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

March 27, 2026

Vietnam’s multi-layered AI development framework

Asia Business Law Journal

Vietnam’s emerging governance framework for artificial intelligence (AI) is developing through a multi-layered structure comprising three components:

  1. Policy instruments setting national priorities for AI development;
  2. Regulatory framework governing development, provision, deployment and use of AI; and
  3. Technical standards and voluntary guidelines.

Policy level. At policy level, the foundation for a strategic framework for AI development and governance was laid in 2021 by the National Strategy for Research, Development and Application of AI until 2030, aimed at strengthening the national AI ecosystem and positioning Vietnam as a regional AI innovation hub.

Subsequently, resolution No.57-NQ/TW (2024) identified AI as a key driver of science, technology, innovation and national digital transformation. AI was also designated as a strategic technology under decision No.1131/QD-TTg (2025) listing priority technologies across sectors.

Regulatory framework. At the legislative level, the new Law on Artificial Intelligence took effect on 1 March 2026, establishing the core regulatory framework governing development, provision, deployment and use of AI systems.

Controlled testing for emerging AI technologies is implemented under the Law on Science, Technology and Innovation.

The AI Law is expected to be further operationalised through implementing instruments, most notably a draft decree guiding the AI Law, and draft decision of the prime minister identifying high-risk AI systems (both published in February 2026). A decision establishing priority datasets for AI development is also anticipated.

Compliance obligations may also arise under sectoral regulatory regimes, including data protection, cybersecurity, banking, consumer protection, e-commerce and intellectual property, particularly where AI systems are used in automated decision-making or data-driven services.

Technical standards and non-binding guidelines. Vietnam’s AI governance framework is also supported by technical standards and voluntary guidelines. A key instrument is decision No.1290/QD-BKHCN (2024), providing guidelines for responsible research and development of AI systems, and represents Vietnam’s first national AI ethics code. The Ministry of Science and Technology (MST) encourages organisations to adopt these principles – though they are not legally binding – to promote responsible AI development.

Vietnam has also begun incorporating international AI technical standards into its national standards system. While these standards are not legally binding unless incorporated into legislation or National Technical Regulations, they provide guidance on AI terminology, lifecycle management, robustness, governance frameworks and machine learning systems, helping align Vietnam’s AI governance ecosystem with international standards.

Regulation under AI Law

Scope of application. The AI Law applies to Vietnamese organisations and individuals, as well as foreign entities engaging in AI-related activities in Vietnam, but excludes those solely for national defence, security and cryptography purposes.

A defining feature of the AI Law is regulating by role rather than by industry, distinguishing between:

    1. Developers who design, build, train, test or fine-tune AI models and control technical methods, training data or model parameters;
    2. Providers who place AI systems on the market or put them into use under their own name;
    3. Deployers who use AI systems under their control in professional or commercial activities;
    4. Users who interact with AI systems or rely on their outputs; and
    5. Affected persons whose lawful rights or interests may be directly or indirectly impacted by the deployment or outputs of AI systems.

Risk-based classification as first compliance gate. At AI Law’s core is a regulatory model in which AI systems are classified as high, medium or low risk.

    1. High risk: AI systems that may cause significant harm to life, health, lawful rights and interests, or national and public interests. The prime minister will issue a list identifying such systems. The draft AI decree also allows exclusions, including systems used for technical data processing, internal operations, controlled research environments or advisory purposes with human oversight. But systems posing significant risks to national security or public order may be designated as high risk.
    2. Medium risk: AI systems that may confuse or influence users where they cannot recognise that they are interacting with AI-generated content or an AI system. Certain systems are excluded, including those performing purely technical editing or used in clearly fictional contexts such as filmmaking or gaming, unless they simulate real persons or events for commercial, financial or political purposes.
    3. Low risk: All remaining systems. This classification framework functions as the primary gateway to compliance, determining whether obligations such as classification notification, conformity assessment and other governance requirements apply. Providers are responsible for initial classification prior to deployment, while deployers must reassess classification if the system is materially modified or used in a different context.

Governance based on risk levels

  1. High-risk AI systems. Classification as high risk triggers extensive governance obligations across the AI lifecycle.
    1. Risk notification: Providers must notify the MST of classification results through the national AI portal before deployment.
    2. Conformity assessment: Certain high-risk systems must undergo conformity assessment before deployment and after significant modifications, through either third-party certification or provider self-assessment depending on regulatory requirements.
    3. Transparency obligation: Providers must ensure users can recognise when they are interacting with AI systems and AI-generated content is clearly labelled. Deployers must disclose when AI-generated or edited content is made public.
    4. Incident management: Developers, providers, deployers and users must ensure system safety and address incidents promptly. Serious incidents need remedial measures and competent authorities must be notified.
    5. Local presence for foreign providers: Foreign providers supplying high-risk AI systems must establish a lawful contact point in Vietnam, and in certain cases maintain a commercial presence or authorised representative.
    6. Lifecycle governance obligations: High-risk systems are subject to ongoing obligations relating to risk management, data governance, documentation, human oversight and regulatory co-operation.
  2. Medium-risk and low-risk AI systems. As with high-risk systems, providers of medium-risk systems are required to conduct risk classification and submit corresponding notification to the MST.

Providers and deployers must comply with transparency obligations and be prepared, on request, to explain the system’s purpose, operation, key input data and risk management measures, without being required to disclose source code, detailed algorithms or other trade secrets. Deployers are also responsible for explaining system operation, risk controls, incident handling measures and safeguards for the lawful rights and interests of affected persons.

Low-risk AI systems, by contrast, are subject to a largely post-hoc oversight model. Providers and deployers are only required to account for such systems when there are indications of legal violations or adverse impacts on lawful rights or interests, while users remain free to use low-risk systems for lawful purposes at their own responsibility.

Regulatory requirements

In addition to governance under the AI Law, several sector-specific regulations impose additional requirements on deployment and use of AI in regulated industries.

In banking and finance, the State Bank of Vietnam has issued a draft circular on safety and risk management for AI deployment. Financial institutions must complete pre-deployment procedures, including risk classification documentation, information security testing, impact assessments for high-risk systems, and operational safety plans covering monitoring and incident response. The draft also introduces transparency requirements and prohibits using AI to exploit customer vulnerabilities or promote unsuitable financial products.

Under consumer protection, operators of large digital platforms must periodically assess and report their use of AI technologies and provide information to competent authorities for regulatory supervision.

In e-commerce, the Law on E-Commerce requires transparency where algorithms or AI-based recommendation systems are used to rank or display goods on digital marketplaces. Platforms must disclose the main criteria used by these algorithms and allow users to enable or disable such features.

For data protection, AI-related data processing is governed by the Law on Personal Data Protection. Organisations using personal data for AI training or analytics must ensure processing occurs for legitimate purposes and implement safeguards such as access controls, encryption and compliance with data subject rights and cross-border transfer requirements. The Data Law further establishes principles governing data management, sharing, and infrastructure relevant to AI development.

Outlook

Vietnam has taken a significant step towards establishing a comprehensive legal framework for AI governance. While the AI Law provides the foundational regulatory structure, several implementing instruments remain under development and will further clarify compliance obligations.

As Vietnam’s digital economy expands, the regulatory approach is likely to evolve towards a more integrated governance model combining AI-specific regulations, sectoral oversight, and internationally aligned technical standards. Organisations deploying AI systems should therefore closely monitor regulatory developments and strengthen internal governance, risk management and transparency practices to prepare for the next phase of AI regulation.

 

This article was originally published by Asian Business Law Journal.

RELATED INSIGHTS​ 

January 13, 2021
Thailand’s Office of the Insurance Commission (OIC) recently issued two notifications—one for life-insurance companies and another for insurance companies—establishing key criteria and requirements for insurance companies to manage risks relating to IT and cybersecurity. The notifications, entitled Notifications Re: Criteria for the Supervision and Management of Risks Relating to Information Technology for Life/Non-life Insurance Companies B.E. 2563 (2020) came into effect on January 1, 2021, and cover eight major aspects of IT risk management as detailed below. IT Governance Insurance companies are required to monitor and manage IT risks and cyber threats in accordance with the size, characteristics, complexity, and context of their business operations, and each company should have at least one director with knowledge of, or past experience in, the field of information technology. IT Project Management Insurance companies are required to develop a written framework for IT project management, covering at least the commencement, implementation, and control of the project, as well as the project closing and post-project auditing. Companies must also appoint a committee for supervising and monitoring IT projects. IT Security Insurance companies are required to institute a written IT security policy, which must be reviewed at least once a year or upon implementing any significant changes. The policy must be approved by the board of directors, or a relevant subcommittee appointed by the board of directors. In outsourcing IT activities to third-party service providers, or entering into any arrangement that allows business partners to connect to or access the company’s IT system, insurance companies are required to specify their own criteria and procedures for the selection of third-party service providers, enter into a written service agreement and a service level agreement with the third-party provider, and conform with other requirements under the notifications. Insurance companies will also be required to comply with the OIC’s forthcoming
January 8, 2021
At a meeting on December 21, 2020, the Thai Board of Investment (BOI) approved a series of stimulus packages aimed at encouraging local and foreign investment, as the government seeks to boost Thailand’s economic recovery from the COVID-19 pandemic. The additional investment incentives, which will be promoted by the BOI in the upcoming year, include a number of sector- and project-specific stimulus measures.   Additional Tax Incentives for Large-Scale Projects Projects in target industries with investment of at least THB 1 billion (approx. USD 33 million) over a 12-month period, starting from the issuance of the BOI promotion certificate, will be entitled to an additional 50% corporate income tax (CIT) deduction for a period of five years, calculated on top of the standard 5–8 year CIT exemptions offered under the normal BOI tax-incentive scheme. To obtain this special tax incentive, eligible projects may apply to the BOI from January 4 to December 30, 2021.   Stimulus Package for Digital Economy and Software Industry Projects that support digital technology adoption, such as software integration, artificial intelligence, machine learning, or big data analytics, may benefit from 50% CIT exemptions on profits generated from their existing BOI projects for an additional three years. Applications for the exemption must be submitted by the end of 2022.   Application Deadline Extensions for Special Economic Zones and Five Southern Provinces Measures relating to special economic zones cover more than 300 investment promotion categories, with both tax and non-tax incentives, including an additional tax incentive for target industries such as textiles, agriculture, home furniture, jewelry, and others. These incentives are available to projects located in the border areas of Thailand (i.e., the 10 special economic zones in the provinces of Chiang Rai, Kanchanaburi, Mukdahan, Nakhon Phanom, Narathiwat, Nong Khai, Sa Kaeo, Songkhla, Tak, and Trat), with the
December 22, 2020
John McCarthy, an American computer scientist and inventor, coined the term “artificial intelligence” (AI) in 1956, and is often called the father of artificial intelligence. Now, nearly a half century later, legal professionals recognize that AI is not just a buzzword for novel computer software but, with the ability of computers to perform tasks normally requiring human intelligence, it holds great potential for technology growth. The term AI followed from research that studied and developed concepts around “thinking machines.” Today, AI is generally accepted as a branch of computer science. It concerns the ability of computers to perform tasks normally requiring human intelligence. Subsets of AI include machine learning, deep learning, natural language processing, computer vision, and neural networking. Existing Use of AI in Legal Research So far, the legal profession’s utilization of AI pales in comparison to other sectors, according to a 2019 management consultancy study by Bain & Company. It found that only about 20 to 25 percent of legal departments embrace AI in at least one area of their work, while 40 percent of finance departments and 54 percent of human resources departments do so. A survey in 2017 (on research not associated with AI) by the American Bar Association found that attorneys spend, on average, 16.3 percent of their working hours conducting legal research. Despite the transition of legal research within the last century from using traditional hardcopy materials to computerized databases, to the adoption of online research within the past few decades, little has changed in the time investment, the survey said. With clients pressuring lawyers to reduce costs, leveraging AI to conduct legal research can save time and money. A 2018 article in the Harvard Journal of Law & Technology  exemplified this point in referencing a bankruptcy lawyer who spent 10 hours searching for a