Artificial intelligence is becoming the core element driving the competitive capacity of many corporate organizations in the modern economy. The scope of applications ranges from startups developing software-as-a-service platforms on cloud computing infrastructure to traditional corporations integrating data analytics algorithms into their operational processes. As economic value increasingly concentrates on intangible components including software, algorithmic models, datasets, and processing procedures, legal risks related to technology replication or entanglement in ownership disputes escalate proportionately. These risks exhibit particular severity during phases when businesses seek to raise capital, establish strategic partnerships, or participate in mergers and acquisitions. This article provides an in-depth and comprehensive legal analysis to identify IP assets, guide the selection of appropriate protection instruments, prepare for detailed legal due diligence, and optimize the valuation of intellectual property assets up to May 2026 based on Vietnam’s latest legal framework.
1. What is Intellectual Property IP in Technology, AI & M&A and why is it important ?
Intellectual property is not merely an administrative procedure to acknowledge the rights of creators but the legal foundation shaping the entire intangible asset structure of an enterprise. According to the Law amending and supplementing a number of articles of the Intellectual Property Law No. 131/2025/QH15, effective from April 1, 2026, the mindset regarding intellectual property management in Vietnam has shifted strongly from the principle of pure right protection to the principle of asset capitalization and commercialization. This shift requires businesses to view intellectual property as a strategic competitive tool. In the context of technology and artificial intelligence, intellectual property rights play an essential role through the aspects analyzed below.
1.1. Proving ownership of core values
Technology companies operate primarily based on source code platforms, training datasets, machine learning algorithms, and brand assets. Establishing intellectual property rights provides solid legal evidence to affirm legitimate ownership over these core values. This is especially crucial as the legal system has begun to officially recognize and clearly classify objects generated through artificial intelligence systems, as detailed in Government Decree 100/2026/ND-CP for industrial property and Government Decree 134/2026/ND-CP for copyright. Protection titles issued by competent state agencies serve as the absolute legal evidence before courts when infringement occurs.
1.2. Reducing legal risks
Building a transparent intellectual property portfolio helps businesses prevent and promptly handle disputes arising with internal personnel or external partners. Specifically, early-established protection measures enable organizations to control the risk of violating open-source license terms, prevent trademark disputes in international markets, or avoid copyright lawsuits regarding source code developed by third parties. Legal clarity is a prerequisite to ensuring business continuity, helping enterprises avoid operational disruptions caused by preliminary injunctions from judicial authorities.
1.3. Increasing negotiation power in fundraising/M&A
In merger and acquisition transactions or venture capital fundraising processes, the transparency of intellectual property assets is always a central evaluation criterion. A clear intellectual property structure facilitates a smooth detailed legal due diligence process, minimizing red flags that could disrupt or cancel the entire transaction. Article 8a of the Intellectual Property Law 2025 officially recognizes intellectual property rights as an independent asset class that can be used for charter capital contributions, mortgages at credit institutions, and direct participation in commercial investments. Therefore, a robust intellectual property system will directly enhance the overall valuation of the target company, bringing substantial financial advantages to founding shareholders.
1.4. Creating new revenue streams
Intellectual property provides the legal basis for businesses to expand their business models through licensing activities, technology transfers, or establishing co-development agreements with strategic partners. These activities allow businesses to maximize profit margins from research and development outcomes without necessarily undertaking direct commercial exploitation across all market segments, thereby optimizing operational costs and expanding global market access.
2. What “puzzle pieces” make up IP in an AI product ?
Depending on the specific business model, an artificial intelligence platform or system typically comprises multiple distinct intellectual property asset groups. The synchronized combination of these protection mechanisms creates a comprehensive legal defense shield for the enterprise. Accurately identifying each asset type is the first step in the intangible asset management process.
2.1. Patents/Technical solutions
Exclusive patents protect technical solutions that possess novelty, involve an inventive step, and are industrially applicable according to current legal regulations. In the field of artificial intelligence, patentable subject matter generally focuses on inference optimization mechanisms, deep neural network architectures, automated data processing pipelines, model compression techniques without accuracy degradation, or solutions integrating artificial intelligence into end devices with strict hardware computational constraints. Furthermore, security methods countering system attacks or techniques reducing latency in natural language processing are highly valuable protectable subjects. The generation and establishment of industrial property rights for objects created via artificial intelligence systems have been specified in Government Decree 100/2026/ND-CP.
2.2. Trademarks
Trademarks encompass company names, commercial product names, graphic design symbols, and promotional slogans used to distinguish the goods and services of different economic organizations in the market. For businesses providing artificial intelligence platforms aiming for multinational scale expansion, early trademark registration is a decisive factor in avoiding the risk of competitors or squatters appropriating commercial identities in target markets. A trademark acts as the bridge connecting technological reputation with service user loyalty.
2.3. Copyrights
Copyright protects the direct material expression of literary, scientific, and artistic works. For artificial intelligence products, copyrightable subjects primarily include collections of software source code, technical specification documents, user interface design texts, and operational manuals. Notably, effective from April 9, 2026, Article 5a of Government Decree 134/2026/ND-CP details the protection conditions for works created with the assistance of artificial intelligence systems. Accordingly, copyright only arises when humans contribute significantly and play a decisive role in the work’s formation process, while simultaneously bearing full legal responsibility for the generated content. Products automatically rendered by artificial intelligence systems without decisive human directional intervention will be denied copyright protection, meaning such products fall into the public domain.
2.4. Trade secrets
In tech industry practice, many core values of artificial intelligence systems cannot or should not be disclosed through patent applications, due to the specific requirement of publicizing the technical solution in this procedure. These elements are protected as trade secrets. The trade secret portfolio usually includes detailed algorithmic structures currently deployed, exclusive interaction prompt sets, data labeling classification criteria, machine learning fine-tuning parameters, and future technical development roadmaps. For information to be recognized and protected as a trade secret by state agencies, the law requires the enterprise to prove three core elements: the information is not common knowledge, it possesses actual commercial value, and the enterprise has applied reasonable physical and technical confidentiality measures.
2.5. Data & data usage rights
Data is an indispensable foundational resource for training artificial intelligence models. Data-related assets involve legal collection rights, analytical processing rights, commercial application rights, and information sharing rights based on contractual commitments with partners. The processing of personal data must strictly comply with the Personal Data Protection Law, officially effective from January 2026. This law requires organizations to conduct data processing impact assessments and update records periodically every six months or immediately upon changes in usage purposes or the emergence of new service types. The data exploitation process must also ensure integrity, security, and the prevention of data poisoning risks or the re-identification of individuals regarding anonymized datasets.
3. Common risks causing businesses to “lose rights” or block deals
During the product development and commercialization process, many organizations violate fundamental intellectual property management principles, leading to the loss of legitimate rights or facing collapse in strategic fundraising transactions. Early identification of these risks provides the foundation for corporate leadership to build the most effective preventive measures.
3.1. Unclear chain of title
The largest and most common risk in tech companies is the failure to clearly identify which organization or individual truly owns the source code, algorithmic models, or training datasets. Many practical cases show software being developed by internal personnel or independent contractors, yet collaboration contracts completely lack intellectual property transfer clauses regarding the work outcomes. Under Vietnamese legal principles, without a clear written property right transfer agreement, the direct creator of the work can invoke copyright to demand compensation or block the platform’s usage, causing severe disputes that directly lead to failure when the enterprise proceeds to raise investment capital.
3.2. Misuse of open-source terms (open-source compliance)
Modern artificial intelligence systems are frequently built upon a multitude of available open-source libraries. Integrating these components without establishing a control mechanism for license compliance can lead to devastating legal consequences. In particular, utilizing code segments governed by copyleft licenses within a proprietary commercial software product can trigger a mandatory legal obligation forcing the enterprise to release its entire closed source code to the public. The incompatibility between open-source licenses and the enterprise’s core business model is a primary factor causing many investors to decline acquisition transactions to avoid core asset leakage risks.
3.3. Input data without rights
The process of collecting data via automated scraping tools from news sources or utilizing partner system data without clear commercialization approval carries immense property right infringement risks. However, to promote innovation, the Intellectual Property Law 2025 introduced a flexible mechanism allowing businesses to use legally published texts and data for analysis to test and train artificial intelligence systems. This act is permitted on the absolute condition that it does not unreasonably prejudice the legitimate interests of the author or right holder, and is not aimed at direct profit generation from reselling the original data. Violating this legal boundary can lead to damage compensation lawsuits of massive scale.
3.4. Premature disclosure
A fundamental principle of global patent law is that a technical solution must possess absolute worldwide novelty at the time the state management agency receives the registration application. Independent research engineering teams disclosing system architectures, presenting algorithms at scientific conferences, or publishing specialized analytical articles online before finalizing patent application procedures will eradicate the possibility of being granted a protection title in most key legal markets. This activity inadvertently turns a highly valuable exclusive asset into public domain knowledge that any competitor has the right to apply for free.
3.5. Overlapping/hard-to-protect trademarks
Many tech startups often delay commercial trademark registration until the product has recorded actual revenue streams to save initial costs. Launching a product into the market without conducting in-depth clearance searches and filing a protection application entails the risk that the trademark has already been filed by other organizations or exhibits confusing similarity with legally protected trademarks. Consequently, the enterprise is forced to execute comprehensive rebranding campaigns with costly restructuring expenses and negative impacts on existing customer recognition, severely diminishing the brand value painstakingly built.
4. Patent protection for technological innovation, AI systems, and software
Not all software components within an artificial intelligence system meet the conditions for an exclusive patent grant. However, for breakthrough technical solutions that create long-term competitive advantages, a patent certificate provides tremendously robust legal defensive capabilities, capable of completely preventing competitors from launching similar products.
4.1. When should you consider filing a patent ?
Management should consider filing a patent application when the technological solution demonstrates a clear technical characteristic, solving a specific technical problem rather than stopping at a broad business idea or an abstract mathematical model. The mandatory timeline for filing is before executing any public information disclosure or offering the product to the market. Crucially, under the amendments in Government Decree 100/2026/ND-CP effective from April 1, 2026, a fast-track substantive examination mechanism has been added to the legal system. This regulation allows significantly shortening the evaluation time for specialized patent applications to three months for cases meeting specific conditions, helping tech companies quickly establish timely protection rights matching the rapid lifecycle of tech products.
4.2. Protectable scope in AI systems
According to current legal examination principles at the Intellectual Property Office of Vietnam and international treaties, the requested protection scope for patents related to artificial intelligence systems typically focuses on the comprehensive processing architecture of the system, including the entire raw data collection chain, pre-processing mechanisms, training methods, parameter fine-tuning, and inference deployment. Additionally, technical optimization methods to accelerate loop processing speeds, minimize physical memory consumption, reduce data processing latency, and compress deep learning model sizes are core targets. Technical mechanisms to integrate artificial intelligence analytical capabilities into edge devices constrained by hardware resources, along with tiered access control systems, are aspects highly likely to be approved for protection by state agencies.
4.3. Patent application preparation checklist
The success of a patent registration process depends largely on the professional quality of the drafted technical specification. The specification must explicitly present the existing technical problem, the new technological solution to overcome that problem, and the achieved technical effects proven through specific quantitative parameters. The dossier needs to broaden the requested protection scope by describing various deployment variants applicable in practice. Organizations must carefully store all legal evidence of the research and development process, including source code change logs, design documents, and testing cycle results. Notably, Government Decree 100/2026/ND-CP also strictly regulates the national security control procedure for patents formed in Vietnam before enterprises file protection applications in other countries, mandating prior approval from competent state management agencies. The Intellectual Property Office will apply the 2025 version of the International Patent Classification in dossier classification and searching.
5. Trademark strategy for tech brands, digital platforms, and the global market
Trademarks are the intellectual property component with the highest commercial presence, acting as a direct bridge between the technological quality developed by the enterprise and user loyalty. For digital platforms, a strong trademark tightly protected across multiple territories will significantly augment the overall intangible asset valuation of the organization.
5.1. What trademarks should be registered ?
The core trademark portfolio needing protection in a tech company includes the official corporate name if this name is used as a direct commercial indication for products sold in the market. Next are the specific names of technology platforms, software modules, or core data analytical tools interacting directly with end-users. Graphic symbols, combinations of image symbols and text characters, as well as slogans conveying long-term business messages should also be filed for independent protection to maximize legal control over the overall brand identity.
5.2. Classification of goods/services: do not do it carelessly
The legal protection scope of a trademark is strictly limited by the classes of goods and services listed by the enterprise in the application. According to the international classification of goods and services, businesses operating in artificial intelligence typically focus their registration resources on Class 9 for downloadable computer software products, and Class 42 for cloud-based software provisioning services, data processing, server hosting, and machine learning applied data analytics. Depending on the vertical industry orientation of the applied product, enterprises must review and supplement related service classes such as medical services, financial services, or corporate governance training consulting. Failing to identify core service classes can create severe legal loopholes for competitors.
5.3. International expansion: follow the market strategy
For digital platform software systems completely unconstrained by physical borders, the trademark protection roadmap must be deployed in parallel with the international market penetration strategy. Organizations need to establish a list of key markets corresponding to the business plan and conduct in-depth trademark clearance searches performed by legal experts before launching promotional campaigns. Businesses in Vietnam can utilize the regulations of the World Intellectual Property Organization to execute international applications via the Madrid system, a mechanism helping streamline administrative procedures, optimize dossier management budgets, and establish a synchronized legal priority mechanism across multiple countries with a single application.
6. Protecting source code, algorithms, data, and trade secrets
Practical analytical data shows that many leading global tech companies maintain competitive advantages primarily based on trade secrets and high-level information security operational systems. However, a trade secret only generates legal value if and only if the enterprise can prove the confidentiality of the information and the comprehensiveness of the protective measures applied.
6.1. Source code protection
Source code is a foundational structural asset requiring protection through the strictest layers of information security governance. Organizations must apply rigorous source code repository access delegation policies according to the specialized functional roles of each department, mandate multi-factor authentication, and store all access event logs for tracing purposes. The onboarding and offboarding processes for personnel must be accompanied by immediate access right provisioning or revocation and an inventory of all handed-over digital assets. Enterprises need to insert stringent legal binding clauses on information confidentiality and intellectual property transfer into all employment contracts and service provision contracts to establish a solid invisible legal barrier.
6.2. Algorithms, models, prompts, pipelines: what to make public and what to keep secret ?
Organizations need to build an information asset classification framework across three basic levels to optimize governance resources. The public level includes basic product functionality description documents serving business marketing activities. The internal confidential level applies to detailed system design documents, technical optimization parameters, training dataset inventories, and fine-tuning interaction prompt systems. The special restricted level is strictly for a limited number of senior management personnel regarding components directly dictating competitive advantage, such as proprietary datasets, critical internal algorithms, and independently developed logic rule systems. Packaging trade secret assets requires clear written descriptions of commercial value, a list of individuals within the access scope, and current protection methods applied at the organization.
6.3. Data & usage rights: don’t leave “legal debt”
The data risk management framework requires enterprises to clearly segregate input data origins, including self-collected organizational data, commercially licensed data, shared data from business partners, and open data. Organizations must store full legal records and agreement documents clearly defining the boundaries of authorized data usage for model training. From a personal information security perspective, since the Personal Data Protection Law took effect in 2026, enterprises are responsible for conducting in-depth assessments and updating personal data processing impact dossiers periodically every six months, or updating immediately upon the emergence of new data-related business service types. Complying with this policy helps businesses avoid administrative sanctions that can reach an enormously high percentage of total revenue.
6.4. Technical obligations and procedures for labeling AI-generated content
According to the detailed regulations in Government Decree 142/2026/ND-CP effective from May 1, 2026, the management of content generated by artificial intelligence systems is strictly controlled by the state through clear disclosure obligations. For organizations acting as artificial intelligence platform providers, the law mandates the application of technical marking solutions in machine-readable formats for all audio, image, and video files generated by the system. Marking methods include embedding digital metadata or applying secure digital signatures.
For organizations acting as deployers, when distributing content to the public, the organization is obligated to provide clear notifications and visible display labels for information likely to cause authenticity confusion, especially content simulating human appearances, imitating voices, or recreating real-life events. Labeling formats can be flexibly implemented through various methods such as displaying warning content directly on the information surface, attaching notices in the title area, displaying on the distribution platform’s screen interface, or providing announcements via audio signals. Certain cases are legally exempted from labeling obligations, including purely technical editing activities, basic spelling corrections, language translation, automated summarization, and applications serving internal circulation or scientific research not published to the public.
7. IP Due diligence in technology-focused M&A transactions
In corporate merger and acquisition transactions and large-scale fundraising, the detailed legal due diligence process regarding intellectual property assets is the most critical phase for assessing the integrity and safety level of the organization’s intangible asset portfolio. The objective of this activity is to verify the legal basis proving the target entity truly holds legitimate ownership and possesses risk control capacity over the foundational technology system.
7.1. What do investors/buyers usually check ?
The in-depth legal due diligence process will focus on reviewing the foundational elements constituting corporate value. Legal experts will examine the continuity of the legal chain of title to accurately determine the true identity of the source code creators and evaluate the valid existence of property right transfer documents from development personnel to the corporate legal entity. The appraisal legal team will scrutinize all employment contracts, expert consulting service contracts, and non-disclosure agreements to ensure absolutely no legal loopholes exist. The consulting organization will also analyze the compliance level of open-source software licenses, review all administrative records of trademarks and patents in key operational markets to assess actual validity status, and identify potential legal dispute risks with third parties.
7.2. Common “red flags” that slow down or fail deals
During the due diligence process, certain specific legal issues can immediately constitute severe risk warning signs that directly impede the signing of merger contracts. These risks include the target enterprise completely failing to present documentation proving legitimate ownership over core tech components built by independent experts or outsourced partners. Training artificial intelligence models using illegally collected data sources or utilizing commercial datasets violating license terms is also an extremely difficult legal bottleneck to overcome. Furthermore, situations involving unresolved legal disputes over shares or property rights lacking final judicial rulings are critical risks compelling the buyer to demand restructuring of the transaction’s financial conditions or to cancel negotiations entirely.
7.3. Reviewing and assessing AI system risks
The enactment of the AI Law 2025 and Government Decree 142/2026/ND-CP introduced an entirely new requirement in tech legal due diligence: checking compliance with AI system risk classification regulations. Organizations developing or providing artificial intelligence systems bear a mandatory obligation to self-classify systems into low, medium, and high-risk tiers based on criteria evaluating the impact level on the health, legitimate rights, and interests of individuals, as well as social order and security. The legal due diligence process will meticulously assess whether the target enterprise has prepared technical notification dossiers for submission to management agencies and completed conformity assessments for systems classified in the high or medium-risk groups before official market deployment.
8. Valuation and commercialization of patents & trademarks based on technology
Intellectual property brings tremendous strategic value not only in terms of defense against unfair competition practices but also acts as an independent profitable asset class generating direct cash flows. Accurately valuing intellectual property assets provides a solid foundation for businesses to execute effective capitalization and fundraising strategies.
8.1. How does IP generate revenue ?
One of the most revolutionary advancements of the amended Intellectual Property Law is the addition of Article 8a, officially recognizing by statute that intellectual property rights are a type of internal management asset that can be used directly in civil, commercial transactions, charter capital contributions, project investments, and asset mortgages to access credit capital. Modern governance thinking demands that enterprises must not waste the economic value of protection titles. The state strongly encourages economic organizations to exploit intellectual property rights to mobilize capital and develop production and business activities, placing intangible assets at the center of the overall growth strategy. Through this legal basis, businesses can create new cash flows by licensing technology usage to partners, executing outright sales and complete property right transfers, or providing tech solutions under third-party brands. Moreover, cross-licensing IP assets among tech organizations helps expand market access capabilities and neutralizes the risk of costly copyright infringement lawsuits.
8.2. Basic valuation framework
The valuation of intangible assets and intellectual property requires objective professional assessment to ensure financial transparency in large commercial transactions. According to international practices and current legal standards in Vietnam, the intellectual property valuation process utilizes three core approaches. The cost approach determines asset value by aggregating all budgets and expenses invested in research, development, and remunerating tech expert teams. The market approach conducts comparative benchmarking against sale or transfer transactions of trademarks or patents with similar technological characteristics that have occurred in the public market. The income approach involves forecasting the expected future income cash flows generated from commercial exploitation licensing activities, subsequently discounting them to present value based on a comprehensive assessment of operational risks.
8.3. Accounting principles for intangible fixed assets
The process of recognizing the value of intellectual property assets in corporate financial reporting systems follows standard accounting principles. According to Circular 99/2025/TT-BTC of the Ministry of Finance, replacing the former Circular 200 and officially effective from January 1, 2026, enterprises are permitted to apply a more flexible and updated accounting system. Accounting Account 213 is utilized to reflect the original cost of intangible fixed assets, which includes computer software programs and intellectual property rights related to technology systems. The original cost of software program intangible fixed assets is determined by the entirety of actual expenses the enterprise has disbursed to legitimately initiate or acquire that system. Adhering correctly to accounting norms and standards helps improve financial capacity indicators and transparentize the asset structure before management agencies and investing shareholders.
9. Handling, transferring, and monetizing tech IP assets
The circulation of intellectual property asset value streams in the digital economy operates through a system of specialized, highly binding legal contracts. Establishing the correct structure for these agreements helps businesses minimize arising conflicts of interest and firmly protect long-term economic exploitation rights.
9.1. Commonly used types of contracts
Transactions exploiting intellectual property value are typically governed by a multi-layered system of commercial contracts. The first is the non-disclosure agreement (NDA) establishing an initial secure data exchange basis before deep negotiations. Next is the master service agreement regulating the cooperation framework and dividing responsibilities. An ownership transfer contract executes the outright sale and hands over all property rights from the seller to the buyer. Finally, a licensing agreement allows partners to exploit intellectual property rights within a specific time and space limit without altering the original ownership. Businesses providing digital software platforms also frequently employ models providing tech solutions under partner brands or establishing cross-licensing agreements to mutually exchange technology usage rights, thereby eliminating the risk of costly patent infringement litigation.
9.2. Principles when transferring/licensing
A rigorous intellectual property licensing contract needs to detail numerous complex technical and commercial aspects. Participating parties must accurately define the boundaries of the usage rights scope, including the authority to apply the asset for specific commercial purposes, and the power permitted to modify or fine-tune the platform system to suit the licensee’s ecosystem. The contract must clearly stipulate geographical territory limits for business operations, the validity duration of the license, and the exclusive or non-exclusive nature of this commercial agreement. Ownership handling principles regarding technology upgrade updates and machine learning models fine-tuned based on the original platform must be transparently delineated to avoid losing technology control to partners. The registration procedure for industrial property usage contracts has currently been significantly streamlined by the state. Under the amendments in Government Decree 100/2026/ND-CP, the Provincial People’s Committee will evaluate and issue decisions granting contract registration certificates within 30 days from receiving a valid dossier, thereby optimizing legal procedure execution time for transacting enterprises.
10. Operating “IP governance” in an AI enterprise
Intellectual property is not a static legal procedure performed only once upon product launch, but a continuous operational risk management system throughout the technology product’s lifecycle. Establishing and maintaining internal compliance governance systems is a mandatory condition to protect sustainable business development against market fluctuations.
10.1. Building a process for recording and classifying technical information
Enterprises need to promulgate internal regulatory systems requiring software engineers and researchers to hold the obligation to record and report new technical initiatives and solutions as soon as they are formed. Based on these invention disclosure reports, the legal department will coordinate with the technical department to analyze and decide on the most appropriate protection direction for each object, including proceeding to file a patent application or establishing strict confidentiality mechanisms as an undisclosed trade secret. Any form of public technical information disclosure in the form of specialized forum articles, tech science event presentations, or public beta releases on telecommunication networks must pass through rigorous board of directors approval procedures to avoid the risk of losing the technological solution’s novelty.
10.2. Controlled testing mechanism and incident reporting obligations
In an effort to foster innovation progress, Government Decree 142/2026/ND-CP issued regulations on a controlled testing mechanism (sandbox) for artificial intelligence systems. Filing dossiers to participate in this testing mechanism provides tech companies with a safe legal space to verify business models and evaluate system performance before deciding on broad market deployment, simultaneously minimizing unintended law violation risks to the utmost extent.
During actual operations, should a severe incident unfortunately occur negatively impacting data integrity and system information security, the deployer and technology provider must strictly adhere to rapid response procedures. Organizations must immediately apply technical measures to limit consequences while preserving and keeping system log data intact to serve in-depth investigations by functional agencies. The legal system stipulates emergency preliminary reporting obligations for severe artificial intelligence system incidents sent to state management agencies within a maximum of 72 hours from incident confirmation, and submitting detailed official reports within the subsequent 15 working days.
10.3. Personnel awareness training and maintaining continuous legal compliance
Practice proves that the human element is always the most critical link in any information security system. Therefore, organizations must plan budget allocations to deploy periodic training courses for all staff members regarding internal information security policies, rules for the safe and legal use of open-source software libraries, and basic principles in collecting and processing personal data under the latest legal regulations. Proper awareness and a compliant attitude from the product development team constitute a proactive, effective legal risk prevention measure that brings the longest-term economic benefits to the enterprise.
11. Conclusion
Intellectual property asset protection activities for artificial intelligence platform products are not merely an independent, situational legal task, but a complex and tight intersection among technological engineering proficiency, operational governance capacity, and the strategic business vision of the organization. Under the powerful impact of the Intellectual Property Law 2025, the AI Law 2025, and the Personal Data Protection Law simultaneously taking effect from early 2026, economic organizations are compelled to establish rigorous governance discipline right from the initial idea formation stage. Making the legal chain of title transparent, establishing robust information security mechanisms for source code repositories, complying with AI risk classification and content labeling regulations, and proceeding with early protection registrations in core markets represent a mandatory action roadmap. Only when the intellectual property governance system is built and maintained integrally can the enterprise possess sufficient capacity to pass immensely stringent legal due diligence rounds, thereby optimizing corporate valuation and building a sustainable competitive position in merger and acquisition activities as well as the long-term development journey.
12. FAQ: Frequently Asked Questions
12.1. Can software systems and artificial intelligence algorithms be granted patents by the law ?
The legal system fundamentally denies patent grants for pure mathematical models or generalized computer science theories. However, based on the guiding documents in Government Decree 100/2026/ND-CP, if the artificial intelligence system solution is expressed through a core technical element, comprehensively solves a practical technical problem, and generates a specific technical effect (e.g., a hardware design method to automatically compress deep neural network capacity or an encrypted data analysis mechanism on end-user telecom devices), then that technical solution fully meets conditions and is capable of being legally protected under an exclusive patent certificate. Businesses can leverage the three-month fast-track examination mechanism to accelerate this process.
12.2. Are works generated by artificial intelligence protected by copyright ?
Based on detailed regulations in Article 5a of Government Decree 134/2026/ND-CP officially applied from April 2026, copyright for works involving artificial intelligence systems only arises if and only if there is a creative intervention and decisive contribution from humans throughout the work’s formation process. The person directly operating and adjusting the system must bear full legal responsibility for the legality of the output product as well as the input data source. Work categories automatically published by computer systems without specific human creative hallmarks will be excluded from the copyright protection scope of intellectual property law.
12.3. Are businesses allowed to use copyrighted works to train artificial intelligence systems ?
According to the landmark amendments in the Intellectual Property Law 2025, using legally published text structures and data files to train artificial intelligence models is recognized by the legal system to serve non-commercial scientific research and technology development purposes. However, this exploitation behavior must remain within strict control limits, ensuring it does not unreasonably prejudice the economic rights and normal exploitation of the original copyright owner.
12.4. What legal document types are the focus during IP legal due diligence in an AI company M&A ?
During detailed legal due diligence of merger and acquisition transactions, the core documents scrutinized most strictly by the legal team include employment and outsourcing contracts which must contain clear IP transfer clauses; a detailed inventory of all open-source libraries deployed in the system accompanied by license texts; administrative registration dossiers and protection certificates for trademarks and patents; commercial cooperation agreements regarding user data exploitation rights demarcation; system documentary evidence proving the enterprise complies with system risk classification regulations; and operational logs of the access control system per the company’s internal information security policy.
12.5. How is the regulation on labeling content generated by artificial intelligence systems practically implemented ?
Based on Government Decree 142/2026/ND-CP, organizations acting as AI system providers hold a mandatory responsibility to integrate machine-recognizable technical markers (such as metadata structures, digital signatures) inside the generated image, audio, and video files. For organizations directly distributing and deploying applications, when publicizing content that simulates human identity or inaccurately recreates real-life events, the organization must affix clear warning labels on the content display screen, in the title area, content description section, or broadcast announcements via audio signals to prevent severe confusion for the public receiving the information.
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