For the last two years, we’ve been asking the wrong question about AI.
The conversation has largely centered around whether AI should be used to create content. But the reality is that AI is now embedded into how many of us work. It’s helping us research, brainstorm, organize ideas, edit drafts, and increase productivity. That genie isn’t going back into the bottle.
How do we preserve authenticity, trust, and original thinking in a world where anyone can generate unlimited content with a single prompt?
Anthropic recently took an important step toward answering that question by announcing invisible watermarking for content generated by Claude.
Their technology embeds machine readable signals into AI generated text, making it possible to identify content that originated from Claude without affecting the reading experience.
At first glance, this may seem like a small technical update.
I believe it’s much bigger than that.
Before we dive in, let’s take a quick look back at the history of watermarks:
The history of watermarking is fascinating because it has always been about one thing: trust.
Every major evolution in watermarking has emerged when society needed a better way to verify authenticity, ownership, or provenance. AI watermarking is simply the latest chapter in a story that began more than 700 years ago.
The First Watermarks (13th Century)
Watermarking originated in Italy during the late 1200s. Papermakers would sew thin wire designs onto the molds used to make paper. As the paper dried, it became slightly thinner where the wire sat, creating a faint image visible only when held to the light.
These marks served several purposes:
- Identified the paper mill that produced the paper
- Signaled quality
- Helped distinguish authentic paper from counterfeit products
In many ways, they functioned like today’s brand logos or digital certificates.
Government Documents and Currency
By the 18th and 19th centuries, watermarks became essential security features for governments.
Paper currency, passports, stock certificates, legal documents, and postage stamps all adopted increasingly sophisticated watermarks.
The goal wasn’t branding anymore, it was fraud prevention.
If someone could reproduce the printed design but not the watermark, the document could still be identified as fake.
Even today, nearly every major currency in the world uses watermarks.
Photography and Copyright (1990s)
As digital photography exploded in the 1990s, creators faced a new problem.
Anyone could copy an image perfectly.
Visible watermarks like…
- Logos
- Signatures
- Semi transparent text
…all became common.
Getty Images arguably made this practice famous, placing large visible watermarks across preview images to discourage unauthorized use.
This era shifted watermarking toward protecting intellectual property.
Invisible Digital Watermarking (Late 1990s–2000s)
Researchers soon realized visible watermarks weren’t enough.
Invisible digital watermarks embed information directly into files by making tiny changes that humans can’t perceive but software can detect.
This technology became widely used for:
- Movies
- Music
- Television broadcasts
- Images
- PDF documents
Studios used it to trace leaked movies back to the original recipient.
Publishers used it to identify unauthorized copies.
Streaming services quietly embedded unique identifiers into distributed media.
The purpose evolved from preventing copying to tracking provenance.
Blockchain and Provenance (2015–Present)
With NFTs and blockchain came another interpretation of watermarking.
Instead of embedding information inside the file, creators began attaching permanent ownership records on decentralized ledgers.
While controversial in some applications, the broader concept reinforced an important trend:
People increasingly care not just about what content is, but where it came from.
AI Watermarking (2023–Present)
Now we’re entering perhaps the most interesting phase.
Companies like Anthropic, Google, OpenAI, and others are exploring ways to indicate that AI systems participated in content creation.
Unlike older watermarks, these aren’t primarily about copyright.
They’re about provenance and transparency.
Questions they’re trying to answer include:
- Was this written by a human?
- Was AI involved?
- Which model produced it?
- Has the content been modified?
Anthropic’s approach is particularly notable because it uses machine readable markers that don’t affect the reading experience but can help identify text generated by Claude supported models.
The Bigger Pattern
What’s interesting is that the purpose of watermarking has evolved alongside society’s biggest trust problems.
| Era | Problem | Watermark Solution |
| 1200s | Who made this paper? | Identify the paper mill |
| 1800s | Is this currency authentic? | Prevent counterfeiting |
| 1990s | Who owns this image? | Protect copyright |
| 2000s | Who leaked this file? | Trace distribution |
| Today | Where did this content come from? | Verify AI provenance |
Why This Matters
I don’t think AI watermarking is really about AI.
It’s about restoring trust in information.
Every time communication technology has made copying easier, the printing press, photography, the internet, and now generative AI, we’ve invented new ways to prove authenticity.
Watermarks have always been society’s answer to the same fundamental question:
“Can I trust where this came from?”
AI has simply made that question more important than ever.
BUT…
…how do we preserve authenticity, trust, and original thinking in a world where anyone can generate unlimited content with a single prompt?
Anthropic recently took an important step toward answering that question by announcing invisible watermarking for content generated by Claude. Their technology embeds machine readable signals into AI generated text, making it possible to identify content that originated from Claude without affecting the reading experience.
At first glance, this may seem like a small technical update.
I believe it’s much bigger than that.
We’re Entering the Next Phase of AI
The first wave of AI was about creation.
The next wave will be about provenance.
Where did this information come from?
Who actually created it?
How much human thought went into it?
Those questions are becoming increasingly important as millions of AI generated articles, emails, social posts, and websites flood the internet every day.
The internet doesn’t have a content shortage.
It has a credibility shortage.
A Cleaner Internet Starts with Better Signals
One of the greatest challenges AI has created is the explosion of low value content.
Entire websites are being generated in minutes. Social feeds are filled with recycled ideas. Search engines have become increasingly crowded with articles that say the same thing using slightly different words.
The result is more noise than insight.
Invisible watermarking has the potential to become one of the mechanisms that helps restore balance.
Not because AI generated content is inherently bad, it isn’t, but because transparency creates accountability.
When we know where content originated, we can make more informed decisions about how much trust to place in it.
That benefits everyone.
Consumers become more informed.
Publishers become more accountable.
Search engines gain another signal to evaluate quality.
And businesses that continue investing in original expertise have an opportunity to stand out.
Original Thinking Just Became More Valuable
Ironically, I believe AI watermarking makes human creativity even more valuable.
When everyone has access to the same language models, information quickly becomes commoditized.
Facts become easy.
Summaries become easy.
Generic advice becomes easy.
What doesn’t become easy is perspective.
Experience.
Judgment.
Original research.
Contrarian thinking.
The unique insights that come from years of solving real business problems.
Those are the assets AI can’t simply manufacture.
In many ways, watermarking shifts the competitive advantage away from who can produce the most content and toward who has something genuinely worth saying.
That’s a healthy shift for the entire digital ecosystem.
What This Could Mean for Search
As the CEO of a digital marketing agency, I naturally think about search.
While Anthropic’s watermark isn’t designed specifically for SEO, it’s difficult not to imagine where this technology could lead.
Search engines have spent decades trying to identify quality content.
Now imagine a future where they have stronger signals around content provenance in addition to authority, expertise, backlinks, user engagement, and behavioral data.
I don’t believe AI generated content should be penalized simply because AI was involved.
In fact, AI can dramatically improve productivity and help great writers communicate more effectively.
But I do believe search engines will increasingly reward content that demonstrates genuine expertise, firsthand experience, unique research, and original thinking.
Watermarking could become one piece of a much larger trust framework.
This Isn’t About Catching People
One misconception is that watermarking exists to “catch” people using AI.
I don’t think that’s the point.
Most professionals today use AI in some capacity.
The better objective is creating transparency while encouraging responsible use.
AI should be a collaborator, not a substitute for expertise.
The best content of the future will almost certainly involve AI.
It will also involve humans asking better questions, applying better judgment, and adding insights that no model could generate on its own.
The Long Term Opportunity
I think this announcement represents something much larger than a watermark.
It’s an early glimpse into an internet where digital provenance becomes standard.
Imagine a future where:
- Readers can better understand how content was created.
- Businesses can more easily distinguish original expertise from mass produced content.
- Publishers can demonstrate authenticity.
- AI companies compete not only on model performance but also on transparency and responsibility.
- Search engines become better at surfacing genuinely valuable information instead of simply rewarding volume.
That future benefits everyone who creates meaningful work.
The Bottom Line
For years we’ve measured content by quantity.
How many articles.
How many blog posts.
How many social updates.
AI has made quantity nearly free.
The next competitive advantage won’t be producing more.
It will be producing better.
The businesses that win won’t necessarily be the ones using the most AI.
They’ll be the ones using AI to amplify authentic expertise rather than replace it.
If watermarking helps move the internet in that direction, even incrementally, I believe it’s one of the most important developments we’ve seen in AI this year.
The future of content isn’t human versus AI.
It’s transparent AI empowering authentic human ideas.
And that’s a future I’m excited to build toward.