Artificial intelligence can generate a credible image, text, voice, or even a video in just a few seconds. What we see on the screen, however, is not necessarily all that the file contains. In fact, more and more AI systems are embedding watermarks—markers that make it possible to recognize, or at least reconstruct, the artificial origin of a piece of content.
You don't necessarily have to picture the classic logo placed in the corner of a photograph. The most interesting AI watermarks are invisible and can be embedded directly into the pixels of an image, the characteristics of an audio file, the frames of a video, or even the way the words in a text are generated.
For anyone who uses artificial intelligence in business, communications, or content creation, knowing that these tools exist and understanding how they work is now almost as important as knowing how to write a good prompt.
A watermark does not necessarily have to be visible
The concept of a watermark has existed long before the advent of artificial intelligence. In the digital world, we are most familiar with its simplest form: text, a logo, or a symbol superimposed on an image to indicate its source.
With AI, the concept has become significantly more sophisticated. A watermark can be imperceptible to a person yet recognizable to a system designed to detect it.
Google DeepMind, for example, uses SynthID, a technology designed to embed digital watermarks in content generated by artificial intelligence. The system is applied to images, videos, audio, and text, and the watermark is not meant to be visible or audible to the user.
In the case of images, the signal is embedded directly into the pixels and is designed to withstand even some common modifications, such as compression, filters, or changes in brightness. This is an important point: removing what we see with the naked eye does not necessarily mean removing every technical trace present in the content.
Even a text can have a watermark
It's pretty intuitive when it comes to images. Not so much when it comes to text.
A document does not contain pixels in which to hide a signal; instead, language models operate using tokens and probabilities. When they generate a sentence, they progressively choose which tokens to use from among various possibilities.
SynthID for text intervenes precisely in this process, slightly modifying the probability distribution during generation. The result remains natural to the reader, while the set of choices made by the model creates a pattern that can subsequently be analyzed.
This system, however, has its limitations. Google itself specifies that it works best on longer, more varied texts and that extensive rewriting or translation can significantly reduce the reliability of the detection. We are therefore not dealing with some sort of indelible signature capable of proving, under any circumstances, that a text was written by an AI.
This is an important distinction, in part because watermarks and AI detectors are not the same thing. A detector generally attempts to determine whether a piece of content exhibits characteristics consistent with artificial generation. A watermark, on the other hand, is intentionally embedded during the creation process and subsequently searched for using a compatible system.
Watermarks aren't the only thing out there
There is also a second level to be aware of: metadata and information about the file's origin.
One of the most important standards in this field is C2PA, which forms the basis of what are known as Content Credentials. The goal is to associate content with verifiable information about its origin and the changes it has undergone over time, using cryptographically signed manifests. Content Credentials can therefore also indicate whether artificial intelligence was used in the creation or modification of a piece of content.
In practice, the future of identifying synthetic content will likely not depend on a single method. Invisible watermarks, metadata, digital signatures, and provenance systems can coexist and provide different types of information.
And that is precisely why downloading a file generated by AI and seeing a normal JPEG or PNG image does not automatically mean that you are looking at a file that is completely devoid of information about its origin.
Why You Should Think It Through Before Posting
For personal use, this may seem like a minor detail. In a business context, however, it makes a big difference.
An image created for an advertising campaign, text intended for the corporate website, or a video posted on social media becomes official company content. Before publication, it is therefore important to know which tool was used to create it, what information the file contains, and what markers—if any—are applied by the service used.
This does not mean that every watermark must necessarily be removed. In some contexts, the stated source may be useful or required by the platform; in other cases, it may be necessary to edit the file before publication, always in accordance with the tool’s terms of use and applicable rules.
The point is not to find out later.
Watermark AI and Google: Be careful not to confuse the two
This topic becomes particularly interesting when we talk about content intended for the web and search engine optimization.
Google does not state that a piece of text is penalized simply because it was written using artificial intelligence or because it contains a specific watermark. Instead, in its anti-spam guidelines, it focuses on content produced on a large scale with the primary purpose of manipulating search rankings, especially when such content lacks originality and offers no real value to users. Among the examples cited is the use of generative AI to produce large quantities of pages without adding value.
It is therefore important not to turn this issue into a simple hunt for AI-generated content. Watermarks, editorial quality, and SEO are interrelated aspects of a digital strategy, but they are not synonymous.
On this point, it’s also worth taking a closer look at the topic of Google penalties and AI-generated content, which we covered in a dedicated article [INSERT LINK TO CHIARA’S ARTICLE].
Removing AI watermarks isn't always the solution
The most obvious temptation might be this: if a piece of content contains an AI marker, just remove it before publishing it.
It's not always that simple, and, above all, that shouldn't be the starting point.
Some watermarks are visible and can be managed using the tools provided by the service that generated the content. Others are embedded in the file and specifically designed to survive common transformations. Additional information may be stored in metadata or through provenance systems.
Before taking any action, it is therefore important to understand what type of marker you are dealing with, why it is there, and what the requirements are for the platform you are using.
In a professional setting, the most useful question isn't "How do I erase all traces of AI?", but "Is this content ready to be published?"
A technical detail that will become less and less minor
The more realistic AI-generated content becomes, the greater the need to be able to trace its origin.
For companies, agencies, and professionals, this means adding an extra step to the normal production process. It’s not enough to simply check that a photo is good, that a text is correct, or that a video works. We also need to understand the file we’re publishing, the tool that created it, and any information it contains.
AI watermarks are neither something to fear nor a flaw to be automatically removed. They are an increasingly common component of synthetic content. Ignoring them, however, means using new tools while continuing to think as if they produced files that are exactly the same as before.
And this is precisely where a problem can arise for a company.
