How to skyrocket your visitor numbers with AI driven SEO... and the hidden risks.
- Roberto Bortoli
- Mar 19
- 3 min read
Agencies and service providers offering so-called "AI content factories" or "AI-driven SEO" are popping up everywhere right now. There are quite a few of them, and each one promises to dramatically improve your search engine rankings thanks to AI and simultaneously explode the number of visitors to your website. This whole thing can actually work, but there are risks, too! We want to make sure you're aware of those risks and, above all, the latest developments, especially from the well-known search giants! That's why we're writing this blog post.
The basic idea behind "AI-driven SEO" (in German "AI-driven search engine optimization") is that with the help of an AI language model (e.g., GPT) and corresponding automation workflows, you can generate a large amount of content in a short period of time in order to continuously publish new content on a website. These posts should then rank on Google & Co. via long-tail keywords and other SEO measures, thus gradually increasing organic traffic.
But how does this work in detail?
The process is practically always the same and consists of the following 3 steps:
1. Industry or topic training:
An AI is first "fed" with industry-specific information. This can be existing texts, white papers, studies, or other sources. The idea is that the AI gains a deeper understanding of the customer's field of expertise and can thus create more specific, relevant content.
Style guidelines and tonality guidelines are often also provided so that the AI content fits the overall brand image.
2. Automated content creation:
Based on predefined SEO strategies (topic clusters, keyword research, etc.), the AI then generates blog articles or other content formats (e.g. white paper summaries, email newsletters, social media posts) at regular intervals.
The content is then usually automatically created in the corresponding CMS (WordPress, HubSpot, etc.) via an API interface and either published directly or submitted for approval.
3. Continuous optimization:
The agency also uses SEO tools or monitoring tools to observe keywords, rankings and traffic development.
If certain articles are not ranked well, the AI can create additional variants or optimize existing content until it performs better.
What are the opportunities and risks?
👍🏼 Chances :
Fast scaling: Instead of just one article per week being created by an editor, dozens of articles can theoretically be produced per week.
Cost efficiency : When content demand is high, automated approaches can be attractively priced (compared to manually created content by a large editorial team).
Topic coverage : Using targeted keyword clustering strategies, you can quickly cover many (long-tail) topics, which can bring in more visitors organically.
❗️ Risks :
Quality and added value : If the AI content looks correct but doesn't provide anything substantial or new, it's a risk of "thin content." Google and other search engines tend to rate such mass content negatively if it lacks depth and added value.
Duplicate content : With high levels of automated production, there is a risk that similar text blocks will appear multiple times, which can harm SEO.
Timeliness : AI models (especially if trained locally) can produce outdated information. This can be a problem for rapidly changing topics (e.g., technological trends, legal requirements).
Google Guidelines : Google has now made it quite clear that AI-generated content is not prohibited per se, as long as it provides real added value for users. "Automated spun content," however, meaning automatically generated but low-quality text, can be penalized .
What should you pay attention to as a customer?
Human editing : It's usually recommended to have AI-generated content reviewed or enhanced by a (human) editor or subject matter expert. This ensures that the content is accurate, error-free, and unique.
Genuine expertise : Blog posts that only provide superficial information are easily exposed these days. On the other hand, those that can provide expert tips, industry insights, or case studies will gain long-term trust from readers and search engines.
Long-term content strategy : Instead of just publishing a mass of generic posts, the content strategy should be geared towards clear user and search intent.
Monitoring and ongoing optimization : AI-driven processes should be tracked and optimized just like any other SEO measure. This is the only way to determine whether the content is actually driving traffic or whether adjustments are necessary.
In certain cases, this can be very successful, provided the quality and relevance of the articles remains high and the generated content meets user needs. However, those who simply "pump out" large amounts of automated text risk being penalized by search engines if they don't generate any real added value!
