There’s no doubt that the recent surge in large language models (LLMs) and content creation tools presents significant advancement to business. Particularly in the content marketing and SEO space, the speed with which AI writing tools generate content translates into cost savings, scalability, and improved efficiency.
However, with these advantages come concerns about content quality, originality, and accuracy. But I’m not here to talk about the quality of AI content. With this piece, I’m more interested in how the AI content tools themselves work, particularly those that help with creating and optimizing content for SEO.
How Most AI Writing Tools for SEO Work
Generative AI tools rely on prompting to produce results. Based on your prompt—a keyword or question—AI tools use neural networks to look for patterns and structures within the datasets they’ve been trained with to generate content as outputs.
Essentially, the content they produce is always based on pre-existing information. But if you’re good with prompting and take care to specify a target audience, tone of voice, and style, the AI will try to string the words together in ways that sound unique and reasonable.
If you run a quick search for content generation on TAAFT (a database for AI tools), you’ll find about 440 AI content tools (as of the time of writing this article). I randomly selected 10 of them for long-form SEO content to get a feel for how they approach SEO content generation.
Each tool I tested churned out content with minimal input. Apart from basic details like tone of voice, content type, topic, and keyword, which I had to provide, none required additional context before generating paragraphs of text. They also did not present additional research on the topic, its search intent, or the competitive landscape before producing outputs that looked very believable at first glance. Here’s an example:
Tools like this demonstrate why most AI-written content often lacks depth and context, is generic and devoid of nuanced understanding.
Most AI Content Fails at SEO
On their own, the output from AI content tools is unlikely to succeed in search. If you frequently play around with content generators, you have seen first-hand how they DO NOT use much logic, nor do they produce content that solves the actual problem of the searcher. This is primarily due to their inability to understand dynamic user needs and satisfy the expertise, experience, authoritativeness, and trust required of helpful content.
Aside from that, content generators are only content generators. They do not understand context and entities and cannot connect the underlying concepts and ideas that an article needs to cover to be seen as authoritative. In a recent test comparing four AI content tools, the CEO of InLinks, Dixon Jones, found that entities are often the missing element when AI tools produce SEO content. And as we’ve discussed multiple times on the InLinks blog, connecting the ideas your content talks about to the entities Google sees and understands in its knowledge graph is the foundation for search ranking in today’s semantic web.
Most content generators cannot provide this added layer of functionality, making them less effective for SEO content when compared to specialized SEO tools.
Specialized SEO Content Tools Are the Way Forward
Before ChatGPT brought AI content to the forefront, many SEO tools, such as InLinks, quietly employed machine learning and natural language processing in their algorithms. For these tools, content generation is only the final mile. Instead, the background research and data analysis behind the scenes enable them to generate SEO content that drives results on the search engine. Some of these tools include InLinks, MarketMuse, and SurferSEO.
InLinks
As the first-ever suite of entity SEO software, InLinks focuses on generating and optimizing content for the semantic web using Natural Language Processing and a combination of advanced AI tools. It works by building a knowledge graph of websites and topics and analyzing audience needs and the competitive landscape with its semantic analyzer before using LLMs to articulate and contextualize information.
Content generation in InLinks begins with creating an entity-informed brief for a topic. This brief includes:
- The entities Google understands and associates with your topic,
- Target audience and user intent analysis
- Real-time keywords and questions pulled directly from Auto Suggest and grouped into topic clusters for creating side-wide connected content
- Comprehensive analysis of the top 10 or 20 competitors for your topic
- A Comprehensive content outline
- An AI assistant for generating content based on the outline.
The AI assistant inside the brief is where the magic happens. InLinks has built an audience finder tool that runs behind its content optimization tool. The audience finder works with the AI assistant to build a comprehensive content outline based on data from keyword and competitive research. Once you call the AI assistant, Open AI uses the outline as the prompt to generate contextually relevant, helpful, and well-optimized content.
This added functionality and depth of research before generating content differentiate InLinks from every other SEO tool in terms of content generation ability. It’s also why InLinks’ AI-generated content got the most traction in Dixon’s test of four AI content tools.
MarketMuse
MarketMuse is another AI content tool for SEO that adds a value layer before generating a word of content. The platform focuses on semantic optimization, so it conducts in-depth topic analysis to identify semantically relevant terms, content gaps, and personalized insights (based on your website) for every topic you wish to write about.
MarketMuse starts by creating a topic model representing entities and their corresponding relationships. It then builds a comprehensive content brief based on the topic model. The platform has built a Natural Language Generation engine that can help produce relevant long-form SEO first drafts based on the initial research performed by the software.
SurferSEO
SurferSEO is an AI SEO platform that has put effort into innovation. The platform provides an AI writer alongside other features such as keyword research, content optimization, audits, and SERP analysis to assist with creating content. However, its AI writer stands out for its ability to analyze your topic for NLP entities first. After its analysis, it provides a list of entities you need to include in your content to improve Google’s understanding of it.
Surfer has built its own NLP engine and uses it in conjunction with Google’s NLP to ensure every content you generate is well optimized for ranking.
ContentSprout
ContentSprout.ai is another AI SEO tool that puts some effort into producing great content. The tool builds out a topical content map and performs keyword clustering before generating content. The content outputs from ContentSprout sound human with little to no hallucinations. It also features a custom GPT editor that reanalyzes content to make sure it is search-optimized and has a human touch.
Wrapping it up
One thing is sure: artificial intelligence tools and LLMs are here to stay. Using them as part of your SEO toolkit will expedite your work and make you more efficient. However, achieving results depends solely on using the right tools. Regardless of their model, LLMs may not produce the desired results without context and entities, the building blocks that connect the world’s information. But if you’re looking for an AI SEO tool that produces content beyond superficial meaning, consider using InLinks today.
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