Low-Effort SEO Is Over—Here’s What Real Content Quality Looks Like

Face it: the content quality on the internet has been declining, and honestly, artificial intelligence has only accelerated the decline into a free fall. In fact, two-thirds of marketers are using AI as their key tool for automated content generation (65%), according to an Artios Q1 2025 AI study of more than 400,000 expressed opinions. 

Even with an increasing number of disclaimers, marketers still blindly publish AI generated content without reviewing it first. Maybe it’s because they’re still playing the old SEO game: flood the internet with large quantities of content in an effort to increase clicks. This approach just creates more content; there isn’t anything new let alone great. As a result, AI can make content forgettable and brands appear generic and undistinctive. 

Delivering Quality Content With a Capital Q

AI generated content may seem better, but in reality, AI degrades content quality. According to Artios, quality of content is defined by its usefulness to its intended reader (i.e., the target audience). Quality content is not just what is said, but how it but how it’s delivered (e.g., copy, press release, tool, graphic, video, podcast, etc.). The more checked boxes for the target audience, the higher the content quality. That’s not to say that AI can’t elevate content quality because it most definitely has the power to do so. If used judiciously and in the right way, AI can actually improve content quality and its utility.  

Marketers are already working on figuring out how to create better content for search engines and LLMs, especially since keywords aren’t working like they used to. One way is to reverse engineer an LLM to determine a predictable formula of success: if you do x, then y will happen. This approach is much easier with traditional SEO because keyword search consoles share reports of what people are inputting. However, for LLMs, it’s a lot less straightforward and much harder to extract. It’s not for lack of effort from marketers; rather, it’s because AI is still new and tools for the SEO industry are still in their embryonic stage. 

Reverse Engineer for a Deeper Connection With People, Not to Outsmart the Machine

Instead of reverse engineering LLMs, marketers may be more successful at reverse engineering target audiences using AI. The 43% of marketers using AI for audience insights are probably already seeing the benefits to some extent. AI can definitely crowd source an idea and summarize what people are saying about their brand, product or service, and marketers can use those insights to spot emerging trends, identify gaps or niches to be addressed, provide audience sentiment, manage reputation and personalize messaging. But that’s using what AI says at face value. How reliable is the information? 

That’s where validation comes in. Ready-made AI models such as Chat GPT can only provide a general idea, but if the goal is to make sure the information will actually support marketing efforts and reach target audiences, then it’s critical to validate the information before spending money on content that might not land as intended if at all. 

One option is to create a new proprietary AI model, like Artios did, that takes source data from online spaces such as X, Bluesky, and Reddit, trains the model, and then validates the information to determine how the data would land in the real world producing statistical parameters with a confidence interval and a margin of error. This approach not only produces validated ideas for new content, but it can also resurrect older, stale content currently living on a brand’s website. 

Transparency builds trust, and in a world where customers expect brands to be more accountable, Artios can deliver AI studies and quality content that brands and their customers can feel confident about. 

If you’re reading this, it’s because you already realize your SEO strategy isn’t working like it used to. Artios AI SEO can help elevate your content quality with validated AI studies of your target audience. Discover how data science can replicate market research results. Contact Artios today.