文章总结： Foreign-investedenterprisesinChinausingoverseasAIsolutionsfacecomplexregulatoryrisksdespitetechnicalsetupslikededicatedlines.ThisarticleclarifiesthatinternalusedoesnotexemptcompliancewithChineselawsregardinggenerativeAI,cybersecurity,andcross-borderdatatransfers.ItemphasizesthatFIEsretainliabilityforcontentdistributionandmustproperlylabelAI-generatedmaterialstoavoidpublicconfusion.Companiesmustrigorouslyassesstheirspecificdeploymentmodelstodetermineobligationsunderinformationsecurityandpersonalprotectionlaws,ensuringstrictadherencetodataprotocolstomitigatepotentiallegalpenalties.
综合评分： 89
文章分类： AI安全,政策法规,数据安全,网络安全
Key Legal Issues of FIE in China Using Overseas HQ AI Solution
原创
Eva Zhang
网数与人工智能法律实务
2025年12月29日 08:00
上海
As multinational corporations accelerate their global digital transformation, many foreign-invested enterprises (FIEs) in China have begun adopting AI solutions centrally deployed by their overseas HQs—ranging from large language models (LLMs) and AI agents to applications with embedded AI capabilities—to support R&D, business decision-making, customer service, and digital content generation. This approach ensures operational consistency, integrated system management, and cost efficiency across global operations.
However, as China’s regulatory framework governing cybersecurity, data compliance, personal information protection, and AI governance continues to mature, this “global one-size-fits-all” deployment model is increasingly caught in a sharp tension between “HQs-driven technological enablement” and the hard boundaries of local regulatory requirements.
In this article, the team at Huiye Law Firm led by Ramon Huang addresses the most pressing compliance concerns for FIEs, analyzing key legal issues—from the regulatory implications of dedicated network connections and the definition of “internal use”, to content output compliance—when leveraging overseas AI systems in China. The following insights are for reference purposes only.
1. Common Technical Implementation Paths
Depending on the degree of localization, FIEs in China typically access their HQs’ AI solutions through one of several technical architectures:
It should be noted that the AI deployment models used by overseas HQs vary significantly. Some adopt private deployments (which may integrate multiple LLMs such as GPT, Gemini, or Claude), while others rely on SaaS-like solutions (e.g., Microsoft Copilot—an application-layer agent powered by underlying LLMs like GPT).
2.Legal Implications of Accessing Overseas AI via Dedicated Lines
2.1Does a Dedicated Line Exempt You from Chinese Law?
Compared to public internet access, dedicated lines offer enhanced privacy, security, and stability at the network transmission layer—but they do not confer any legal immunity from Chinese jurisdiction. Regulatory practice does not hinge on whether traffic flows over the public internet; instead, it focuses on whether the service is actually delivered within China and whether it produces legal effects on entities within Chinese territory.
2.2Does Granting Access to an FIE Constitute “Providing Services to the Public” Under Chinese Law?
Within complex multinational structures, the overseas entity operating the AI system (e.g., the parent company or its tech subsidiary) is often legally distinct from the China-based FIE—sometimes lacking direct equity control or even belonging to different business units or regions. Legally and regulatorily, they are separate entities operating under divergent legal regimes. In SaaS-style deployments within multinational structures (e.g., Copilot), the AI provider itself is typically a third-party vendor.
Therefore, whether such arrangements constitute “providing services to the public” under Chinese law must be assessed case-by-case, taking into account deployment architecture, corporate structure, applicable jurisdictions, and actual usage patterns (discussed further below).
3.Key Legal Issues When FIEsin China Use Overseas Parent Company’s AI Exclusively for Internal Employee Purposes
Many assume that if an FIE uses an overseas group’s AI system exclusively for internal employee purposes, it falls outside the scope of China’sInterim Measures for the Management of Generative Artificial Intelligence Services—since the regulation applies only when “generative AI services are offered to the public within China.” However, this interpretation is overly simplistic and potentially misleading.
First, the term “public” under Chinese law is not limited to individual consumers (to-c)—it also encompasses to-business scenarios. This is precisely why major overseas platforms like Gemini, ChatGPT, and Copilot generally do not sell directly to Chinese enterprises. As discussed earlier, the complex corporate structures of multinational groups make it difficult to categorically classify such usage as purely “internal”—especially since “internal use” is not a defined legal concept under Chinese law. After all, FIEs in China and their overseas parent groups are legally distinct entities; if something goes wrong at the HQs level, the China-based entity cannot simply disclaim all responsibility—at least not in the eyes of Chinese regulators. Moreover, some FIEs in China configure their office systems (including AI-enabled components) to be accessible not only to employees but also to external parties such as suppliers, distributors, and franchisees. In such cases, it becomes even harder to credibly argue that the AI system is used “exclusively for internal purposes.”
Second, even if theInterim Measures for the Management of Generative Artificial Intelligence Services do not apply (and which specific compliance obligations may be exempt should be assessed by legal professionals based on the actual business scenario), the overseas AI system may still be deemed as providing information services within China—for example, if it is exclusively targeted at the Chinese market or supports local transactions in China. In such cases, the enterprise remains subject to other applicable Chinese laws and regulations, including but not limited to: the Cybersecurity Law (e.g., content moderation, cryptographic compliance), the Personal Information Protection Law (e.g., consent requirements, cross-border data transfer rules), etc.
One might ask:What’s the difference between using an overseas AI system internally versus using overseas email or cloud storage?From a telecommunications licensing perspective, there is no fundamental legal distinction—both lack the necessary Chinese business permits. However, AI introduces qualitatively higher information security risks due to its autonomy, unpredictability, weak controllability, and limited explainability. This explains why services like Gmail remain accessible to Chinese IP addresses, while AI platforms like Gemini are not—and why doesn’t Gemini launch a China-specific version like Teams did?—because it also involves issues such as export controls on artificial intelligence.
Finally, many wonder: if the overseas HQs’ AI solution violates Chinese laws—such as by generating politically sensitive content—could the FIE in China still be held legally liable? The answer depends on the technical implementation model outlined in Part 1. Specifically, under Modes 2, 3, and 4, there is a local landing page or interface physically hosted within China, establishing a clear domestic nexus. As the local entity operating this China-based access point, the FIE would find it extremely difficult to completely disclaim legal responsibility—especially if the violation triggers a public incident (e.g., the overseas HQs’ website mislabeling regions on a map, as seen in past cases).
Finally, even when acting solely as an end user, the FIE in China must still comply with relevant regulations, including: theProvisions on Ecological Governance of Online Information Content, the Administrative Provisions on Deep Synthesis in Internet Information Services, and the Measures for Marking AI-Generated Content. Risks related to cross-border data transfers are discussed in Part 5.
4. Key Legal Issues When Internal Employees Use AI from Overseas Parent Groups to Generate and Publicly Distribute Synthetic Content
When employees of FIEs in China use text, images, videos, or other materials generated by AI systems operated by their overseas HQs—and subsequently publish such content on social media platforms, e-commerce sites, corporate websites, mobile apps, or other public channels—one of the regulators’ primary compliance concerns is whether the content is properly labeled as AI-generated.
The Measures for Marking AI-Generated Content are grounded not only in the Interim Measures for the Management of Generative Artificial Intelligence Services, but also in the Administrative Provisions on Algorithmic Recommendation in Internet Information Services and the Administrative Provisions on Deep Synthesis in Internet Information Services. Accordingly, from a legal standpoint, what matters is not whether the AI system is provided by an overseas parent company or whether content generation occurs outside China. Rather, the key considerations are whether the publicly disseminated material constitutes “synthetically generated content” and whether it could potentially mislead or cause confusion among the public.
Moreover, under theMeasures for Marking AI-Generated Content, the obligation to label such content applies to at least three categories of parties: (1) internet information service providers, (2) internet information content dissemination service providers, and (3) end users. As analyzed in Part 1, depending on the technical deployment model used, the legal statuses of the FIEs in China—where internal employees use AI-generated content from their overseas parent groups for public release—are summarized in the table below：
In certain e-commerce or advertising scenarios, when AI is used to generate or enhance product-related images or videos, it is recommended to consider the following factors to assess whether such content “may mislead or cause confusion among the public”—and thus determine whether an explicit disclosure label is required:
(1) Whether the core subject—such as the product, person, or scene—was synthetically generated by AI;
(2) Whether the AI-processed images or videos have altered fundamental attributes of the original product, including its shape, material, color, size, functionality, or other essential characteristics, thereby affecting consumers’ right to be informed and their freedom of choice;
(3) Whether the AI-generated content includes human faces, voices, or other biometric features;
(4) Whether the AI-generated content touches upon socially sensitive topics, such as current events, emergencies, or issues related to politics or history; etc.
5.Key Legal Risks of Using Overseas Parent Group’s AI to Provide Services to the Public Within China
Based on the analysis in Part I, depending on the technical approach, when using an overseas parent group’s AI to provide services to the public within China, the legal roles of the algorithm/large model service provider under Chinese law and the corresponding filing and compliance obligations differ, as detailed below:
In Modes 1 and 2, although the overseas group (including the AI provider) may not be required to file or register its algorithm or large model in China, any information security incident involving violations of laws such as the Cybersecurity Law could result in the blocking of the relevant application or service, thereby disrupting the continuity of its China operations. Moreover, these two modes may also be viewed as the overseas entity directly conducting business activities within China, potentially triggering legal risks related to market access and licensing requirements. In Modes 3 and 4, there is an additional risk that the relevant applications may be rejected by app stores or distribution platforms due to compliance gaps.
Furthermore, depending on the technical implementation approaches outlined in Part I, the potential cross-border data transfers involved when using an overseas parent group’s AI to serve the public within China are detailed below:
In Modes 1 and 2, personal information originating from within China is processed directly overseas. Under China’sPersonal Information Protection Law and related regulatory guidance, this still triggers China’s cross-border data transfer compliance obligations. Regarding whether user data is used for algorithm/model training: for enterprise versions of mainstream large language models (LLMs), this functionality is disabled by default; for consumer (individual-user) versions, users typically need to manually opt out if they wish to prevent their data from being used for training. As for LLM/Agent memory, implementations vary significantly across different AI solutions.
Moreover, unless the user explicitly consents to the use of their data for algorithm or model training, conversation history data (including prompts and generated outputs) is generally stored in a structured format at the application layer, not the model layer. Even when such data is later used for model training, the trained model parameters and internal memory do not retain or directly store the original conversation history. However, the application layer may temporarily access or review users’ conversation history for purposes such as risk control, abuse prevention, and audit compliance.
In most multinational corporations, the AI solutions deployed by their overseas HQs typically consist of a commercially licensed large language model (provided by LLM vendors) at the model layer, and an application layer developed and deployed either in-house by the HQs or through third-party vendors. Naturally, data storage and processing for both layers often rely on cloud environments provided by cloud service providers.
For additional dimensions of legal risk assessment, please refer to:
Huiye Insights | Key Security Risks and Compliance Self-Assessment Checklist for Enterprises Deploying AI Agents
汇业研究 | 企业上线AI Agent的主要安全风险与合规自评估清单
作者往期文章推荐：
企业上线AI Agent的主要安全风险与合规自评估清单
几款主流 2C 的 AIGC 类 APP 的合规实践调研（摘要）
企业在中国境内部署及应用AI Agent的主要法律问题（二）
企业在中国境内部署及应用AI Agent的主要法律问题（一）
《大型网络平台个人信息保护规定（征）》解读二：数据本地化及其数据中心合规管理
《大型网络平台个人信息保护规定（征）》解读一：负责人及工作机构的特殊合规要求
个人信息保护负责人（PIPO）信息报送及官方审核的十大实务问题
个人信息保护负责人（PIPO）信息报送的十五个实务问题
企业接入国家网络身份认证公共服务的几个常见问题
零售行业的隐秘角落：门店个人信息处理合规评估项目实践
免责声明：
本文所载程序、技术方法仅面向合法合规的安全研究与教学场景，旨在提升网络安全防护能力，具有明确的技术研究属性。
任何单位或个人未经授权，将本文内容用于攻击、破坏等非法用途的，由此引发的全部法律责任、民事赔偿及连带责任，均由行为人独立承担，本站不承担任何连带责任。
本站内容均为技术交流与知识分享目的发布，若存在版权侵权或其他异议，请通过邮件联系处理，具体联系方式可点击页面上方的联系我。
本文转载自：网数与人工智能法律实务 Eva Zhang《Key Legal Issues of FIE in China Using Overseas HQ AI Solution》