What Is a Deepfake? Why Do Businesses Need to Care About Deepfakes?

The rapid advancement of generative artificial intelligence is making the creation of images, videos, and audio easier than ever. Among these applications, deepfakes have garnered significant attention due to their ability to generate or alter content simulating real people and events with a high degree of realism. While deepfakes can serve creative, entertainment, or research purposes, they can also be exploited for identity theft, fraud, spreading misinformation, and damaging the reputation of individuals and organizations. For businesses, properly understanding what deepfakes are and the risks they pose has become a critical component of safe AI adoption.

What is a Deepfake?

Deepfake is a term used to describe visual, audio, or video content created or modified using AI techniques to simulate a real person or event. The technology can analyze image data, facial features, voices, or physical movements to generate synthetic content that closely resembles reality. According to the U.S. National Institute of Standards and Technology (NIST), deepfakes fall under the category of synthetic or technologically manipulated digital media; however, not all modified or synthetic content carries malicious intent. Proper assessment requires evaluating the content itself, its context, and its intended purpose.

Deepfakes are often mentioned alongside AI-generated content, but these two concepts are not entirely identical. Generative AI can produce text, images, audio, video, and many other content formats. In contrast, deepfakes typically emphasize the simulation or manipulation of content related to a real person or event. For example, an AI-generated image depicting a completely fictional character is not necessarily a deepfake; conversely, a video simulating a real person speaking or taking an action they never actually did can be considered a deepfake.

Why have Deepfakes become an issue businesses must pay attention to?

One of the most notable risks is identity impersonation. When AI can simulate an individual’s likeness or voice, businesses may encounter content that misleads recipients into believing that executives, employees, clients, or partners have genuinely made a statement or issued a request. Regulatory authorities and international research organizations have warned that synthetic content can be exploited for impersonation, fraud, and intellectual property infringement.

Deepfakes can also directly impact brand reputation and trust. A convincing fraudulent video or audio recording can spread rapidly across social media platforms before a business has time to verify it. Even if the content is subsequently confirmed to be fake, the enterprise may still need to expend substantial resources to verify facts, issue responses, and restore customer confidence. NIST also notes that the proliferation of synthetic media can affect information integrity and trust within digital environments.

Another critical issue involves personal data and individual rights. Generating content that simulates a specific person often involves using their likeness, voice, or other identifying data. Consequently, businesses should not only look at the end product, but must also examine the underlying data sources, data usage rights, and the core purpose of content creation from the outset.

Are Deepfakes banned in Vietnam?

This question requires precise understanding. Deepfakes should not be equated with an activity that is universally prohibited. The legal framework focuses specifically on instances where AI and manipulated content are used to commit prohibited acts or cause serious harm to legitimate rights and interests.

The Law on Artificial Intelligence No. 134/2025/QH15, effective March 1, 2026, strictly prohibits the use of deceptive elements or the AI simulation of real persons or events to intentionally and systematically deceive or manipulate human perception and behavior, causing serious harm to legitimate rights and interests. The Law also strictly prohibits creating or disseminating fraudulent content capable of severely endangering national security, public order, and social safety.

Furthermore, the Law on Cybersecurity No. 116/2025/QH15, effective July 1, 2026, has incorporated provisions strictly prohibiting the unlawful use of AI or emerging technologies to forge another person’s video, image, or voice. This provides a direct legal basis for addressing cases that exploit deepfakes for fraud or violations of honor and dignity.

Therefore, rather than simply asking “Are deepfakes banned?”, businesses should ask: “What is the purpose of this AI-generated content, whose data is being used, and what potential impact could it cause?”

Where can businesses encounter deepfake risks?

Deepfakes can surface across various business functions, from media and marketing to internal communications and customer service. Forged content impersonating leadership or brand ambassadors can generate misleading information about the company. In digital workplace environments, employees may also face challenges verifying whether an incoming call, video, or audio recording genuinely originates from the stated sender.

Notably, detecting deepfakes with the naked eye is becoming increasingly difficult. NIST continues to research and evaluate deepfake detection systems, pointing out that the performance of detection tools can vary significantly between controlled testing environments and real-world conditions. This highlights that businesses should not rely entirely on a single “AI detection” tool; instead, they must combine technology with rigorous information verification workflows and human oversight.

What should businesses do in response to deepfakes?

A sound approach involves building an AI content and data governance framework rather than merely searching for deepfake detection software. When deploying AI-generated images, videos, or voices, businesses need to define data sources, intended use cases, data authorization rights, and designated personnel responsible for review before publication. For content that carries a risk of misleading customers regarding identity or actual events, inspection and verification become even more crucial.

In parallel, employees must be equipped with baseline knowledge concerning AI and synthetic media. Beyond the IT department, teams across marketing, communications, human resources, customer service, and management can all become recipients or users of AI-generated content. A straightforward workflow—such as verifying the source, inspecting content, confirming the sender, and securing approval before taking action—can substantially mitigate the risk of making decisions based on fabricated content.

Deepfakes and the challenge of responsible AI adoption

Deepfakes clearly demonstrate that AI brings both opportunities and risks. Technology that simulates images, videos, and voices can empower diverse creative endeavors; however, when leveraged to impersonate, deceive, or inflict harm, its consequences extend well beyond the technical sphere.

In the context of Vietnam enacting its Law on Artificial Intelligence starting in 2026 and updating its Cybersecurity Law regarding AI misuse, enterprises must proactively cultivate capabilities for safe and responsible AI deployment.

AI is not a technology to be avoided, but it must be utilized alongside knowledge, structured workflows, and human control. This forms the foundation for businesses to harness AI effectively while safeguarding data, brand reputation, and stakeholder interests.

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