In SEO and content marketing, we’re seeing the immense potential of AI tools to generate large volumes of articles, FAQs, and social media posts. This can be valuable for targeting high-intent keywords and reaching new audiences. But there’s a flip side: AI content can just as easily damage your search rankings if it’s generic, untargeted, or lacks the expertise that real users (and Google) are looking for.
So, which is it? The reality is, it’s both.
Like any tool, the output of AI is only as good as the preparation you put in. If the process is simply “prompt, edit, publish,” the results will be shallow.
Take a solicitors new website for example. In building out SEO content for their family and divorce services, it would be easy now to let AI generate a standard list of FAQs. A quick process might look like this:
The result? A lot of words, but not much value. The content risks being thin, repetitive, and indistinguishable from any other law firm’s site.
The key to unlocking AI’s true potential is going beyond what’s publicly available. AI models already know the internet, so if you don’t give them anything new, the output will be generic.
Rather than letting AI “free run,” ground it with:
This preparation means that AI becomes an accelerator, not a shortcut—helping scale content while keeping it distinctive, authoritative, and genuinely useful.
AI is a powerful tool for generating content at speed. But the real value is directly proportional to the quality of the data you give it. By laying the groundwork with your own knowledge, stories, and processes, you can ensure AI output is valuable for users and effective for SEO.
That’s the lesson we’ve learned in practice: treat AI as a partner, but feed it like a specialist. The difference between generic content and meaningful, performance-driving work isn’t the tool—it’s the foundation.
Author: Phil McDowell
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