The Cutting Edge of AI Internal Regulations for Global Companies: Governance and Deployment Strategies for Overseas Offices
As of Reiwa 7 (2025), the implementation of generative AI in society is rapidly advancing. For companies, the formulation of “AI Internal Regulations” has evolved from merely a risk avoidance measure to a crucial management foundation that influences global competitiveness.
For organizations expanding their business overseas, adhering solely to Japanese laws and guidelines is insufficient. They must accurately understand and adapt to a complex web of cross-border legal requirements, including the EU AI Act in Europe, China’s Interim Measures for the Management of Generative AI, and the intricate data protection laws enforced in various U.S. states.
This article organizes the unique challenges faced by Japanese companies with overseas bases. It details strategic grouping methods for bases based on similarities in data protection laws across countries and provides design guidelines for “AI Internal Regulations” that effectively balance deployment speed and compliance. These insights are based on the latest official guidelines and practical knowledge.
The Necessity and Strategic Significance of AI Internal Regulations in Global Expansion
In today’s business environment, generative AI has become an indispensable infrastructure for enhancing operational efficiency, reducing costs, and improving decision-making. According to the 2024 Edition of the Information and Communications White Paper, over 90% of companies in major countries such as the United States, Germany, and China utilize generative AI in some capacity. In contrast, the utilization rate among Japanese companies is approximately 70%, indicating a persistent gap in international adoption levels. To bridge this gap and secure a competitive edge in the global market, it is urgent to establish “AI Internal Regulations” across the entire organization, including overseas branches.
One of the greatest risks faced by companies with overseas branches is the issue of “shadow AI,” where employees use AI without company authorization. Particularly overseas, AI utilization often precedes that in Japan, and neglecting to establish robust “AI Internal Regulations” can lead to unforeseen information leaks abroad or substantial penalties for violating stringent local data protection laws. For instance, within the EU, the use of AI deemed to pose “unacceptable risk” under the EU AI Act will be prohibited from February 2025 (Reiwa 7), with potential fines reaching tens of millions of euros for violations.
Therefore, “AI Internal Regulations” for global companies must function not merely as translations of domestic rules but as a “governance mechanism” symbolizing an international governance framework. Maintaining governance from the Japanese headquarters while flexibly adapting to local legal regulations in each country through a two-tier strategy of “Global Core Policy” and “Local Addendum (region-specific additional regulations)” is becoming the standard in current global legal practices.
Design Philosophy of AI Internal Regulations to Control Legal Risks at Overseas Bases
When designing “AI Internal Regulations” with a global expansion in mind, it is crucial to first understand that the risks associated with the use of generative AI are subject to different legal interpretations in each region. The three major risks—information leakage, rights infringement, and hallucination—need to be redefined in an international context.
Regarding the risk of information leakage, there is always a danger that confidential or personal information entered into prompts may be reused as AI training data and unintentionally leaked to third parties. The incident where engineers at Samsung Electronics in South Korea input confidential source code into AI, leading to its leakage, shocked organizations worldwide. Such situations not only result in the loss of protection as “trade secrets” under Japan’s Unfair Competition Prevention Act but also constitute a significant breach of non-disclosure agreements (NDAs) with other companies. Furthermore, under overseas legal frameworks like the GDPR (General Data Protection Regulation), the “use for learning” of personal information may be considered unauthorized use, potentially leading to severe penalties.
In terms of rights infringement, particularly copyright risks, the issues revolve around the liability for infringement if AI-generated content resembles another’s work and the attribution of copyright to the AI-generated content itself. Article 30-4 of the Japanese Copyright Act broadly permits learning for information analysis purposes, but if the generation stage relies on specific works and similarity is recognized, it constitutes infringement. In contrast, legal battles continue in the United States from the perspective of fair use, and in China, there have been rulings recognizing certain copyrights for AI-generated content, indicating that international judicial decisions are fluid. In global “AI Internal Regulations,” it is recommended to incorporate operational flows that consider these regional differences and align with the strictest standards.
Regarding hallucination risk, which refers to the phenomenon where AI generates plausible falsehoods, there are concerns about defamation in external communications and liability for damages due to decisions based on incorrect data. As emphasized in the “AI Business Operator Guidelines” by Japan’s Ministry of Internal Affairs and Communications and Ministry of Economy, Trade and Industry, explicitly stating the “Human-in-the-loop” principle, where humans are involved in the final decision-making, in the “AI Internal Regulations” is a minimum requirement for ensuring global safety.
Strategic Grouping of Data Protection Laws and AI Internal Regulations Across Countries
To accelerate overseas expansion, it is efficient to group target countries based on the nature of their legal regulations and establish a priority for addressing them. Considering the international situation as of Reiwa 7 (2025), it is possible to categorize them into the following four groups.
GDPR Compliance and Strict Regulation Group (EU, UK, Thailand, etc.)
This group is personalityized by extremely strict privacy protection modeled after the General Data Protection Regulation (GDPR) of the European Union (EU) and pioneering comprehensive regulations on AI, such as the EU AI Act. Here, explicit consent from individuals and Data Protection Impact Assessments (DPIA) are strongly required for everything from data collection to processing and international transfers.
Additionally, the EU AI Act adopts a risk-based approach, classifying AI systems according to their risk levels and imposing very stringent transparency obligations and conformity assessments on high-risk systems. Due to the high compliance costs associated with AI utilization in locations belonging to this group, it is imperative to prioritize the localization of detailed “Internal AI Regulations” in these areas.
Unique Reinforcement and National Security-Focused Group (China, Vietnam, etc.)
This group is personalityized by unique regulations that emphasize “national security” and “public interest” in addition to personal privacy protection, as exemplified by China’s Personal Information Protection Law (PIPL) and the Interim Measures for the Management of Generative AI Services. Key features include the obligation to register AI algorithms, strict monitoring of generated content, and the requirement for data localization, which mandates the storage of data within the country.
At the bases of this group, merely applying the “AI Internal Regulations” of the Japanese headquarters is insufficient. It is necessary to establish dedicated operational flows that align with local political risks and the latest guidelines from authorities, as well as to build a regular audit system.
Opt-Out and Consumer Rights-Focused Groups (U.S. States, etc.)
This group emphasizes consumer rights, such as requests for data deletion or cessation of sales, as exemplified by the California Consumer Privacy Act (CCPA/CPRA) in the United States. Since there is no unified federal privacy law in the U.S., state-level regulations exist in a patchwork manner. Additionally, there is a complex situation regarding AI regulations, with the federal government adopting a more lenient stance while state governments are strengthening regulations.
In this context, it is necessary to design flexible “AI Internal Regulations” that align with the strictest standards, such as those in California, assuming a low level of legal stability.
Relaxed and Emerging Regulations Group (Japan, Parts of ASEAN, South America, etc.)
In regions like Japan, there is a focus on promoting “agile governance” through guidelines and self-regulation (soft law) rather than strict enforcement by law (hard law). The legal barriers to utilizing AI are relatively low, making it easier to conduct pilot tests and early implementations.
These locations are strategically prioritized as “pilot cases for AI utilization” in global expansion. The knowledge and safety measures accumulated here can be gradually shared with other groups under stricter regulations.
| Group Name | Main Target Regions | Regulatory Characteristics | Priority of AI Internal Regulations |
| GDPR-Compliant and Strict Regulations | EU, UK, Thailand | Risk-based approach, high fines, AI laws | Extremely high (localized as top priority) |
| Independent Reinforcement and National Security | China, Vietnam | Algorithm registration, content monitoring, domestic data storage | High (requires individual response to local authorities) |
| Consumer Rights Emphasis | Various U.S. States | Consumer opt-out rights, significant differences between states | Medium (requires flexible standard setting) |
| Relaxed and Emerging Regulations | Japan, Emerging Countries | Guideline-focused, agile governance | Medium (utilized as a place for accumulating knowledge) |
Basic Rules for Balancing Deployment Speed and Compliance in Japanese AI Internal Regulations
For global companies to swiftly implement AI across various regions, it is essential to design basic rules based on a “phased rollout” approach, rather than imposing perfect rules on all locations from the outset.
In the initial phase of implementation, a very simple yet strict rule of “prohibiting the input of personal and highly confidential information” is established as a common principle across all locations. This allows companies to begin basic AI utilization—such as general document creation, translation, and aggregation of public information—while avoiding critical information leaks and legal violations, even before completing complex legal reviews in each country.
In the next phase, “individual adaptation (whitelisting)” is advanced according to the high business needs and low risks. For example, in the marketing department, inputting specific customer attribute data is permitted only when technical measures ensure that input data is not used for AI learning, such as through corporate paid plans or API usage with opt-out settings. During this process, it is crucial to incorporate an “application and approval workflow” into the “AI Internal Regulations,” where IT and legal personnel at each location verify local conditions and obtain headquarters’ approval. This is key to maintaining governance without slowing down deployment speed.
Moreover, in global deployment, it is important to clearly define “responsibility.” The “AI Internal Regulations” should specify that local employees and their respective departments bear full responsibility for the outcomes of tasks performed based on AI-generated results, positioning AI strictly as an “auxiliary tool.” This enhances organizational resilience in the event of unforeseen issues.
Specific Measures for AI Internal Regulations to Comply with the Latest EU AI Law and Other Regulations
For Japanese companies expanding their business overseas, the most urgent matter to address as of Reiwa 7 (2025) is the extraterritorial application of the EU AI Law. This law applies not only to companies based within the EU but also to AI systems offered within the EU and their output results used within the EU.
When incorporating compliance with the EU AI Law into “AI Internal Regulations,” the critical process is the “inventory and classification of AI assets.” Companies are required to identify which of the four risk levels defined by the law (unacceptable, high risk, limited, minimal) their AI systems fall under. Particularly for “high-risk AI” used in employment decisions, education, financial services, and infrastructure management, there is a strict obligation to conduct conformity assessments, establish quality management systems, maintain logs, and ensure human oversight.
Additionally, in China, under the “Interim Measures for the Management of Generative AI Services” enacted in Reiwa 5 (2023), it is necessary to register algorithms and conduct security evaluations when providing AI services with public significance. In the “AI Internal Regulations” in China, it is critically important for business continuity to establish provisions for the registration process with authorities and strictly limit the input of information classified as China’s “core data” or “important data.”
| Regulation Name | Scope and Main Obligations | Reflected Items in AI Internal Regulations |
| EU AI Law | Use and provision within the EU, output provision from outside the EU. Obligations according to risk classification. | Flow for AI system risk classification, explicit human oversight obligations for high-risk AI. |
| China Interim Measures for Generative AI Management | Service provision within China. Algorithm registration, content monitoring. | Regulations for registration application process with authorities, prohibition of inputting data related to national security. |
| U.S. CCPA/CPRA | Data processing of California residents. Right to opt-out of sale, right to deletion. | Ensuring transparency in employee processing of personal data, opt-out response channels. |
Enhancing AI Internal Regulations and Practices Through Collaboration with Overseas Law Firms
To ensure that global “AI internal regulations” remain effective and not merely symbolic, it is essential to establish a “joint formulation and operation system” in close collaboration with local law firms, rather than having the legal department of the Japanese headquarters develop them in isolation.
The first practical step is to identify “critical issues” that require modification based on the “AI internal regulations” and guidelines formulated in Japan, in light of each country’s legal system. For instance, it is necessary to highlight areas where Japanese-specific perspectives are strong, such as criteria for AI usage, definitions of confidential information, and the linkage with employment regulations concerning adverse actions. Subsequently, specific questions should be posed to local attorneys, such as “Does this operation conflict with local labor laws or privacy laws?”
Next, request estimates and collaboration support from local law firms (or existing partners). It is crucial not to simply delegate by saying, “Please conduct a legal check,” but to accurately convey your business model and AI usage scenarios (for example, analyzing European customer data with AI in Japan) and seek specific risk assessments. Additionally, in multilingual deployments, it is worth considering the method of “back translation” to ensure that legal nuances are accurately conveyed, beyond merely instructing translations of guidelines into English or local languages.
Law firms like Monolith, which specialize in IT and global legal affairs, act as a hub with these overseas law firms, clarifying instructions, optimizing costs, and providing feedback on extracted local rules to the Japanese headquarters’ regulations. This support aids in constructing truly global and functional “AI internal regulations.”
5 Steps to Embed AI Internal Regulations in Your Organization and Regular Reviews
After formulating global “AI internal regulations,” the next challenge is how to effectively disseminate them among employees at each location and prevent them from becoming mere formalities. The following five-step process is recommended for embedding these regulations.
Step 1 is “Sharing the Purpose of Global Implementation.” Management should communicate not only the aspect of risk management but also how AI utilization can benefit each country’s location, thereby lowering employees’ psychological barriers.
In Step 2, “Identifying Available Services” tailored to the operational personalityistics of each location is conducted. Distribute IDs for secure corporate plans and physically and systematically restrict the use of personal free accounts.
Step 3 involves conducting “Multilingual and Multicultural Employee Training.” This goes beyond merely conveying the wording of the rules; it includes educating employees on why certain inputs are dangerous, using specific examples such as local sanction cases.
In Step 4, monitor the utilization status at each location and establish a feedback loop to capture any inconveniences with the rules or new needs.
As Step 5, conduct regular reviews of the “AI internal regulations” at least every six months, in line with technological advancements and legal amendments in each country.
Particularly from Reiwa 7 (2025) onwards, the spread of more autonomous technologies such as AI agents and physical AI is anticipated. Consequently, the definition of “mechanisms involving human judgment” is expected to shift from simple verification tasks to more advanced audits and discussions on responsibility allocation. In the rapidly changing world of AI, regulations that are “created once and left unchanged” pose a risk in themselves. “Dynamic governance,” which continuously reflects the latest international developments and updates flexibly, should be the goal for global companies.
Summary: Turning Risks into Opportunities with Global AI Internal Regulations
As we approach the year Reiwa 7 (2025), the effective utilization of generative AI will be crucial for the success of companies. Establishing “AI Internal Regulations” that encompass overseas branches is a top priority for global compliance. It is essential to not only adhere to Japanese guidelines but also to accurately grasp stringent comprehensive regulations like the EU AI Act and the dynamic legal changes in the United States and China. Strategic deployment based on the grouping of branches is required.
Starting with a clear basic rule of “uniform prohibition of personal information input” at the initial stage, and gradually transitioning to individual responses from operations where safety has been confirmed, is a practical and powerful method that balances deployment speed and risk management. Furthermore, by collaborating with local law firms and maintaining governance from the Japanese headquarters while adapting to local laws, a “layered regulation development” can be achieved, resulting in truly effective global governance. The evolution of AI technology is relentless, and the legal environment surrounding it is constantly changing.
To transform this change from a “risk” into an “opportunity,” it is essential to use “AI Internal Regulations” based on expert knowledge as a compass and to continuously build a flexible yet robust governance system. For companies accelerating their global expansion, aligning the complex AI regulations of various countries with their business needs is an extremely challenging task that requires a high level of expertise. At Monolith Law Office, our specialized team, which combines IT attorneys and engineers, provides legal advice based on an advanced understanding of technology.
Our firm offers comprehensive support for the global establishment of “AI Internal Regulations” based on the following three pillars:
- We closely collaborate with local law firms and existing partner firms worldwide to build governance that aims for full compliance with GDPR, the EU AI Act, China’s PIPL, and U.S. state laws.
- We provide one-stop support for everything from requesting estimates from local law firms to directing the entire project and coordinating legal issues, dramatically reducing clients’ coordination costs.
- Drawing from the know-how of “AI Internal Regulations” developed in Japan, we accurately extract important matters such as “criteria for AI use” to be provided to overseas offices and give precise instructions for translating guidelines into English, establishing globally unified safety standards.
To harness the innovative technology of AI as a driver for cross-border growth, it is necessary to eliminate legal uncertainties and build a system that allows for confident acceleration.
Guidance on Measures by Our Firm
Monolith Law Office is a legal firm with extensive experience in both IT, particularly the Internet, and law. AI businesses come with numerous legal risks, making the support of attorneys well-versed in AI-related legal issues indispensable. Our firm provides advanced legal support for AI businesses utilizing technologies like ChatGPT. Our team, consisting of attorneys and engineers familiar with AI, offers services such as contract drafting, examining the legality of business models, protecting intellectual property rights, addressing privacy concerns, and establishing internal AI regulations. Detailed information is provided in the article below.
Category: IT
