The introduction of generative AI has changed the way we communicate in ways that are difficult to measure and perhaps even harder to understand. Alongside that transformation has come an enormous ecosystem of tools designed to make writing and creating content faster and easier, which can be incredibly valuable when the technology is used to support the person behind the content rather than replace them.
For someone like me, AI has been something of a superpower because grammar and spelling have never been my strengths, and turning the ideas in my head into polished writing has often required an editor. Today, I can take my own thoughts, research, and experiences and use AI to improve the structure, clean up the grammar, and make the writing more effective without changing the substance, which has made it much easier for me to communicate what I actually want to say.
That distinction matters because not everyone is using these tools the same way, and I think what we are seeing with AI-generated content looks remarkably similar to something we experienced years ago with Google.
We Have Seen This Movie Before
When search became increasingly important, marketers quickly figured out that keywords and inbound links influenced rankings, and that knowledge led to keyword stuffing, hidden text, purchased links, and other tactics designed to manipulate the algorithm rather than create better content for the person actually searching.
Google eventually got smarter as its algorithms evolved to recognize the difference between content created to satisfy the search engine and content created to provide genuine value. Relevant, authoritative content increasingly performed better, while tactics designed primarily to game the system became less effective.
I believe we are now entering a similar phase with AI because organizations can suddenly produce enormous amounts of content with very little effort, creating a powerful temptation to focus on volume rather than value. We are already seeing AI-generated articles, social posts, marketing materials, and content created specifically to influence how large language models perceive and surface companies, and while there are legitimate reasons for organizations to care about how they are represented within these systems, the strategy becomes problematic when producing content becomes more important than having something meaningful to say.
The Platforms Are Getting Smarter
We are already seeing early signs that the major platforms understand this problem as LinkedIn has introduced mechanisms that allow users to identify AI-generated content they believe provides little value, giving the platform another signal it can potentially use when determining what appears in users’ feeds. Claude has also introduced approaches to watermarking AI-generated content, while there has been growing discussion around how Google and other platforms can identify and evaluate material created with AI.
The details will continue to evolve, but the direction is what matters because these platforms have a strong incentive to distinguish between useful content and content created primarily to manipulate their systems. People do not want endless streams of generic, repetitive material filling their feeds and search results; they want expertise, perspective, research, and something worth spending their time reading.
That is why I believe the important distinction will increasingly become the difference between content that uses AI and content that is created by AI. When I take my own experience, incorporate research from 3Sixty Insights, develop an argument, and then use AI to help structure the writing and correct my grammar, there is still genuine thought behind the content, which is not fundamentally different from working with an editor who helps turn an author’s ideas into something more polished.
The bigger problem is content with no original thought behind it, where someone simply enters a prompt, accepts the output, and publishes it as though it represents their own expertise. That approach may create a tremendous amount of content, but eventually the platforms responsible for distributing that content will have to determine whether it deserves to be seen.
The Reckoning Is Coming
I think organizations that have built their marketing strategy around massive volumes of AI-generated content are eventually going to face a reckoning, much like the organizations that relied too heavily on SEO tactics before Google became better at recognizing content created to manipulate rankings rather than serve the reader.
The opportunity, in my opinion, is actually on the other side of this equation because companies still need strong marketing content, research, and perspectives that help their customers understand complicated markets. What will matter increasingly is the expertise behind that content, the credibility of the person or organization producing it, and whether there is a real reason for the content to exist.
That is one of the reasons we created Analyst Content as a Service at 3Sixty Insights, where organizations can work directly with an analyst and subject matter expert who understands the market, knows the terminology, has spent years studying the space, and can bring genuine perspective into the content creation process rather than simply generating another piece of material from a prompt. AI should amplify that expertise rather than replace it, because the technology can make a knowledgeable person more productive and a strong writer more effective, but it cannot manufacture the experience, perspective, and original thinking that give good content its value.
The next phase of AI in marketing will not simply be about who can create the most content or publish the fastest. I believe the organizations that ultimately stand out will be those that combine the efficiency of AI with the experience, research, and original thinking that make content worth consuming, because we learned that lesson with Google and I suspect we are about to learn it again with AI.