EU AI Act and the GPAI Code: A Practical 2026 Readiness Checklist for Product Teams
The GPAI Code of Practice turns AI Act obligations into product work: documentation, copyright policy, transparency, and risk governance.
The EU AI Act is moving AI governance from legal review into product operations. The General-Purpose AI Code of Practice gives model providers and downstream teams a concrete way to think about transparency, copyright, and safety obligations.
Why product teams should care
Even if your company is not training a foundation model, your application may depend on one. That makes vendor selection, data handling, logging, user disclosure, and human review part of the product architecture.
The practical checklist
- Record which AI models are used in each product flow.
- Keep model version, provider, purpose, and fallback behavior in configuration.
- Document whether user data is sent to an external model provider.
- Add human review for high-impact or irreversible actions.
- Keep prompt and output audit trails where appropriate.
- Prepare a copyright and data-use policy for AI-generated content.
- Make AI involvement visible to users when it affects their experience.
What the GPAI Code adds
The European Commission describes the code as a tool for AI Act obligations around safety, transparency, and copyright. Its Transparency and Copyright chapters are designed to help providers demonstrate compliance with Article 53 obligations, while Safety and Security applies to the most advanced systemic-risk models.
Engineering implication
The product team needs a small AI inventory. Without it, compliance becomes a manual archaeology project every time a model, prompt, or provider changes.
Sources
- European Commission, General-Purpose AI Code of Practice: https://digital-strategy.ec.europa.eu/en/policies/contents-code-gpai