AI Watermarking
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Two very different things get called AI detection, and the difference decides how much weight either deserves. A third-party detector reads finished text and makes a statistical guess from style, which is why its output is unreliable for any individual page. A watermark is not a guess: the system that generated the content inserts a signal deliberately, at the moment of generation.
The second category is arriving now, under regulatory pressure rather than voluntarily, and readers, regulators and platforms are starting to ask about it.
What is AI watermarking?
AI watermarking embeds a machine-readable signal into generated output so that its origin can later be established. The signal is imperceptible to a reader and, in the designs currently shipping, does not change what the content says.
This matters because the alternative is so weak. The two most-quoted figures about how much of the web is AI-written both come from detectors: Ahrefs sampled 900,000 newly published pages in April 2025 and classified 74.2% as containing at least some AI-generated content,1 and Graphite estimated 42.7% of the references ChatGPT cited in June 2026 were themselves AI-generated.2 Both studies are careful, and both rest on an instrument that misclassifies human writing as machine-written often enough that no individual result from it should be trusted.
Watermarking answers a narrower question more reliably. It cannot tell you whether a page is any good, and as the next sections show, it cannot yet tell you much at all unless you work at the company that applied the mark.
How does SynthID work?
SynthID is Google DeepMind’s watermarking system, and it covers images, video, audio and text.
For text, it works by adjusting the probability scores the model uses to choose each word. Every candidate word is assigned a score based on how likely it is to come next, and SynthID modulates those scores so a pattern is embedded across the output without degrading quality.3 Nothing is added to the text and nothing is removed, which is why the mark survives copying and pasting in a way a visible label never would.
Scale is no longer the constraint. Google reports watermarking over 100 billion images and videos and 60,000 years of audio, with OpenAI, Kakao, ElevenLabs and NVIDIA bringing SynthID to their own generated media.4
Verification is the constraint. The SynthID Detector portal exists but is in limited testing, offered to journalists and media professionals through a waitlist rather than released publicly.3 For most people the only route is to ask Gemini directly, or, in Google’s own products, to ask “Is this made with AI?” through Lens, AI Mode, Circle to Search or Gemini in Chrome. Google expanded that verification to Search in May 2026, with Chrome following.4
What are C2PA Content Credentials?
C2PA Content Credentials take the other approach. Rather than hiding a signal inside the content, they attach cryptographically signed metadata to the file recording who created it and how it has been edited since.
The two are complementary rather than competing. A watermark travels with the pixels or the words and survives stripping the metadata; Content Credentials carry a fuller history but can be removed with the metadata. Google’s C2PA verification reached the Gemini app in May 2026 and was scheduled for Search and Chrome in the months after.4 Anthropic attaches C2PA provenance metadata to .svg, .png and .jpg files Claude generates.5
For a publisher, Content Credentials are the more actionable of the two, because they are something you can apply to your own images rather than something a model applies to its output.
Can you detect AI-generated text?
Not reliably, and not yet through watermarks either.
Anthropic marks all text from supported Claude models with an imperceptible watermark, worldwide rather than only in the EU. Two limits in Anthropic’s own documentation set the ceiling on what any of this proves.5
A mark does not prove the content was written by AI. Anthropic states a detected mark means content “may have been processed by Claude”, which covers proofreading, translating or summarising something a person wrote.
The absence of a mark proves nothing at all. Heavy editing, format conversion, or output from an older model will not carry a detectable mark.
Detection tooling for third parties is promised but unpublished. Anthropic says it will “share details on detection mechanisms in forthcoming technical documentation”, and SynthID’s detector remains gated. So provenance marking will eventually make origin more knowable than a detector ever could, and today it changes nothing you can check.
It will also never produce a clean split between human and machine writing, because most content is neither. Ahrefs’ own breakdown makes the point: of those 900,000 pages, only 2.5% were classified as pure AI and 25.8% as pure human, with the large majority a mixture.1
Do you have to label AI-generated content?
If you publish in or into the EU, there is a rule, and there is an exemption that most editorial workflows already satisfy.
Article 50 of the EU AI Act, which applies from 2 August 2026, places an obligation on deployers, not only on the companies building the models. A deployer publishing AI-generated text to inform the public on matters of public interest must disclose that the content was artificially generated. The exemption is the part worth reading closely, because it is written in the language of ordinary publishing:6
where the AI-generated content has undergone a process of human review or editorial control and where a natural or legal person holds editorial responsibility for the publication of the content
A human review step with someone accountable for what goes out removes the disclosure requirement. That is the same workflow AI content risks and E-E-A-T already argue for on quality grounds, now with a second reason attached.
Whether it reaches a UK publisher is genuinely unsettled. Article 2 applies the Regulation to deployers “that have their place of establishment or are located within the Union”, which excludes a UK business, but extends it to third-country deployers “where the output produced by the AI system is used in the Union”.7 Whether a UK website read by EU visitors counts as output used in the Union is an interpretation question that has not been tested. Treat it as a reason to keep the review layer documented rather than as a settled obligation, and take legal advice if the answer would change what you publish.
Does AI watermarking affect search rankings?
No platform has said so.
Google’s announcement of SynthID and C2PA verification in Search describes a capability for users checking an image, not a signal in ranking, and says nothing about search results being affected.4 Nothing in Google’s guidance on AI-generated content ties provenance marks to ranking either. The position across generative engine optimisation applies unchanged: content is assessed on quality, usefulness and evidence, not on how it was produced.
The plausible near-term consequence is a reader-facing one rather than an algorithmic one. If verification becomes a normal thing to do inside Search and Chrome, an image on your site that returns “made with AI” is answering a question in front of the reader, at the moment they are deciding whether to trust you. That is a presentation and disclosure decision, not a ranking one.
What to do now
For most publishers, three things, none of them expensive.
- Keep the human review layer, and record who owns it. A named author, a documented editorial process and someone holding editorial responsibility is what the Article 50 exemption describes. It is also what earns citations.
- Disclose AI-generated imagery in the caption. A one-line credit costs nothing, matches what verification tools will report anyway, and reads better coming from you than from a right-click.
- Do not buy a detector to police your own writers. Detectors misclassify human writing, and a false positive against a real author is a worse outcome than the problem it was bought to solve.
What not to do: nothing here justifies engineering work. There is no markup to add, no header to set, and no confirmed benefit to chase.
Frequently asked questions
Can Google tell if my content was written by AI?
Not from a watermark in most cases, because the marks currently shipping are applied by the model provider and the detection tooling is not public. Google’s stated position is that it rewards helpful, reliable content regardless of how it is produced, and penalises content made primarily to manipulate rankings, also regardless of how it is produced.
Does a SynthID watermark survive editing?
For images, video and audio Google says the mark survives cropping, filters, frame-rate changes, lossy compression, added noise and speed changes.3 For text the resilience is not documented, and Anthropic notes that heavy editing or format conversion can remove a text mark entirely.5
Should I add Content Credentials to my images?
It is reasonable for original photography and for AI-generated illustrations where you want the provenance to travel with the file. It has no confirmed search benefit. Treat it as a transparency measure rather than an SEO one.
Is a watermark the same as an AI content detector?
No, and the difference is the point. A detector inspects finished text and infers from style, which is unreliable per page. A watermark is inserted deliberately by the system that generated the content. The detector is a guess; the watermark is a record, once anyone outside the company can read it.
Footnotes
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What percentage of new content is AI-generated? — Ahrefs ↩ ↩2
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AI search collapse: AI responses collapse when AI retrieves its own generations — Graphite ↩
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Making it easier to understand how content was created and edited — Google. Published 19 May 2026. ↩ ↩2 ↩3 ↩4
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Article 50: Transparency Obligations for Providers and Deployers of Certain AI Systems — EU Artificial Intelligence Act. Chapter IV applies from 2 August 2026. ↩
