EU AI Act 训练数据合规：完整指南（2026）
企业需要了解的关于 EU AI Act 训练数据要求的一切——数据质量、偏差测试、文档要求和2026年8月截止日期。
EU AI Act 是自 GDPR 重塑数据隐私以来对 AI 训练数据最重要的法规。
EU AI Act 对训练数据的实际要求
高风险 AI 系统必须遵守第10条：数据质量标准、偏差检查、统计属性理解和文档化、涵盖收集/来源/准备/标注/质量保证的数据治理实践 。
你的数据管道需要什么
- 数据来源文档
- 质量指标和报告
- 偏差评估记录
- 标注方法文档
- 版本控制和审计追踪
大多数企业的不足之处
缺口通常不在数据质量本身——而在文档和可追溯性。追溯性文档化一个未记录的管道远比从一开始就构建文档要昂贵得多。
处罚
高风险要求违规最高1500万欧元或全 球年营业额的3%。
2026年8月截止日期不远了。审计你的训练数据管道的时间是现在——不是等执行信到达的时候。
Turn unstructured data into AI-ready datasets — without it leaving the building.
On-premise data preparation with full audit trail. No data egress. No fragmented toolchains. EU AI Act Article 30 compliance built in.
Keep reading
EU AI Act Data Governance Checklist for High-Risk AI Systems
An actionable checklist covering data quality, bias detection, documentation, audit trails, and monitoring obligations for high-risk AI systems under the EU AI Act.
GDPR + EU AI Act: Double Compliance for AI Training Data
How enterprises must navigate both GDPR and EU AI Act requirements simultaneously when preparing AI training data — covering data minimization, consent, and the tension between privacy and AI needs.
EU AI Act Article 10: What It Means for Your AI Training Data
EU AI Act Article 10 sets strict data governance requirements for high-risk AI systems. Here's what it means for enterprise teams preparing AI training data — and the August 2026 compliance deadline.