases, and measures to detect, prevent and mitigate bias. Data must be relevant, sufficiently representative and, to the best extent possible, free of errors and complete for the intended purpose.

Source-linked Applies from 2 Aug 2026

Voluntary guidance data governance Singapore

Manage data quality, model development and monitoring across the lifecycle

Singapore Model AI Governance Framework · Second edition, Part on operations management

Covers data lineage and quality, minimising bias in datasets, model explainability, repeatability, robustness, regular tuning and active monitoring after deployment.

Source-linked