China regulates AI through a layered set of rules tied to what a service does, whom it serves, and how it distributes or generates content—not through one all-purpose AI law. For companies, the first questions are whether a product provides an AI service to the mainland public, whether it uses recommendation or deep-synthesis technology, whether it simulates ongoing emotional interaction, and whether it has public-opinion attributes or social-mobilization capacity. Those answers determine which content, data, labeling, assessment, and filing duties may apply.
China’s AI rules are a layered framework, not one approval for every model
The national instruments covered here regulate distinct activities and overlap. The main measures in force as of 13 October 2026 are the Algorithm Recommendation Provisions, effective 1 March 2022; the Deep Synthesis Provisions, effective 10 January 2023; the Generative AI Interim Measures, effective 15 August 2023; the AI-Generated Synthetic Content Labeling Measures, effective 1 September 2025; and the Anthropomorphic AI Interaction Services Interim Measures, effective 15 July 2026.
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They sit alongside general rules on cybersecurity, data security, personal information, intellectual property, and other applicable laws. Sector-specific activity can also bring additional requirements: the generative-AI measures preserve applicable special rules for areas such as news publishing, film and television production, and literary and artistic creation. The list above is therefore a map of central AI-specific instruments, not a complete compliance inventory or a substitute for reviewing the rules applicable to a particular product and market entry.
The policy framing in Article 3 of the Generative AI Interim Measures pairs development with security and innovation with governance under law. The following English rendering is a working translation of the official Chinese text, not an official English version: “The state adheres to the principle of giving equal weight to development and security, combining the promotion of innovation with governance according to law … and exercises inclusive, prudent, and classified and tiered regulation over generative AI services.”
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Start with the service, its audience, and its function
A company should classify the service users actually receive, not just the underlying model. The same model may sit behind an internal research tool, a public chatbot, a recommendation feed, or a synthetic-media editor. Those uses can raise different rules, and a product may fall into more than one category at once.
| Question | Why it matters | Relevant rule or consequence |
|---|---|---|
| Does the service provide generated content to the mainland public? | The generative-AI measures are directed at generative AI used to provide public services in mainland China. | Covered providers have duties concerning content security, data, personal information, user records, complaints, and unlawful outputs. |
| Does it recommend, rank, select, search, filter, or dispatch content or decisions? | Algorithm recommendation technology is defined broadly and is not limited to generative models. | Recommendation providers have disclosure, user-choice, safety-review, and content-management duties; a defined subset must file algorithms. |
| Does it generate or edit text, voice, music, faces, images, video, digital people, or virtual scenes? | These are among the technologies and content types addressed by the deep-synthesis provisions. | Registration and review, input/output controls, records, data and personal-information management, labeling, and conditional assessment or filing duties may apply. |
| Does it simulate a person for continuous emotional interaction? | The 2026 anthropomorphic-service measures distinguish ongoing emotional interaction from ordinary assistance. | Covered providers face dedicated safeguards, including clear AI identity, interaction-data protection, exit routes, and assessment and filing requirements. |
| Does the service have public-opinion attributes or social-mobilization capacity? | This is a significant procedural trigger in the algorithm, generative-AI, and deep-synthesis frameworks. | Security assessment and algorithm filing may be required; the trigger does not make filing universal for all AI models. |
“Public service” here concerns provision to the mainland public under the generative-AI measures. Those measures expressly exclude research and development, or application, that does not provide such a public service. That is a scope boundary for this instrument—not a blanket exemption from other Chinese law for internal tools, research, data use, or the company operating them.
What the generative-AI measures require of providers
The CAC and six other central agencies issued the Generative AI Interim Measures on 10 July 2023; they took effect on 15 August 2023. They cover services that use generative AI to provide the mainland public with generated text, images, audio, video, or similar content. They also state that foreign-invested generative-AI services must comply with foreign-investment laws and regulations and obtain any administrative license otherwise required. These provisions do not by themselves resolve whether a specific foreign company may enter a market or which sectoral permissions its service needs.
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- Use training data and foundation models from lawful sources, respect intellectual-property rights, and meet personal-information requirements, including consent or another lawful basis where required.
- Improve training-data quality and establish workable rules and checks for data annotation.
- Protect user inputs and usage records, avoid collecting unnecessary personal information, and handle requests to access, copy, correct, supplement, or delete personal information.
Manage outputs, users, and incidents
- Providers assume responsibilities as network-information content producers and must fulfill information-security duties. Where personal information is involved, they also have personal-information-handler responsibilities.
- Publish applicable information about users, settings, and uses of the service, and provide a safe, stable service.
- Respond to complaints and take action when illegal content is found. The measures also require relevant labeling under the deep-synthesis framework.
These are lifecycle obligations, not just launch paperwork: data sourcing, service design, user privacy, output handling, and complaint response all matter. A product review should identify who performs each function—model provider, application operator, or other service provider—rather than assume that use of a third-party model removes the downstream operator’s responsibilities.
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When algorithm filing and security assessment are triggered
Filing, security assessment, registration, and administrative licensing are distinct procedures. The rules do not say that every model or AI-enabled product must complete the same process. A central procedural trigger in the algorithm recommendation, generative-AI, and deep-synthesis rules is whether the service has public-opinion attributes or social-mobilization capacity.
Algorithm recommendation: broad technology coverage, conditional filing
The four-agency Algorithm Recommendation Provisions took effect on 1 March 2022. Their coverage includes generation and synthesis, personalized push, ranking and selection, search and filtering, and dispatch and decision algorithms. Providers must maintain algorithm-safety and review controls, manage unlawful content, disclose that they provide algorithmic recommendations and explain basic principles, purposes, and operating mechanisms. They must give users a way to opt out or choose non-personalized recommendations.
Providers whose services have public-opinion attributes or social-mobilization capacity must file through the algorithm filing system within ten working days after commencing the service, and update or cancel filings when required. The generative-AI and deep-synthesis provisions point back to this framework for services with that capacity. The ten-working-day rule is therefore not a universal deadline for every company releasing any AI model.
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The CAC, Ministry of Industry and Information Technology, and Ministry of Public Security issued the Deep Synthesis Provisions, effective 10 January 2023. They apply to internet information services using deep-synthesis technologies in China. In addition to generated or edited text and audio, they cover technologies involving faces, images, video, digital people, and virtual scenes.
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Providers must maintain user registration and review systems; examine inputs and outputs; keep relevant records; and manage training data and personal information. They must apply technical labels and, in specified cases, prominent labels. For face or voice biometric editing, users must be prompted to notify the person concerned and obtain separate consent as required by the rule.
Certain biometric or sensitive-scene models and tools require a security assessment. Services with public-opinion attributes or social-mobilization capacity have algorithm-filing obligations, and launching specified new products, applications, or functions also requires a security assessment. Companies should assess both the underlying technology and the service’s features: a media tool could trigger a category-specific assessment even when a different product would not.
What AI-generated content labeling means in practice
The four-agency AI-Generated Synthetic Content Labeling Measures were issued on 7 March 2025 and took effect on 1 September 2025. They apply to covered network-information service providers under the algorithm, deep-synthesis, and generative-AI provisions. The measures distinguish labels users can perceive from information embedded in the file.
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| Label type | What it is | What the measures address |
|---|---|---|
| Visible | A notice perceptible to users through text, sound, graphics, or an interaction interface. | Specified content types need notices in appropriate locations; exported files need to retain required visible marks where applicable. |
| Hidden | Information placed in file data, including metadata. | Generated-content files must contain identifying production information. Hidden-label information may include content attributes, provider name or code, and content number. |
Digital watermarking is encouraged as a form of hidden label, but it is not synonymous with every hidden label: the measures specifically address file metadata and separately encourage watermarking. Content-distribution services must inspect metadata and add notices in specified cases. App-distribution services must ask whether an app offers generation or synthesis and check relevant labeling materials. Users who post generated content must declare it and use the provider’s labeling function.
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For a company, that makes labeling a chain-of-custody issue as well as an interface issue. It should consider what its generator embeds, what survives export or transformation, what downstream distribution systems must inspect, and how users declare synthetic content when posting it. The precise mark depends on the content type and the applicable rule; the measures should not be reduced to a single universal watermark requirement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When an AI companion falls under the 2026 anthropomorphic-services rule
The CAC’s Anthropomorphic AI Interaction Services Interim Measures took effect on 15 July 2026. They cover services provided to the mainland public that simulate human personality traits, thought patterns, and communication style for continuous emotional interaction, including companionship, emotional care, and support through text, image, audio, or video.
Ordinary customer service, factual question-and-answer, work assistance, education, and scientific research are outside this measure when they do not involve continuous emotional interaction. A conversational interface alone does not establish that a service is covered; the nature and continuity of the interaction matter.
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Covered providers must manage safety through deployment, operation, upgrades, and termination; protect interaction data; make clear that the user is interacting with AI; provide an exit route; and address overreliance, emotional dependence, and risks to minors. The measures bar virtual family-member or partner services for minors and set guardian-consent and minor-mode requirements in specified cases.
Assessment thresholds and ongoing formalities
A safety assessment is required in circumstances including launch or addition of a related function, a material service change resulting from new technology or application, reaching 1 million or more registered users, reaching 100,000 or more monthly active users, specified safety risks, or another situation designated by regulators. These figures are legal triggers under the 2026 measure, not estimates of how many users a service has. Covered providers also have algorithm filing and annual verification requirements.
What the CAC’s 2026 filing figures do—and do not—tell companies
In an announcement published on 14 September 2026, the CAC reported 1,112 generative-AI services filed and 731 AI applications or functions registered by 31 August 2026. The announcement said 124 services and 133 applications or functions were added during July and August. It also said launched applications or functions should display the filed or registered service they use, including the model name and filing or launch number.
Those are CAC-reported totals for filings and registrations, not a count of all AI products, all companies using AI, or all products subject to one identical process. The distinction matters: a model service filing, registration of an application or function, a security assessment, and an administrative license are not interchangeable labels for a single approval.
A practical compliance triage for a product team
- Map the deployment. Record whether users are in mainland China, whether the service is available to the public, and whether the use is research, internal application, or a product delivered to users. Treat the generative-AI scope exclusion as limited to that measure, not as a general exemption.
- Describe what the feature does. Identify content generation, recommendation or ranking, synthetic-media creation or editing, and continuous emotional interaction separately. A single service can combine these functions.
- Identify the parties in the content path. Distinguish the model provider, application operator, content-distribution service, and app distributor. Check which entity controls data, user disclosures, output moderation, labels, and complaint handling.
- Test the specific procedural triggers. Assess public-opinion attributes or social-mobilization capacity; relevant deep-synthesis biometric or sensitive-scene functions; new or specified launches; and, for anthropomorphic services, the listed changes, user thresholds, and safety-risk conditions.
- Keep procedures distinct. Determine separately whether algorithm filing, an application or function registration, a security assessment, or an administrative license applies. Do not infer one from another.
- Review the full legal context. Check cybersecurity, data-security, personal-information, intellectual-property, foreign-investment, sector, and other applicable obligations for the specific facts. The central AI measures do not settle every local implementation or sector question.
What companies should take away
China’s framework is best understood as function-based and cumulative. A public generative service has provider duties even without a filing trigger; recommendation systems can be regulated without being generative; synthetic-media tools bring deep-synthesis controls and labeling; and sustained emotional companionship can activate a dedicated rule. Public-opinion or social-mobilization capacity changes the procedural analysis, while specific technology, launch events, scale, and sector context can create additional requirements.
For product and legal teams, the useful unit of analysis is the deployed service and its user-facing functions—not the model label in isolation. Classify the audience and function first, then map provider and distribution roles, content and data controls, labels, assessment triggers, filings, and any separate licensing or sector rules. This avoids both errors that a single “AI approval” framing invites: assuming every model needs the same filing, and assuming a product outside one measure’s scope has no other obligations.
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