Conformity Assessments for Industrial AI: Documentation That Passes

Under the EU AI Act, high-risk AI systems require a conformity assessment before being placed on the market or used in production. This process ensures your AI meets safety, transparency, and data-quality requirements — and it’s the most common audit failure point for industrial projects.

When You Need a Conformity Assessment

Any AI system that influences a product’s safety or regulatory compliance must undergo the procedure. This includes vision QA systems, robotic control algorithms, and predictive maintenance models tied to machinery safety.

Core Documentation Requirements

• System architecture and data flow diagrams.
• Training data sources, curation, and validation methods.
• Model versioning, explainability, and retraining policy.
• Risk management plan and mitigation measures.
• Human oversight definition and fallback procedures.
• Post-market monitoring and incident logging.

Who Performs the Assessment

For most high-risk industrial systems, a self-assessment is allowed if harmonized standards are applied (e.g., ISO/IEC 42001, 24029). For novel use cases, a Notified Body must verify compliance.

Best Practices to Pass on First Attempt

1. Reuse documentation from your ISO 9001 or 62443 quality systems.
2. Use AI lifecycle management tools for traceability (MLOps).
3. Include dataset bias testing and explainability metrics.
4. Conduct internal pre-audit before submission.

Case Example: Automotive Tier-1 Supplier

A supplier using AI for weld-defect detection passed conformity assessment by integrating AI model monitoring into its existing MES, allowing full traceability from training to deployment.

Related Articles

• EU AI Act for Manufacturing: Is Your Vision System ‘High-Risk’?
• AI Governance for Factories: Policies, Logs, and Human Oversight
• Timeline to Compliance: A Factory’s 12-Month Plan

Conclusion

Passing a conformity assessment requires discipline, not luck. With complete documentation and transparent governance, AI systems can demonstrate compliance efficiently — avoiding rework and production delays.