What is AI-Generated Content? Is it necessary to label content created by AI?

Generative AI is becoming a familiar component of media, marketing, and business operations. From advertising visuals, videos, and audio to written text, diverse types of content can now be generated or assisted by AI within a short time. However, as AI-generated outputs become increasingly difficult to distinguish from human-created content, transparency and the ability to identify content origins have become critical issues. In particular, effective March 1, 2026, Vietnam’s Law on Artificial Intelligence No. 134/2025/QH15 has come into force, setting forth specific regulations regarding transparency, identification of AI interactions, and the labeling of AI-generated content.

What Is AI-Generated Content?

AI-generated content refers to digital materials created entirely from scratch or with significant involvement from artificial intelligence systems. Depending on the specific tool used, AI can produce text, images, videos, audio, or other digital formats. For instance, enterprises can leverage AI to draft advertising copy, generate product illustration visuals, or produce voiceovers for introductory videos.

A distinction must be drawn between AI-generated content and content where humans merely utilize AI for editing assistance. Not all content involving AI exhibits the same degree of “generation.” For businesses, the crucial step is to determine the extent of AI’s involvement in the content creation workflow and whether the final output falls under mandatory requirements for transparency, identification, or labeling under applicable regulations.

Why is transparency in AI-Generated content necessary?

As AI-generated images, videos, and audio grow increasingly realistic, audiences may find it challenging to distinguish between real-world media and synthetic content. Without proper transparency mechanisms, AI can be exploited to produce deceptive information, simulate real individuals, or manipulate perception.

This is also a core issue addressed by the 2025 Law on Artificial Intelligence. According to announcements published on the Government Portal, the Law establishes foundational principles of transparency, accountability, and human oversight in AI-related activities. Transparency obligations include requirements to identify interactions with AI systems and label content generated by artificial intelligence.

Therefore, labeling is not merely a technical requirement. It also serves as a mechanism to inform users that they are consuming content with AI involvement, thereby providing them with a factual basis to evaluate the information appropriately.

Must all AI-Generated content be labeled?

This is a critical consideration for businesses. One should not simply assume that using AI automatically mandates an identical label for every piece of content. Specific obligations depend on the classification of the AI system, the type of content created, and the regulatory provisions applicable to each scenario.

The Law on Artificial Intelligence establishes a risk-based management framework, categorizing systems into high, medium, and low risk. Simultaneously, the Law outlines distinct transparency requirements for AI operations and AI-generated outputs.

For businesses, the safest approach is not to wait until content is publicly released to conduct compliance checks. Right from designing internal AI workflows, organizations should identify which categories of content contain AI elements, evaluate the degree of AI involvement, and determine which instances mandate notification or labeling under current regulations.

In particular, where content has the potential to lead viewers to confuse real individuals with AI-generated avatars, or real-world events with synthetic simulations, transparency requirements must be strictly prioritized.

What does labeling AI content mean for businesses?

For enterprises, AI transparency primarily serves to safeguard customer trust. In marketing and communications, deploying an AI-generated image or video does not inherently diminish brand equity. On the contrary, proactive transparency demonstrates a responsible approach to technological adoption.

Labeling also mitigates the risk of audiences misunderstanding the origin of content. This is especially vital for media utilizing images, videos, or audio that simulate real individuals. If not properly governed, AI content can generate unintended misconceptions, leading to reputational, data, or legal liabilities.

Furthermore, the Law on Artificial Intelligence strictly prohibits concealing information subject to mandatory public disclosure, transparency, or explanation, as well as erasing or falsifying mandatory information, labels, or warnings within AI-related activities.

What should businesses prepare when using AI-generated content?

Rather than treating labeling as an isolated task, businesses should integrate AI transparency into their broader content governance framework. When utilizing AI to generate images, videos, audio, or text, the responsible department must identify the input data sources, tools deployed, creation objectives, and the level of AI involvement.

Once content is produced, a human review stage is essential prior to publication. The reviewer should not only check for factual inaccuracies but also assess whether the content could cause confusion regarding real people, actual events, or information provenance. For higher-risk content, enterprises should implement rigorous approval workflows and archive necessary documentation to support accountability audits when required.

This fully aligns with the human-centric focus mandated by the Law on Artificial Intelligence. The Law requires the maintenance of human oversight, intervention, and control mechanisms over AI systems, particularly in scenarios involving significant societal or operational impact.

AI-Generated content and the challenge of responsible AI adoption

The evolution of generative AI is blurring the line between human-made and machine-generated content. Consequently, AI-generated content is not merely a matter of technical capability—it is intrinsically tied to transparency, accountability, and institutional trust.

For enterprises, labeling AI content should be regarded as an integral component of a responsible AI deployment strategy rather than a burdensome procedural hurdle. By maintaining transparency in AI usage, governing input data, and upholding human-in-the-loop oversight, organizations can effectively harness the power of technology while mitigating unnecessary risks.

With the 2025 Law on Artificial Intelligence taking effect on March 1, 2026, businesses should proactively review their production pipelines and AI content workflows to guarantee full compliance with active regulatory standards.

AI delivers sustainable value only when deployed alongside the right people, structured workflows, and robust control mechanisms. BPO.MP partners with enterprises in training and practical AI adoption, empowering teams to accurately understand the technology, construct compliant AI workflows, and systematically integrate AI into operations efficiently and safely.