The Anatomy of an AI-Powered "SEO Heist": Was It Worth It?

In the ever-evolving world of search engine optimization (SEO), the increasing accessibility of powerful AI tools is causing both excitement and concern. Recently, one agency founder‘s bold move to use AI to "steal" 3.6 million pageviews from a competitor sparked heated debate in the SEO community.

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By leveraging Frase for AI-generated content and Ahrefs for competitive research, the agency claims to have pulled off a massive "SEO heist." But was this clever exploitation of AI tools a strategic success or an unethical stunt that threatens the integrity of search results?

Let‘s dive into the details of how this "heist" was executed, the backlash it received, and what it means for the future of AI and SEO.

Inside the Heist: How They Used AI to Produce Content at Scale

The mastermind behind this scheme is [name], founder of [agency]. With a background in [relevant info], they saw an opportunity to use AI to quickly outrank a competitor.

The process they used was relatively straightforward:

Use Ahrefs to scrape the competitor‘s entire sitemap and compile a list of target keywords and topics.
Convert the target topics into SEO-optimized blog post titles and outlines.
Feed the outlines into Frase‘s AI writing tool to generate full articles at scale.

Using this system, the team was able to churn out over 1,800 blog posts in just a few hours – a feat that would take a human writer months or even years to accomplish.

To put this in perspective, the average time to write a quality blog post manually is 3 hours and 55 minutes, according to a survey by Orbit Media. At that rate, producing 1,800 posts would take over 7,000 hours – nearly 3 years of 40-hour work weeks!

So from a sheer efficiency standpoint, it‘s clear why the allure of AI-generated content is strong. But what about the impact on quality and search rankings?

The SEO Mechanics That Allowed the AI Content to Rank

Savvy SEO pros may be wondering how this mass-produced AI content was able to outrank the original, human-written pages. While Google‘s systems are designed to identify and demote low-quality or duplicative content, the AI posts were able to slip through by using a few key tactics:

Speakable schema was applied to help Google identify key passages and give the AI content more visibility in voice search and featured snippets.
PAA (People Also Ask) questions were used as H2s and H3s to mirror the style of top-ranking pages and build relevance for long-tail keywords.
Aggressive internal linking was employed to quickly spread link equity to the new pages and help them gain authority.
Exact-match anchor text was used to send strong keyword relevancy signals, taking advantage of the fact that the AI content was able to be hyper-targeted to specific terms.

In essence, the AI content was heavily over-optimized in a way that would be difficult or risky for publishers of human-written content to replicate. And by doing this at such a large scale in a short period of time, the new pages were able to leapfrog to the top of search results before the algorithms could adjust.

Backlash & Ethical Concerns: The Dark Side of AI-Powered SEO

While the agency founder framed this as a clever "heist" and "experiment," many in the SEO community saw it as a dangerous step toward normalizing the mass production of low-quality, AI-generated pages.

The most vocal critics were, understandably, the original content creators whose work was used as "inspiration" for the AI. As shared in the intro, one of them responded to the agency founder‘s bragging post on LinkedIn with valid concerns:

"Who will answer for the AI-generated content, not reviewed or tested by anyone who cares? This kind of project is really the worst of the web. It will seriously degrade the quality of the content we humans consume."

This sentiment was echoed by many SEO experts who worry that this type of "blackhat" AI usage could pollute search results with content that is, at best, surface-level regurgitation and, at worst, inaccurate or untrustworthy.

Lily Ray, Senior Director of SEO at Amsive Digital, shared her take on Twitter:

"I don‘t support agencies bragging on social media about using AI chat tools to pump out content at scale in order to intentionally steal rankings from other sites. In general, publishing AI content without serious editing is a bad idea for the end user and risky from an SEO perspective."

Glenn Gabe of G-Squared Interactive also weighed in:

"Regarding AI-generated content, I recommend proceeding with caution. Make sure there‘s a human involved reviewing that content for accuracy, and to add more value. Check E-E-A-T while you‘re at it. 🙂 Just publishing it as-is can be super risky…"

These experts raise important points about the risks and downsides of prioritizing efficiency over quality when it comes to AI content generation:

Inaccuracies and misinformation: AI writing tools are prone to "hallucinating" facts and can perpetuate false information if not carefully fact-checked by humans.
Quality and trust issues: Content that is surface-level or riddled with errors erodes user trust and leads to high bounce rates and poor engagement.
Lack of E-E-A-T: AI can‘t demonstrate the expertise, experience, authoritativeness, and trustworthiness that Google‘s quality rater guidelines prioritize.

It‘s also worth noting that the original content creators likely spent dozens or even hundreds of hours researching, writing, and fact-checking their posts – not to mention the years of experience and expertise they drew from.

To have all that in-depth, hard-won knowledge reduced to an AI training set and spit back out in minutes feels, to many, like intellectual theft. Even if the AI output is technically "unique," it‘s still leveraging someone else‘s ideas and information without actually improving upon it or adding value.

Google‘s Countermeasures: Why the "Heist" Is Likely Short-Lived

For publishers considering replicating this AI-powered "heist" playbook, there are strong signals that it‘s not a wise long-term strategy. Google has made it clear that they do not want search results dominated by thinly-veiled AI spam.

In Google‘s view, the goal of search is to surface high-quality content that demonstrates strong E-E-A-T (expertise, experience, authoritativeness, and trust) and provides a satisfying user experience. Their algorithms are constantly being updated to better identify and reward content that meets those criteria.

Some key ways Google is fighting back against low-quality AI content:

Helpful Content Update: Launched in August 2022, this update specifically targets "content that seems to have been primarily created for ranking well in search engines rather than to help or inform people."
Spam Updates: Google rolls out periodic spam updates to better detect and nullify spammy tactics like auto-generated content, keyword stuffing, and cloaking.
Quality Rater Guidelines: Google employs over 10,000 search quality raters whose feedback is used to train its machine learning algorithms on how to spot low-quality pages.
Engagement Signals: Google‘s RankBrain system uses machine learning to adjust rankings based on user engagement signals like click-through rate, bounce rate, and time on page. Thin AI content often performs poorly on these metrics.

So while this "SEO heist" was able to game the system in the short term by exploiting loopholes before Google could react, it‘s unlikely these rankings will last as the algorithms continue to get smarter.

In fact, we can already see evidence that Google has caught on and is penalizing the AI-generated pages that were bragging about "stealing" traffic:

[Traffic graph showing steep drop after publishing LinkedIn post]

Aleyda Solis, a renowned international SEO consultant, summed up the fleeting nature of this AI-gaming approach on LinkedIn:

"Blackhat will be able to scale much more using AI, but it will also become much more detectable by Google, faster. Both sides scale but Google will still win at the end with their ML systems + quality raters + engagement signals feedback loop."

The Right Way to Leverage AI for SEO

All this isn‘t to say that AI tools have no place in an SEO strategy. When used ethically and with human oversight, AI can help scale and streamline parts of the content creation process without sacrificing quality.

Some legitimate ways to leverage AI for SEO include:

Keyword research: Use AI to analyze search data and identify content gaps and opportunities, then have human experts assess the findings and prioritize topics.
Content outlining: Generate blog post outlines or briefs with AI to help guide writers and ensure SEO elements are addressed, but let humans do the actual writing and editing.
Meta tag optimization: Have AI suggest title tags and meta descriptions at scale, then have an SEO editor review, refine, and implement them.
Content optimization: Employ AI-powered tools like Clearscope, MarketMuse, or Surfer SEO to ensure human-written content is well-optimized for relevant keywords and entities.
Fact-checking and plagiarism detection: Run AI-generated content through tools like Grammarly or Copyscape to catch potential errors or accidental duplication before publishing.

The key is to have knowledgeable humans involved at every step to provide quality control and direction. AI should assist and augment human expertise, not replace it completely.

When you keep people at the center and prioritize original ideas and analysis, AI can be a powerful tool for improving your content‘s quality, relevance, and SEO performance.

The Future of AI and SEO: Human-Centric Content Is King

As AI content generation tools become more sophisticated and accessible, it‘s clear that they will play a growing role in SEO and digital marketing.

Google itself is leaning heavily into AI, with language models like MUM and LaMDA powering more intelligent and intuitive search features.

And from an SEO practitioner‘s perspective, AI will undoubtedly become a go-to solution for tasks like keyword research, content optimization, and even technical elements like schema markup and internal linking.

However, what‘s equally clear is that Google is committed to rewarding content that puts humans first. Their entire business model relies on serving search results that people find genuinely useful and trustworthy.

No matter how well AI tools can optimize for keywords and engagement signals, they will always struggle to replicate the depth of knowledge, original ideas, and authentic experiences that only humans can provide.

As Google‘s search algorithms continue to evolve, they will only get better at detecting and devaluing mass-produced AI content that skimps on quality in favor of scale.

So while AI should certainly be part of any forward-thinking SEO professional‘s toolkit, it must be balanced with a steadfast commitment to creating people-first, high-E-E-A-T content.

Those who view AI as an "SEO heist" shortcut will inevitably face the consequences as Google cracks down. But those who leverage AI ethically and strategically to enhance their human-led content will be well-positioned to succeed in the future of search.