The Dangers of Black Hat AI SEO Techniques

Why Black Hat AI SEO Is Gaining Traction (and Why That’s a Red Flag)

For years, businesses have relied on traditional SEO tactics, keyword targeting, link-building, content pages, technical optimisation. Now with generative AI in the mix, some agencies and marketing teams are tempted to pivot to “fast-and-dirty” GEO: mass-produce pages, use AI models to generate lots of content, create “encyclopaedias” around services or products, and hope the volume wins at the rank/answer layer.

From one vantage, it makes sense: you serve your category by rapidly building strong topic coverage. In the context of your brand, indexLab helps businesses “stay visible in the age of AI search”, recover traffic lost to AI, and get cited by LLMs. But here’s where the trap lies: if you build tons of low-value pages just to game ranking/AI citation without ensuring genuine helpfulness, you cross into black-hat territory.

Why this is dangerous:

• It dilutes your domain’s quality signals. When you generate hundreds of pages that don’t truly serve users, you burn your E–E–A–T (Experience, Expertise, Authoritativeness, Trustworthiness).

• Automatically generated, shallow or templated content tends to get flagged by search engines and answer-engines as “scaled content abuse”. (Google for Developers)

• Generative AI tools make it easy to create volume, but they don’t guarantee value or uniqueness. Some of this content becomes what tech folklorists call “AI slop”; meaning content that’s mass-produced and low-impact. (Wikipedia)

• If you’re trying to game LLM answer citations (e.g., get mentioned in ChatGPT responses), you risk being disqualified by the LLM’s own filtration of low-quality sources, or worse: becoming part of a spam network that these systems suppress.

• Once the algorithm penalises you, recovery is time-consuming, painful and often costly in brand reputation.

For heads of marketing and business owners seeing traffic collapse: the impulse to ramp up AI-content generation is understandable, but that very move may be part of the reason visibility is dropping. It’s like trying to outrun a fire by running into more fire-hazards.

What Google & OpenAI Have Said About AI-Generated Content and Spam

Google

According to Google:

• “Using generative AI tools or other similar tools to generate many pages without adding value for users may violate Google’s spam policy on scaled content abuse.” (Google for Developers)

• Google states: “Automation, including AI, used with the primary purpose of manipulating search rankings is a violation of our spam policies.” (Google for Developers)

• In the updated Search Quality Rater Guidelines (2025) Google says pages where all or almost all of the main content is AI-generated/auto-generated with little or no added value should be rated “Lowest Quality”. (Search Engine Land)

OpenAI

OpenAI, for its part, is also actively disrupting malicious AI uses. According to its October 2025 report, they’ve “disrupted more than 40 networks that violated our usage policies… including abuses like scams, malicious cyber activity, and covert influence operations.” (OpenAI)
While the OpenAI policy is more about model misuse (spam, disinformation) than SEO operations per se, the implication is clear: generative AI campaigns built for manipulation are increasingly visible to the major platforms.

Together, these signals show that the tide is turning: the “easy-game” era of mass-generative pages is over, at least for those who want sustainable visibility in search or AI answer contexts.

Real-World Example: The J.C. Penney Case: A Lesson for the AI Era

In 2010/2011, J.C. Penney found itself on the front pages of the internet for all the wrong reasons. A The New York Times investigation revealed that thousands of seemingly unrelated sites were linking to jcpenney.com in a clear link-scheme designed to game Google LLC’s ranking algorithms. (Search Engine Land)

Google confirmed that the tactics violated its Webmaster Guidelines and promptly penalised J.C. Penney. Their rankings collapsed, and traffic plummeted. (Stone Soup Tech Solutions)

Why this matters today in the AI-SEO context:

• The mechanism is different (AI content rather than bought links), but the principle is the same: manipulation of ranking/visibility signals rather than serving users.

• Just like links used to serve as popularity signals, in the AI era aggregated signals like “how much useful content does this domain offer a human?” or “does this domain get cited by LLMs?” will matter. If you flood your domain with shallow pages, you’re building “fake popularity” not genuine value.

• The penalty wasn’t just about a drop in rankings; it was about trust. Once the search engine decided J.C. Penney had crossed the line, their brand lost credibility in the eyes of the algorithm and the ecosystem.

• For business owners/heads of marketing, the takeaway is clear: you can gain visibility rapidly with shortcuts, but you risk long-term collapse. In the AI-SEO era that risk is magnified because LLMs also factor in signals we’re only beginning to understand (citation, domain authority, context, helpfulness).

Three Recommendations: How to Avoid Going Too Far in AI-Search-Friendly Content Creation

When you’re engaging in AI visibility optimisation, generative engine optimisation, or preparing to recover traffic lost to AI, you want to be bold but safe. Here are three key recommendations:

1. Focus on People-First Value, Not Volume

• Before you publish a page created with AI assistance, ask: “Does this page serve a real human need better than what’s already out there?” If the answer is no, don’t publish it just because you need more pages.

• Align to the E-E-A-T framework: does this page demonstrate experience (from someone who has done it), expertise (subject-matter knowledge), authoritativeness (credible backing or links) and trustworthiness (clear authorship, transparency)? Google says any content must satisfy these whether AI-generated or human-written. (Google for Developers)

• Use AI as a tool to help craft the content, not as a substitute for human insight. Let human writers refine, add anecdotes, examples, personal insights.

• Produce fewer but better pages. One well-crafted guide that genuinely helps a buyer or prospect beats 100 templated machine-generated posts that barely move the needle.

2. Use AI-SEO Optimisation Responsibly and Contextually

• For your domain focusing on “AI Visibility optimisations”, “Recover Traffic Lost to AI”, “Get Cited by ChatGPT” etc, build a content ecosystem rather than islands of pages. Use pillar-pages, topic clusters, internal linking, and depth of subtopics. Avoid the trap of squeaking out marginal pages purely for “keyword coverage”.

• Make sure each content piece aligns with searcher intent and also with AI-answer intent. LLMs like ChatGPT, Gemini and Perplexity don’t just look at keywords; they assess credibility, depth, uniqueness. So your content must reflect that.

• Monitor your content’s performance not just in Google rankings but also in terms of mentions/citations in answer-engines. If you’re not being cited by AI, review whether your content is genuinely answer-ready or just “SEO-engineered”.

• Audit your site regularly with an “AI Visibility Audit” (a service indexLab offers) to detect weak pages, low-value pages, poor experience content and remove or consolidate them.

3. Build Long-Term Trust and Authority; Don’t Chase Shortcuts

• Use backlinks, but focus on genuine authority-building rather than “link buying” or manipulative linking networks. The J.C. Penney case shows how swiftly link-based manipulations collapse.

• Gain trust signals for AI engines: author profiles, real testimonials, case studies from your work.

• Encourage your domain to become a source for other trustworthy sites. When you build real value, other sites and answer engines will reference you. That signals to AI-SEO systems that you matter.

• Keep yourself updated with policy shifts. For example, Google has rolled out stricter rater guidance around generative AI content in 2025. (Search Engine Land)

Table: Quick Overview of Risks vs Safe Approach

Frequently Asked Questions

1. What is black hat AI SEO and why is it dangerous?

Black hat AI SEO refers to using AI‑generated content or manipulative tactics solely to game search engines or AI answer engines. It is dangerous because it can lead to algorithmic penalties, loss of traffic, and damage to your brand’s trust and authority.

2. How can I avoid black hat practices while using AI for SEO?

Focus on creating content that provides real value to users, use AI as an assistant rather than a replacement for human insight, and ensure your content aligns with Google’s E‑E‑A‑T principles. Audit your site regularly to remove low‑value or thin content.

3. Can black hat AI SEO tactics impact AI citations like ChatGPT or Gemini mentions?

Yes. LLMs and AI answer engines prioritise credible, authoritative, and helpful content. Sites using manipulative AI tactics risk being excluded from citations and losing visibility in AI-powered search results.

Conclusion

When you hear about “quick wins” in AI SEO, think of the old link-schemes that got companies like J.C. Penney penalised. The mechanisms differ today (generative content rather than bought links), but the underlying principle remains: you cannot trick algorithmic visibility systems for long without building real substance.

At indexLab, our focus is not just on AI SEO optimisation in isolation but on AI Visibility optimisation; ensuring your brand is seen, trusted, and chosen in an era when humans ask LLMs and answer-engines rather than typing keywords. That demands more than “lots of pages”; it demands authentic, helpful content, integrated into a broader visibility strategy.

👉 Book your AI Visibility Audit with IndexLab today and make sure your brand isn’t invisible in the age of AI search