Written by Julien Ricciarelli-Bonnal
17 August 2026
The Essentials
LinkedIn is beginning to reduce the visibility of AI-generated content it considers generic, repetitive or lacking a genuine point of view. The platform is developing detection systems, targeting automated comments and now allows some users to report what it calls “AI slop”. The paradox is obvious: like many platforms, LinkedIn actively encouraged the adoption of artificial intelligence before having to deal with its effects on content quality. The problem is not the use of ChatGPT or Claude itself. It begins when producing content becomes so easy that publishing more no longer means contributing more.
For several years, artificial intelligence has primarily been presented to content creators as a powerful accelerator. Finding ideas, preparing an outline, rewriting a text, summarising a study or producing a first draft can now take minutes. Platforms themselves have supported this shift by gradually integrating AI features into their own tools.
LinkedIn has been no exception. The professional network introduced features designed to help users write or improve their posts, while AI took an increasingly prominent place across its ecosystem. For a platform that depends directly on the volume of content published and the interactions it generates, making creation easier made perfect sense.
But the equation becomes more complicated when everyone can produce faster. Volume increases, the same structures appear everywhere, automated comments multiply and perfectly written posts end up saying very little. LinkedIn is therefore beginning to tackle a problem that AI itself has helped accelerate.
The platform is not declaring war on artificial intelligence. It is trying to prevent its feed from gradually becoming a conversation between machines.
LinkedIn Does Not Want to Remove AI, but Content That No Longer Adds Anything
The distinction matters. LinkedIn is not asking its members to abandon ChatGPT, Claude or other tools that can help them write. The platform acknowledges that AI can be useful for improving a formulation or facilitating production, provided that the result retains a genuine personal perspective.
What it is now targeting is what it describes as “AI slop”: content produced with little effort, often polished in appearance but generic, repetitive and interchangeable. This applies to posts, but also to automated comments that simply reformulate what the author has just written without adding a point of view, experience or additional information.
LinkedIn says it has developed its systems with its editorial teams to recognise this type of content. In early testing, the company claims a 94% accuracy rate in identifying generic posts. When content appears to be AI-generated and clearly lacks perspective, its distribution beyond the author’s direct network can be reduced.
The platform is going further by allowing some users to report content that “seems like AI slop”. It has also removed an automatic post-enhancement feature and is working on warnings for users when their writing appears excessively artificial.
All of this leads to a rather amusing situation: LinkedIn continues to regard AI as a perfectly legitimate tool, but is beginning to intervene when its use becomes too visible or too industrialised.
Platforms Are Discovering the Cost of Infinite Production
The problem LinkedIn faces extends far beyond its own feed. Generative AI has dramatically reduced the cost of producing average content. Something that previously required an hour can sometimes be created in a few minutes, while tasks that once required certain writing skills are now accessible to almost anyone.
For platforms, this abundance initially looks highly attractive. More creators can publish, users have more content to consume and overall activity increases. LinkedIn recently reported that content creation on its network had grown by 14% year on year.
But a platform does not survive on volume alone. It also depends on the amount of time users are willing to spend there, and that time partly relies on the belief that they can still find something worth reading. If ten consecutive posts use the same structure, offer the same advice and reach the same conclusions, ease of production eventually becomes a consumption problem.
This is probably where platforms are beginning to discover a limit they had little reason to anticipate at the beginning of the generative AI boom. Reducing the cost of creation almost to zero does not automatically produce more value. It can also produce a great deal more noise.
A Perfectly Written Post Can Become Perfectly Invisible
One of the most interesting consequences of this shift concerns the very idea of quality. For a long time, a well-structured, correctly written and pleasant-to-read post already had a clear advantage over careless content. AI has largely democratised that formal quality.
It is now possible to generate a grammatically correct text in seconds, complete with an effective introduction, logical progression and polished conclusion. When this capability becomes available to hundreds of millions of people, it inevitably stops being a differentiating factor.
The risk is that it can even produce the opposite effect. Certain structures have become so strongly associated with generative tools that readers recognise them before reaching the end of the first paragraph. Sequences of short sentences, artificial contrasts, relentlessly inspirational conclusions or comments that congratulate the author before summarising their own argument can create the impression of reading endless variations of the same post.
Two publications can therefore be equally polished and generate completely different reactions. The one containing a specific experience, an unusual opinion, a professional anecdote or simply a personal way of telling the story retains something the other does not.
AI has not removed the value of human writing. It has mainly reduced the value of writing that is merely correct.
The Paradox Affects Every Platform That Encouraged AI
LinkedIn is a particularly visible example because much of its value proposition relies on professional expertise. When users read the analysis of an executive, consultant, recruiter or specialist, they are generally looking for access to what that person knows, thinks or has experienced. If the entire post could be reproduced by a model using information that is already widely available, the value of that contribution becomes harder to identify.
But the same problem could gradually affect other platforms. Social networks have every incentive to make creation easier because content fuels audiences, recommendation systems and ultimately advertising revenue. At the same time, they need that production to remain diverse enough for people to continue wanting to consume it.
This creates a new contradiction. For years, the main challenge was convincing more people to create. With AI, the question may become how to prevent everyone from creating the same thing.
For companies seeking to build a content strategy that retains a genuine identity in an increasingly automated environment, AI will probably need to be treated as a production tool rather than a source of thought. It can accelerate research, help structure an argument or improve a formulation, but it cannot invent on behalf of an organisation the experiences and convictions that make its voice recognisable.
The Real Advantage May Once Again Be Having Something to Say
LinkedIn’s reaction ultimately says something rather ironic about the evolution of content marketing. For years, companies invested in publishing more frequently and maintaining a constant presence across different channels. AI finally gives them the ability to produce almost without limit, just as platforms begin telling them that volume will no longer be enough.
This obviously does not mean that using artificial intelligence is becoming incompatible with a strong editorial strategy. AI is already integrated into the working methods of many professionals and will probably remain there. The distinction will increasingly depend on what the user brings to the process.
A company using ChatGPT or Claude to turn genuine expertise into content is not in the same position as one simply asking it to generate five LinkedIn posts about trends in its industry. The final results may be technically comparable, but one has raw material the other cannot artificially generate: clients, experiences, failures, internal data, decisions and a particular view of its profession.
The consequence could actually be quite healthy. As formal writing quality becomes easier to obtain, experience, personality and the ability to defend an idea become valuable again. The technology that was supposed to help everyone write better may ultimately make the difference between writing correctly and genuinely having something to say much more visible.
LinkedIn is therefore not really fighting posts written with AI. It is beginning to fight a world in which AI allows everyone to publish indefinitely without necessarily having anything more to contribute.
We support companies that want to build a distinctive editorial strategy that uses new tools without allowing automation to erase their own voice.
Written by Julien Ricciarelli-Bonnal
17 August 2026
