AI-generated content may seem like an easy win for companies, especially when the promise is simple enough to sell internally: publish more crypto content, cover more keywords, spend fewer resources, and pick up more organic traffic along the way.

On paper, that may sound cost-efficient, and in some cases, AI can absolutely help with research, structure and early drafting. But once that logic turns into pumping out large volumes of thin and repetitive pages, the whole strategy starts to work against itself, and in the crypto space, that can become a bigger problem than some companies seem willing to admit.

The reason is fairly straightforward: A company might think they’re improving their search visibility, but if the pages it publishes feel like generic fluff pieces, the content stops looking like a serious effort to inform readers and starts looking like a cheap attempt to occupy search results.

This ends up defeating the purpose of creating those pages in the first place, since no goal is being achieved; it’s like you’re just throwing content at your website, with no strategy and thinking that will get you results.

If readers don’t trust you, how will they convert or take any action? And if your pages start slipping down in the rankings, how will your platform, exchange or dapp be discovered?

When AI Slop Turns Into Scaled Content Abuse

Google’s policy on scaled content abuse is pretty clear: The problem is creating and publishing lots of web pages mainly to manipulate search rankings while giving users very little to no value in return, and that standard applies regardless of how it’s created.

That is worth stressing, because many people still talk as though the real issue is the tool, when Google is actually focused on how the content is produced and why it is published in the first place.

So when a site starts pumping out huge volumes of unoriginal, low-value pages just to win more search visibility, it is moving straight into the kind of territory Google says can lead to lower rankings or even removal from search results.

And that is where some crypto companies should probably be more honest with themselves. If AI is being used to support a real editorial process, where a writer or editor checks the facts, adds context, sharpens the argument and makes sure the finished piece actually helps the reader, then that is one thing.

Google’s own guidance says generative AI can be useful for research and structure, and that deserves to be part of the conversation. But when a company starts publishing fully generated articles with little or no editorial review because it wants to rank for more queries at a lower cost, it is getting very close to the kind of scaled output Google is warning about.

There is also a real difference between using AI to assist the writing process and using it to dump out content at scale. Some publishers use AI for research, brainstorming, or outlining, and then pass the piece to a real writer or editor who checks the facts, adds unique reporting, sharpens the argument, and makes sure the article actually has something worth saying.

It’s the same old SEO playbook… with a faster machine

From that perspective, AI slop is really just the same old mass-page SEO playbook, with a faster machine behind it and a much lower cost to produce weak content.

That is one reason this keeps getting worse. Once publishing more pages starts to feel cheap and easy, it becomes much easier to keep feeding the machine instead of stopping to ask what is actually worth publishing. And with Google’s March 2026 spam update rolling out recently across all languages, it is clear the company is still working on how it handles web spam at scale.

That does not mean every weak article gets hit instantly, but it does show that Google is still refining how it detects and handles spammy behavior.

Some crypto companies are already using AI to publish large volumes of pages aimed mainly at pulling in search traffic.

Sometimes that takes the form of comparison pages built around competitor terms and location-based keywords. In other cases, it shows up in token pages, wallet guides, airdrop explainers, exchange reviews, educational content, or service pages that look like they were created to get clicks without providing any real value.

When you look closely at how those pages are made, and how little they actually do for readers, it becomes much easier to understand the search risk involved.

Under Google’s scaled content abuse guidelines, crypto companies relying on this kind of low-value material should think carefully about whether those pages belong in search at all. In many cases, setting them to “noindex” may be the safer move.

So, crypto companies treating mass AI output like a marketing shortcut are taking a real gamble in an environment where Google keeps updating enforcement in plain view.

There’s a smarter way to use AI

There is still a smart way to use AI in publishing, and it starts with keeping the SEO strategy in place while using AI for support tasks where it can genuinely save time. Research help, idea generation, outlining and early structuring all make sense, especially for crypto companies that want to move faster without lowering their standards.

Google explicitly says those uses can be helpful, and that gives crypto companies a sensible way to use AI, so let it speed up the early groundwork and then leave the reporting, writing, editing, verification and final judgment to human hands.

That approach is safer for search, and it also leads to better content, because people can usually tell when something has been properly thought through, carefully put together, and written by someone who actually knows what they’re talking about. In the crypto industry, especially, where trust already has to be earned more carefully, that difference carries a lot of weight.

The crypto companies that come out ahead will be the ones that use AI as a support tool within a proper editorial process, because that gives them a better chance of creating work people actually want to read, cite and come back to.