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The European Union has taken another significant step towards regulating artificial intelligence by publishing its long-awaited AI content labelling playbook ahead of key compliance deadlines under the EU AI Act.

Released by the European Commission on 10 June, the voluntary Code of Practice provides practical guidance for developers and deployers of generative AI systems on how to meet transparency obligations that become enforceable across the bloc from August 2, 2026. While participation in the Code remains optional, the legal requirements underpinning it are not.

The initiative reflects growing concern among policymakers about the potential misuse of AI-generated content, particularly deepfakes and synthetic media capable of influencing public opinion, political discourse and consumer decision-making. As AI tools become increasingly sophisticated and widely accessible, regulators are seeking ways to ensure citizens can distinguish between human-created and machine-generated content.

Strengthening transparency in the AI era

At the heart of the new framework is a simple principle: people should know when they are interacting with artificial intelligence or consuming content created or significantly altered by AI systems.

Under Article 50 of the EU AI Act, organisations will be required to clearly disclose when users are engaging with AI-powered systems such as virtual assistants, customer-service chatbots or automated support agents. In addition, certain categories of AI-generated content must carry visible labels indicating their artificial origin.

Particular attention is being paid to deepfakes and AI-generated content related to matters of public interest. These include synthetic images, audio recordings, videos and text that could influence public debate or shape public perceptions of important social, political or economic issues.

European policymakers argue that transparency is essential for maintaining public trust as AI technologies become increasingly integrated into everyday life.

According to the Commission, effective labelling can help reduce the risks of misinformation, manipulation and deception while allowing businesses to continue innovating responsibly.

Shared responsibilities across the AI ecosystem

The Code of Practice establishes a division of responsibilities between AI model developers and the organisations that deploy those models in real-world applications.

Developers of generative AI systems are encouraged to embed machine-readable markers into AI-generated outputs. These technical identifiers are intended to make synthetic content easier to detect and trace as it moves across digital platforms and communication channels.

Meanwhile, organisations deploying AI technologies bear responsibility for ensuring that users receive visible and understandable disclosures when required by law.

The framework recognises that AI-generated content often passes through multiple stages before reaching the public. As a result, transparency measures must be implemented throughout the AI supply chain rather than relying on a single point of control.

To support consistency across member states, the Commission is promoting the use of open technical standards alongside a common European visual icon that can be used to identify AI-generated material. This approach aims to provide a recognisable signal for users while reducing compliance complexity for businesses operating across multiple markets.

The guidance also acknowledges the role of human oversight. In the case of AI-generated text concerning matters of public interest, labelling requirements generally apply where content is published without meaningful human review or editorial intervention.

Industry faces a narrow implementation window

Although the Code is now open for signatures, businesses face a challenging timeline.

Companies serving European customers have less than two months to evaluate their AI systems, identify where transparency obligations apply and implement appropriate labelling mechanisms before enforcement begins.

For many organisations, compliance may involve reviewing existing workflows, updating customer-facing interfaces, integrating technical watermarking solutions and establishing governance processes to monitor AI-generated content.

The challenge is compounded by the fact that several important implementation details remain under development. The European Commission is expected to publish additional guidance clarifying aspects of the legislation and addressing areas not fully covered by the Code of Practice.

This leaves many businesses balancing regulatory preparation with a degree of uncertainty regarding how specific provisions will ultimately be interpreted and enforced.

Technology firms, media organisations, public institutions and digital platforms are among the sectors expected to be most directly affected by the new requirements.

A global model for AI governance?

The publication of the AI content labelling playbook f…