You are using an outdated browser and your browsing experience will not be optimal. Please update to the latest version of Microsoft Edge, Google Chrome or Mozilla Firefox. Install Microsoft Edge

August 6, 2025

Thailand Releases Draft Guidelines on Government Cloud Adoption and Data Classification

Thailand’s Digital Government Development Agency (DGA) has released drafts of two pivotal documents to guide Thai government agencies in adopting cloud technology and classifying data for cloud usage. These draft guidelines, open for public hearing through August 12, 2025, are part of the national “Go Cloud First” policy, which aims to accelerate digital transformation, improve efficiency, and ensure robust data security across the public sector. The new standards will have significant implications for both government agencies and cloud service providers operating in Thailand.

Highlights of the draft guidelines are presented below.

Government Cloud Usage Guidelines

  • Cloud-first transformation: All government agencies are directed to prioritize cloud solutions for new IT projects, in line with the cabinet’s “Go Cloud First” policy.
  • Cloud model selection: Agencies must assess their needs and select the most appropriate cloud deployment model—public, private, hybrid, or community cloud—based on the sensitivity of the data and operational requirements.
  • Service types: The guidelines provide criteria for choosing between Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), emphasizing the importance of using standard, non-customized services where possible.
  • Cost management: Agencies are required to plan and separate cloud-related expenses, ensuring transparency and efficient budget allocation.
  • Cloud migration: The guidelines outline the steps for migrating to the cloud and highlight the role of cloud service providers in facilitating the process, including supporting innovation and enabling smooth exit strategies.
  • Procurement compliance: All cloud procurement must comply with public sector procurement laws and regulations. Only providers meeting government-mandated standards can be selected.
  • Security and shared responsibility: The guidelines clarify the division of security responsibilities between cloud providers and government agencies. While providers manage infrastructure security, agencies remain responsible for data, application, and access controls.
  • Legal framework: Agencies must comply with the Digital Government Administration Act, Cybersecurity Act, Personal Data Protection Act (PDPA), and other relevant laws.

Cloud Data Classification Guidelines

  • Three-tier data classification: Government data is classified into three categories:
    1. Official data: Low-sensitivity data, suitable for public cloud storage.
    2. Protected data: Data that could cause harm if disclosed (e.g., tax, medical, or financial records), recommended to be stored in domestic public clouds with enhanced security.
    3. Highly protected data: Critical or top-secret data (e.g., national security information), must be stored in sovereign or state-controlled clouds within Thailand, with the highest security measures.
  • Data sovereignty and localization: The guidelines stress that all government data is recommended to be stored within Thailand to ensure compliance with local laws and maintain data sovereignty. Exceptions require DGA approval, except for highly protected data. The guidelines also distinguish between data at rest and data in transit or processing. While the focus of localization is on data at rest, data in transit (e.g., during transmission) or temporary processing outside Thailand could be permitted under certain technical and legal safeguards, provided no unauthorized access occurs. A localization exemption could be granted with special approval from the DGA.
  • Cross-border data transfers: Storing data outside Thailand is generally prohibited for sensitive information, with limited exceptions subject to DGA approval. The guidelines define “data that should be in Thailand” as data at rest (i.e., data stored on servers), and this does not include data in transit (data being transferred) or data being processed.
  • Risk assessment: Agencies must conduct risk assessments based on confidentiality, integrity, and availability to determine the appropriate level of security and cloud deployment.
  • Security controls: The guidelines mandate strict access controls, encryption, and compliance with international standards (e.g., ISO 27001) for sensitive data.
  • Legal compliance: The framework aligns with the Official Information Act, PDPA, Cybersecurity Act, and other national security regulations.

Implications and Action Steps for Government Agencies and Cloud Providers

Under the new guidelines, cloud adoption will be highly encouraged for government agencies. Any deviation from the cloud-first approach will need to be justified, with the decision-making process documented.

Government agencies who have implemented or are seeking to implement cloud technology will need to review and update their internal policies to align with the new guidelines, implement robust data classification and risk assessment processes for all digital services before migrating data to the cloud, and plan cloud migrations accordingly.

To be eligible for government contracts, cloud service providers will need to meet stringent security, localization, and compliance standards, and prepare for increased scrutiny regarding data residency, security certifications, and service transparency.

Outlook

These new guidelines represent a significant step forward in Thailand’s digital government strategy. All stakeholders should familiarize themselves with the requirements to ensure compliance, minimize risk, and support the secure and efficient adoption of cloud technology in the public sector.

RELATED INSIGHTS​ 

June 23, 2026
On May 14, 2026, Thailand published a ministerial regulation in the Government Gazette to prescribe measures for prevention and suppression of technology crimes. The regulation creates a comprehensive procedural framework for returning money and digital assets to victims of technology crimes. It will take effect 90 days after publication (in mid-August 2026), giving affected entities a limited window to prepare. Mandatory Reporting Obligations for Financial Institutions When a deposit account, e-money account, or digital asset wallet is frozen in connection with a technology crime, the relevant financial institution or business operator must report transaction data to the Anti-Money Laundering Office (AMLO) via AMLO’s designated electronic system. Required data elements include account numbers (sender and receiver), names, identification or passport numbers, legal entity registration numbers, phone numbers, remaining balance, damage amount, transaction reference numbers, and the bank case ID. Institutions that already share data through the information-sharing system under the emergency decree are deemed to have satisfied this reporting obligation, creating an incentive for platform participation. When the Royal Thai Police or the Department of Special Investigation seize or freeze assets related to technology crimes, they must provide AMLO with investigation reports, complaint evidence, money-trail data, and account statements. Notification and Claims Process Once the AMLO secretary-general approves verified reports of a technology crime, the account information of persons connected to the crime will be published in the Government Gazette, triggering a 90-day window for victims to file claims and for related persons to file objections. Officers will also publish details on AMLO’s electronic media and send registered mail to identified victims, which will be deemed received after 7 days domestically or 15 days internationally. Victims have 90 days from the date the crime is published in the Government Gazette to file claims through AMLO’s electronic system. Claims must include
June 15, 2026
The surge in AI development has led to a desperate demand for large, high-quality training data. However, real-world data can be expensive to collect, difficult to access, and often subject to strict privacy and regulatory constraints. Synthetic data, which consists of artificially generated records that replicate the statistical properties of real-world data without reproducing specific individuals’ information, provides an appealing solution by generating artificial datasets at scale without relying on identifiable personal information. It combines speed, cost efficiency, and regulatory compliance, making it a sensible alternative for organizations seeking to reduce risks while maintaining data utility. When properly anonymized, synthetic datasets may fall outside the scope of laws such as the EU’s General Data Protection Regulation (GDPR) or Thailand’s Personal Data Protection Act (PDPA), reducing compliance burdens while still supporting high-quality model training. However, relying on synthetic data without rigorous legal due diligence could be a strategic mistake. It replaces one set of known risks (scraping, direct privacy liability) with a new set of complex liabilities. The narrative that synthetic data is a “silver bullet” for privacy and IP compliance is dangerous and could be misleading. While synthetic data addresses data scarcity, it also introduces new legal uncertainties. Legal counsel should anticipate downstream risks arising from compromised data sources. Models trained on unlawfully obtained data may need to be decommissioned, even if their outputs appear lawful. What is synthetic data? Synthetic data refers to artificially generated information created using AI techniques such as deep learning and generative models. Instead of copying real records, it reproduces the statistical patterns and relationships found in the original dataset. Synthetic data generally falls into three categories: Fully synthetic data – Entirely new data points generated from learned patterns. The model studies the structure of the original data and produces records that resemble real-world
June 11, 2026
Thailand’s Electronic Transactions Development Agency (ETDA) has released a revised draft Electronic Transactions Act (ETA) for public hearing from May 12, 2026, to June 15, 2026. This is not merely an amendment to certain provisions of the current ETA, but a comprehensive redrafting of the entire act. The revised draft ETA introduces several significant changes from the current framework, with practical implications for businesses operating in Thailand. Unified Coverage of Public and Private Sectors The current law segregates government transactions into a separate chapter with distinct rules. The draft ETA eliminates this division, defining “transaction” to encompass civil and commercial juristic acts as well as administrative procedures, administrative contracts, and other acts of government agencies. Enhanced E-Signature Definition The definition of “electronic signature” is broadened to expressly include biometric data and refocused on identifying the signatory and demonstrating intent regarding the content of the electronic data. Shift in Burden of Proof When a party challenges the reliability of electronic data created using a “trusted electronic method” or a method prescribed by the ETDA, the burden of proof and the cost of proving unreliability shifts to the challenger. Introduction of New Digital Method Concepts The draft ETA introduces several new digital method concepts that are not currently recognized under the existing ETA framework. These include: Electronic timestamping (e-timestamp) Electronic registered delivery Electronic company seals Electronic stamp duty compliance Electronic identity authentication and verification Electronic transferable records (electronic bills of lading, promissory notes, and similar negotiable instruments) Recognition of Automated Systems and Electronic Contracting The draft ETA expressly recognizes the legal validity and enforceability of contracts formed through automated systems, including contracts concluded entirely between automated systems or between an automated system and a person. A party may not deny the binding effect of such contracts solely because no human review
June 5, 2026
Vietnam’s AI regulatory framework has reached an important milestone. While the Law on Artificial Intelligence No. 134/2025/QH15 (AI Law) established the foundation for AI governance, many practical compliance requirements were left to implementing regulations. On April 30, 2026, the government issued Decree No. 142/2026/ND-CP (Decree 142), which took effect on May 1, 2026, and provides the first detailed guidance on the implementation of the AI Law. Although an official list of high-risk AI systems is still pending from the prime minister, Decree 142 provides valuable insight into how Vietnam’s risk-based AI regulatory framework will operate in practice. Risk Classification Framework The AI Law adopts a risk-based approach under which AI systems are classified as high-risk, medium-risk, or low-risk. Decree 142 builds on this framework by providing detailed guidance on how these classifications are determined. High-risk AI systems are determined based on factors such as (i) their potential impact on life, health, property, human rights, public interests, or national security; (ii) the sector in which they are deployed; and (iii) the scale of affected users or integration with critical infrastructure. The latest draft list of high-risk AI systems appears to follow these same principles. Medium-risk AI systems generally include systems that may mislead, influence, or manipulate users, particularly where users may not realize they are interacting with AI or AI-generated content. The focus is therefore on transparency and authenticity risks rather than broader societal or safety concerns. Low-risk AI systems are those that do not meet the criteria for either high-risk or medium-risk classification. Importantly, Decree 142 seeks to avoid over-classification. Certain systems may fall outside the high-risk or medium-risk regimes, including internal-use systems, office-support tools, technical editing applications, certain back-end processing systems, and AI systems used in artistic, gaming, cinematic, or other creative contexts. Providers must also review and