The highly anticipated mandatory national standard of China, “Identification Methods for Artificial Intelligence-Generated Content” (GB 45438-2025), has been officially announced and will take effect on September 1, 2025. The implementation of this regulation marks a critical step for China in the governance of AI content labeling.
The standard aims to establish a closed-loop management system covering “generation-distribution-accountability.” This means that every link in the chain—from AI model developers to content distribution platforms and end-users—has clear responsibilities and obligations. All AI-generated content must carry a verifiable “AI-generated” label. Non-compliance will result in severe consequences: platforms may be taken down, model filings may be rejected, and relevant individuals or enterprises will face legal risks. This mandatory requirement will fundamentally change the current chaotic landscape of AI-generated content.
I. Detailed Explanation of the New AI Content Labeling Regulations: “Explicit” and “Implicit” Labeling
The new standard specifies concrete and actionable requirements for AI content labeling, which can be summarized into two categories: “explicit” and “implicit” labeling.
1、Explicit Labeling: Making Content Instantly Recognizable for Users
The purpose of explicit labeling is to enable ordinary users to intuitively identify AI-generated content. This requires clear visual and auditory cues:
- Text Content: Articles must be clearly marked with “AI-generated” at the beginning or end, with a font size that cannot be easily overlooked.
- Images: A visible label such as “AI-generated” must be added to a conspicuous area of the image (e.g., a corner), with a font size no smaller than 5% of the shortest side of the image.
- Videos: A “AI-generated” prompt must appear for at least two seconds at the beginning of the video.
- Audio: A “AI-generated” voice prompt or a specific Morse code/audio watermark must be played at the beginning of the audio.
- Interactive Interfaces: AI chatbots or content generation pages must display a permanent “Powered by AI” prompt at the bottom, ensuring users are aware of the content’s origin throughout the interaction.
2、Implicit Labeling: Ensuring Permanent Traceability for Machines
Implicit labeling is more technical and aims to create a “digital DNA” for content, facilitating machine-based tracing and verification. The new regulation requires that JSON metadata be embedded within the files of all AI-generated content. This metadata includes the following core information:
- Generation Confirmation: Proof that the content was generated by AI.
- Service Provider Information: Records of the service provider that generated the content.
- Distribution Platform: Records of the platform where the content was first published.
- Unique Identification Number: A unique ID assigned to each piece of generated content.
- Digital Signature/Hash: Provides tamper-proof verification for the content.
It is worth noting that the metadata field names must include the term “AIGC” (Artificial Intelligence-Generated Content) to ensure standardized identification.
3、Responsibility Entities: Clearly Defined Roles and Responsibilities
The new regulation clearly defines two major responsibility entities in the AI content ecosystem:
- Generators: Including AI model developers and application providers offering AI-generated services. They are the source of content and must ensure that generated content carries standardized labels.
- Distributors: Refers to all platforms that allow users to publish and share AI-generated content. These platforms are obligated to review published content and ensure compliance with labeling requirements.
II. Benefits of the New AI Content Labeling Regulations: Reshaping the AI Ecosystem and Ushering in a Trust Dividend
The implementation of “AI Content Labeling” is not merely a technical burden but a reshaping of the entire industry ecosystem, bringing multiple positive impacts:
- User Benefits: Explicit labeling makes it easy for the general public to distinguish the authenticity of information, effectively preventing risks such as AI deepfake scams and fake news. This helps rebuild user trust in online content.
- Platform Advantages: The new regulation provides platforms with clear accountability boundaries. If issues arise, platforms can quickly trace the source of content through implicit labeling, ensuring clear accountability and avoiding widespread repercussions.
- Healthy Industry Development: In the past, the proliferation of low-quality and fake AI content squeezed out high-quality content. The implementation of the new regulation will end the era of “bad money driving out good,” allowing enterprises that comply with regulations and focus on content quality to gain traffic and trust dividends. This is a sign of the industry maturing.
- National Governance: From a macro perspective, this initiative will significantly improve the overall information environment, laying a solid foundation for the healthy and sustainable development of AI technology.
III. Action Checklist: Preparing for September 1st
As readers or practitioners in the AI industry, we must take immediate action to prepare for the formal implementation of the new regulation.
- Comprehensive Audit: Immediately review all aspects of your products or services involving AI-generated content.
- Technical Upgrades: Begin implementing technical upgrades for both front-end and back-end labeling. Ensure explicit labeling on the front-end and standardized implicit metadata embedding on the back-end.
- Process Updates: Revise user agreements, content review processes, and risk control rules to incorporate AI content labeling requirements into daily operations.
- Internal Testing and Launch: Complete all upgrades and conduct internal testing before September 1st to ensure a smooth transition and avoid business disruptions due to non-compliance.
Conclusion:
The implementation of the “AI Content Labeling” regulation is a bold innovation in China’s AI governance efforts. It is not just a compliance threshold but also a starting line for a new track in the AI industry. Those who can complete the compliance deployment of AI content labeling first will win the dual trust of users and regulators, seizing the high ground in future competition.
How do you think this new regulation will change the AI field you are in? Or what challenges might arise during its implementation?
