The Hidden Dangers of AI-Generated Content in Crypto

The appeal of AI-generated content is undeniable, particularly when it promises to increase output while reducing costs and effort. However, this strategy can backfire if not implemented thoughtfully. When AI-generated content is used to churn out large volumes of low-quality, repetitive pages, it can ultimately damage a company's credibility and search visibility. The issue lies in the fact that such content often appears as generic and lacks the depth and insight that readers expect from a genuine effort to inform. This approach not only fails to achieve its intended goals but also risks alienating readers and damaging the company's reputation. If readers do not trust the content, they are unlikely to engage with it or take any meaningful action. Furthermore, if the pages start to slip in search rankings, the platform, exchange, or dapp may struggle to be discovered. Google's policy on scaled content abuse is clear: creating and publishing numerous web pages primarily to manipulate search rankings, with little to no value for users, is problematic, regardless of the method used. The focus should be on how the content is produced and its purpose, rather than the tool itself. When a site starts producing vast amounts of unoriginal, low-value content to boost search visibility, it risks facing lower rankings or even removal from search results. Crypto companies should be honest about their use of AI. If AI is used to support a genuine editorial process, where writers or editors verify facts, add context, and ensure the content is helpful, then it can be beneficial. Google's guidance indicates that generative AI can be useful for research and structure, and this should be part of the conversation. However, publishing fully generated articles with minimal editorial review to rank for more queries at a lower cost is close to the kind of scaled output Google warns against. There is a significant difference between using AI to assist the writing process and using it to mass-produce content. Some publishers use AI for research, brainstorming, or outlining and then pass the piece to a real writer or editor who adds unique value. The old SEO playbook is still in use, but now with faster machines and lower production costs for weak content. This is why the problem persists. Once publishing more pages becomes easy and cheap, it is tempting to continue feeding the machine instead of questioning what is worth publishing. With Google's recent spam update, it is clear the company is refining its approach to detecting and handling web spam. Not every weak article is immediately affected, but it shows Google's ongoing effort to combat spammy behavior. Some crypto companies already use AI to publish large volumes of pages aimed at attracting search traffic. These pages often lack real value for readers. Under Google's guidelines, crypto companies relying on such low-value content should consider whether these pages should be indexed at all. In many cases, setting them to 'noindex' might be the safer approach. Companies treating mass AI output as a marketing shortcut are taking a significant risk. There is a smarter way to use AI in publishing, starting with keeping the SEO strategy in place and using AI for support tasks where it can genuinely save time. Google explicitly supports such uses, providing a sensible way for crypto companies to leverage AI. By letting AI handle early groundwork and leaving the reporting, writing, editing, verification, and final judgment to humans, companies can create better content that earns trust. In the crypto industry, where trust is crucial, this approach carries significant weight. The companies that will succeed are those that use AI as a tool within a proper editorial process, giving them a better chance of creating work that people want to read, cite, and return to.