Category: Technology | Published: 2026-08-06
If you have spent any time on LinkedIn recently, you will likely have noticed a particular kind of post. It tends to be three or four paragraphs long, starts with a short punchy sentence, uses line breaks for dramatic effect, and arrives at a conclusion about resilience, growth, or the importance of showing up. It could have been written by anyone. It probably was not written by anyone.
LinkedIn has noticed too, and it is now making a series of changes specifically designed to push back against what it is calling AI slop — generic, low-quality, AI-generated content that clogs feeds and gradually erodes trust in the platform.
What LinkedIn Is Actually Changing
The most visible new feature is a reporting option that lets users flag posts or comments they believe have been generated by AI. When you tap the menu on a post, you will see an option labelled something along the lines of "Seems like AI slop" — a phrase that is quite direct for a professional networking platform but reflects how seriously LinkedIn appears to be taking the problem.
That user-level reporting feeds into LinkedIn's broader detection systems, giving the platform a combination of automated classification and human signal to identify content that feels hollow, repetitive, or machine-produced.
The more substantive change, though, is what LinkedIn is doing to one of its own AI tools. The existing "Enhance your post" feature, which rewrote users' text using generative AI, is being retired. In its place comes a proofreading tool that corrects grammar and improves clarity without touching the author's voice or rewriting their sentences.
LinkedIn's Chief Product Officer Hari Srinivasan explained the thinking plainly: the team asked why people run posts through AI in the first place, and the answer was that LinkedIn feels like a place where you need to sound polished, and AI gives people confidence they otherwise lack. The new tool tries to provide that confidence without erasing the person behind the words.
The Scale of the Problem
LinkedIn is not being coy about how significant the automated content problem has become. Srinivasan revealed that the platform is already blocking hundreds of thousands of automated comment attempts every single day, and has blocked billions of automation attempts — mass posting, bulk commenting, feed flooding — over just the past couple of months.
Those are not small numbers. They suggest that LinkedIn AI abuse has become an industrial-scale operation, with networks of automated accounts or tools posting and commenting at volume in order to game the platform's reach algorithms.
Independent research adds further context. Originality.ai analysed 5,000 public LinkedIn posts of more than 100 words and concluded that over 81 per cent showed strong signs of AI generation. That figure uses the company's own detection methodology and is not LinkedIn's own measurement, but even if it overstates the problem significantly, the underlying trend is clearly real and clearly large.
LinkedIn is also deploying new AI classifiers that will assess content quality before deciding how widely to distribute it. Posts that appear to be automated or generic are expected to receive less algorithmic reach, which is the consequence that will matter most to anyone using the platform for marketing or brand building.
The Private Feedback Loop
One feature worth paying attention to is a new private feedback mechanism for content creators. When users flag a post as AI-generated or inauthentic, the person who published it will receive a note in their analytics dashboard explaining that some viewers found the content to feel automated or lacking in personal voice.
This is a meaningfully different approach from simply suppressing content or removing it. Rather than penalising creators invisibly, LinkedIn is trying to give them the information they need to understand how their content is landing. That reflects a distinction the platform is drawing carefully: using LinkedIn AI tools to refine and sharpen your thinking is fine; using AI to generate content you then publish as your own authentic voice is the thing they want to discourage.
Srinivasan put it directly: AI and slop are not the same thing. Many people refine their thoughts with AI assistance, and the platform believes those people genuinely want to know when the result sounds inauthentic.
Why This Is Happening Now
LinkedIn's changes are part of a broader reckoning across professional and social platforms about what generative AI has done to online conversation.
The basic problem is structural. LinkedIn's algorithm rewards engagement — likes, comments, shares. For years, people optimised their posts for that engagement, which pushed content towards the emotional, the inspirational, and the easy-to-consume. When generative AI arrived, it became trivially easy to produce exactly that kind of content in bulk. The result is a feed full of posts that look like thought leadership but contain no actual thought.
For LinkedIn specifically, this is a more serious problem than it would be for a consumer social network. The platform's value proposition is built on professional credibility. People come to LinkedIn to find expertise, make hiring decisions, assess potential business partners, and understand what is happening in their industry. If the content cannot be trusted to represent genuine human knowledge and experience, that value proposition collapses.
LinkedIn's own summary of its position is clear: people come to the platform to connect with real people and share real perspectives, ideas, and expertise. Maintaining that is described internally as a top priority.
What This Means for Businesses Using LinkedIn
For any business that uses LinkedIn for content marketing, recruitment branding, or executive visibility, these changes are directly relevant.
The most immediate practical point is that content which is visibly or detectably AI-generated is likely to receive less reach. LinkedIn's new classifiers are designed specifically to reduce how widely that content is recommended. If your business's LinkedIn presence relies on volume of output rather than quality of insight, the algorithm is about to become a less friendly environment.
The more important strategic point is what LinkedIn's actions are signalling about where value is going. Authenticity, genuine expertise, and original perspective are becoming harder to fake and more actively valued by the platform. A post that reflects real experience, a distinct point of view, or specific knowledge about your industry is going to perform better in this environment than a well-polished but hollow one.
There is also a reputational dimension. If your team's LinkedIn activity is flagged by followers as AI-generated slop, that feedback now surfaces privately to the poster. That is not a comfortable notification to receive, and businesses managing the LinkedIn presence of senior figures will want to make sure the content genuinely reflects those individuals' thinking rather than a prompt sent to a chatbot.
Using LinkedIn AI tools to proofread, structure, or polish content that originates from genuine human expertise is exactly the use case LinkedIn is now actively supporting. Using those tools as a substitute for that expertise is the use case it is working to identify and demote.
If you want to think through how AI can genuinely support your business communications without replacing the human insight that makes them valuable, our AI Consultancy page is a good place to start.