What the New AI Disclosure Requirement Means for Your Website

Labeling AI Content: What Will Actually Apply Starting in August 2026

“Do we now have to include a note with every blog image stating that it was created using AI?” This question has come up repeatedly in recent weeks, ever since the new labeling requirement for AI-generated content officially took effect on August 2, 2026. There was a lot of speculation about it beforehand, but far less concrete discussion about what this actually means for your company going forward.

Incidentally, this isn’t a standalone new law. The labeling requirement is set forth in Article 50 of the European AI Regulation—that is, the same AI Act that has been under discussion for some time and which we’ve already covered in more detail here on the blog. What’s new is that this requirement is now actually in effect, backed by specific implementation guidelines and a few exceptions that often get overlooked in the public debate.

This post explains what has actually been in effect since August 2, who is subject to the requirement and who is not, and what this means in concrete terms for the various types of content on your website.

A quick note to start with: This post is not a substitute for legal advice. For a definitive assessment of your specific case, we recommend consulting a lawyer who specializes in IT and data protection law.

What Article 50 of the AI Regulation Actually Requires

Article 50 essentially distinguishes between two different obligations that are often lumped together. The first concerns interactions with people: Anyone who uses a chatbot or virtual assistant on their own website must make it clearly evident that the visitor is currently speaking with an AI system, not a human. A discreet notice in the chat window is generally sufficient for this purpose, as long as it is actually noticed and not hidden in a footnote.

The second requirement concerns the generated content itself: text, images, and audio and video content created primarily by AI must be labeled as such in a machine-readable format and made recognizable. So-called “deepfakes”—AI-generated images or videos of real people or events that appear deceptively real—are subject to particularly strict regulations. These must also be clearly labeled in a way that is recognizable to humans, not just machine-readable in the background.

Both requirements have been in effect since August 2, 2026. However, for providers of AI systems that were already on the market prior to that date, there is a separate four-month transition period ending on December 2, 2026, specifically for the technical implementation of content labeling.

Who is subject to this requirement—and, more importantly, who is not

One point that often causes confusion in initial consultations: The labeling requirement primarily applies to providers and operators of AI systems, not automatically to every company that occasionally uses an AI tool for text or images. Companies that use AI tools such as image generators or writing assistants generally fall under the category of “operator” and are therefore subject to the corresponding obligation to label the content they generate.

However, there is one important exception that is particularly relevant to texts: If an AI-generated text has been editorially reviewed by a human and a natural or legal person bears editorial responsibility for the published content, the labeling requirement does not apply to that text. This exception was originally formulated primarily with journalists and law firms in mind, but it generally applies to any person or organization that can demonstrate that it assumes this editorial responsibility.

For most corporate blogs, this means in practice: A blog post created with AI assistance but proofread, reviewed, and approved by a human before publication does not necessarily have to be labeled as AI-generated, as long as it is clear who is editorially responsible for it. The situation is different for images and videos; in those cases, the exception does not apply to the same extent because the regulation is more tailored to text.

The Code of Practice: What the Labeling Should Look Like from a Technical Perspective

On June 10, 2026, a so-called Code of Practice was published, which translates the rather abstract legal requirements of Article 50 into a concrete technical procedure. The guideline recommends a multi-layered approach consisting of three components: metadata embedded within the file itself, an invisible technical watermark that is intended to remain detectable even after the content has been edited, and logging by service providers that allows content to be traced back in case of doubt.

The reason for this three-pronged approach is simple: each individual method has a weakness. Metadata can easily be lost when a file is saved or converted. An invisible watermark can be damaged by extensive image editing. Simply logging the data with the provider is of little help if no one from outside can access it. Only the combination of all three methods makes the marking reasonably robust.

For you as a business, this means one thing above all else: With most major AI tools, a significant portion of this technical labeling now occurs automatically in the background, because the providers themselves are required to comply with the code. The actual task on your end is rarely to add technical watermarks yourself, but rather to include visible, human-readable notices where it makes sense and is required by law.

What this means specifically for the content on your website

When applied to the day-to-day operations of a corporate website, the situation can be divided into three categories. First: AI-generated blog posts that were reviewed by a human before publication. In most cases, the editorial exception applies here; explicit labeling is generally not legally required, but may still be advisable for transparency reasons.

Second: AI-generated images, such as blog illustrations or background graphics. The rules are stricter here; a recognizable label is generally required, at least in the form of a discreet note in the image caption or in the file’s metadata. Third: Chatbots or AI-powered customer service assistants on your own website. Here, the disclosure requirement is unambiguous: a clearly visible notice at the beginning of the conversation is mandatory, regardless of how good or human-like the chatbot appears.

What is often overlooked in this list is that even pure translations or minor linguistic revisions of a text written by a human using AI are generally not subject to the labeling requirement, because the actual content remains of human origin. The line is therefore drawn not so much by whether an AI tool was used in the process at all, but rather by who bears responsibility for the content of the result.

At first glance, this distinction may seem somewhat subtle, but in practice it is actually the key factor in determining the legal classification. A text that is published directly and entirely by AI without any human review differs fundamentally, from a legal standpoint, from a text that is created with AI support but for which a human ultimately takes responsibility. Those who clearly document this distinction in their own editorial process will be in a much stronger position in case of doubt.

A real-world example

A client in the education sector had already been using AI tools in several areas of their daily work: for initial drafts of blog posts, for illustrations on topic pages, and for a simple chatbot to schedule appointments. After the announcement of the labeling requirement, there was a brief period of genuine uncertainty within the team as to whether all existing content would now have to be revised.

After a structured review, a much more reassuring picture emerged. The blog posts had already been editorially reviewed and approved by the marketing management prior to publication, so the exception applied. For the illustrations, we added a small, unobtrusive note in the caption area. In the end, the only real need for action concerned the chatbot, which had previously given no indication of its AI nature. A single, clearly worded introductory sentence at the beginning of each conversation resolved the issue within a few minutes. What had initially been a major concern turned out to be a manageable afternoon’s work, involving three small, specific adjustments and a clear, documented chain of responsibility for future content.

Consequences of Violations

Violations of the transparency obligations set forth in Article 50 are penalized under the general system of administrative fines established by the AI Regulation. Depending on the severity and nature of the violation, potential fines can range up to 15 million euros or three percent of global annual revenue, whichever is higher. By way of comparison, the penalty range is even higher for the most serious violations of the AI Regulation as a whole, such as prohibited AI practices.

For the vast majority of companies that are sincerely trying to comply with the regulations, such maximum penalties are a theoretical scenario. In practice, the initial focus is on notices and deadlines for rectification, not on immediate maximum penalties for a single missed label. However, this does not relieve companies of their obligation to address the issue, precisely because the relevant regulatory authorities are only just beginning to develop their own audit practices for this still relatively new set of regulations.

Why the Four-Month Deadline Is Often Misunderstood

One detail consistently causes confusion in discussions: the separate transition period lasting until December 2, 2026. Many interpret this to mean that the entire labeling requirement does not take effect until December, but that is not entirely correct. These four months apply exclusively to providers of AI systems that were already on the market before August 2, 2026, and specifically concern the technical implementation of automated content labeling at the system level.

For you as users of such systems, this deadline does little to change the fundamental obligation to make AI-generated content identifiable. So anyone expecting new obligations to suddenly arise in December is misunderstanding the actual logic behind the system. The deadline primarily applies to the providers of the tools themselves, not to the companies that use these tools in their day-to-day operations. Therefore, anyone who is already publishing AI-generated content should not rely on this deadline as a convenient excuse to delay fulfilling their own responsibilities.

The Difference Between Legal Obligation and Best Practice

One point worth clearly distinguishing: what is required by law, and what may still be advisable purely for the sake of trustworthiness. Even in cases where the editorial exception applies and disclosure is not legally required, transparent, open communication about the use of AI tools can build more trust in the long run than strictly exploiting every legal loophole.

We are now observing a clear trend in this direction across several client projects: Companies that openly communicate where AI is used to provide support—and where, ultimately, a human always makes the final decision—often come across as more credible to their target audience than companies that remain completely silent on this topic. This openness cannot be enforced by law, but it often pays off in practice—especially at a time when many people are already becoming increasingly sensitive to the issue of AI-generated content.

What you should specifically review over the next few weeks

Instead of resorting to knee-jerk reactions, it’s worth taking a structured, calm look at your own website. First, make a list of all content where AI tools played a role in the creation process—from blog posts and images to automated response systems. This inventory alone often provides surprising clarity about the actual scope of AI use within your company—which is usually much smaller than you might have previously assumed.

Next, for each of these content types, it is worth asking whether a human editorial review actually takes place and whether this responsibility is clearly assigned to a specific person or department within the company. This last point in particular is often overlooked: It is not enough that someone, at some point, glanced over a text. Responsibility should be clearly identifiable—and, if in doubt, documented—so that, in the event of a dispute, it is clear who actually performed this editorial role.

Conclusion: No reason to panic, but a good time to take stock

The requirement to label AI-generated content is real and has been in effect since August 2, 2026, but it impacts most companies far less severely than the initial headlines might suggest. Companies that editorially review AI-generated text, discreetly label AI-generated images, and clearly identify chatbots as such can meet the key requirements with manageable effort. A calm assessment of the situation generally yields better results than frantic, knee-jerk reactions—especially since the authorities’ review practices will only begin to settle into a routine in the coming months.

Related: AI Agents for Small and Medium-Sized Businesses in 2026: What Runs Autonomously, What Doesn’t, and What Costs Ten Slots a Month, and How to Show Up in ChatGPT and Perplexity Responses · Services: AI Consulting and Implementation

Not sure where your website stands when it comes to AI labeling?

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