The platforms want more original content. Why are brands producing more of the same?

There has never been more content being produced by brands. There are more LinkedIn posts, more thought leadership articles, more videos, more newsletters and more commentary on whatever happened in the market that morning.

And yet so much of it feels exactly the same.

The language is polished. The formatting is clean. The right keywords appear in the right places. There is usually a confident opening line, a predictable observation and a conclusion about embracing change.

Technically, there may be nothing wrong with it. The problem is that there is often nothing particularly interesting about it either.

This matters because the major platforms are becoming increasingly clear about the type of content they want to surface. LinkedIn is trying to reduce generic and recycled posts in favour of real expertise and personal perspectives. Meta is giving more reach to original content while deprioritising low-value copies and reposts. Google has been telling businesses for years to create useful, trustworthy content grounded in genuine experience.

The platforms are all saying roughly the same thing: give people something they could not get from hundreds of other accounts.

Brands, however, appear to be moving in the opposite direction.

LinkedIn is trying to clean up the feed

LinkedIn has been unusually direct about the problem. In its announcement about improving the feed to show more relevant and authentic content, the company said it was working to reduce generic, recycled and engagement-driven posts while giving greater visibility to content grounded in real experience, knowledge and professional perspective.

LinkedIn has also made it clear that AI use itself is not the target. As reported by TechRadar following LinkedIn's announcement, the platform's position is that people can use AI to help them write, but their posts and comments still need to represent their own voice and perspective.

That distinction is important.

A subject-matter expert might use AI to organise a complicated argument, improve the structure of a draft or make their writing clearer. The expertise still comes from the person. The examples are theirs, the opinion is theirs and the conclusions are based on something they have actually seen or done.

Generic AI content works differently. It begins with a broad topic, draws on the same publicly available information and produces a safe summary of what is already known. The result may sound professional, but it rarely gives the reader a reason to remember who published it.

LinkedIn has since gone further by allowing members to flag posts that appear to be "AI slop". The platform is not treating every AI-assisted post as low quality. Its concern is content that feels repetitive, inauthentic or produced at scale without adding anything meaningful.

That should concern brands relying on volume as their primary content strategy. Publishing more frequently will not help if every post sounds as though it could have come from any company in the category.

Meta is rewarding originality too

Meta has made a similar move across Facebook and Instagram.

In March 2026, Meta announced that it was giving original creators greater reach and monetisation while reducing the distribution of unoriginal content. Its updated guidance makes an important distinction between simply reusing existing material and adding something genuinely new.

According to Meta, content can still incorporate third-party material if the creator contributes fresh information, analysis or a substantial creative improvement. Minor changes such as adding captions, borders, reaction footage or changing the speed of a video are not enough to make it original.

This is partly about protecting creators from accounts that copy their work, but it also speaks to a wider problem. Social feeds have become crowded with recycled clips, replicated formats and versions of the same idea edited just enough to appear new.

Meta reported that views and time spent watching original Reels approximately doubled during the second half of 2025 compared with the same period in 2024. The platform has a commercial reason to prioritise originality: repeated content makes the feed less interesting, and a less interesting feed gives people fewer reasons to keep using it.

Recency also matters because people use social platforms to understand what is happening now. A current topic can create an opportunity for a brand to contribute, but speed alone is not enough. Repeating the same announcement or observation as everybody else does not make the content valuable simply because it was published quickly.

The advantage comes from connecting the event to something the business actually understands.

Google has been saying this for years

Google's language is different, but its direction is consistent with what we are seeing from LinkedIn and Meta.

Its guidance on creating helpful, reliable, people-first content asks whether content provides original information, research or analysis, whether it offers insight beyond the obvious and whether it demonstrates first-hand expertise.

Google's E-E-A-T framework considers experience, expertise, authoritativeness and trustworthiness when assessing content quality. Google is careful to explain that E-E-A-T is not a single ranking factor, but the principles provide a useful way to understand what its systems are designed to reward.

One of the most significant additions to that framework was the extra "E" for experience.

Expertise is knowing the subject. Experience is having actually done something with that knowledge.

A software company can publish an article explaining the common benefits of automation. Thousands of other companies can produce an almost identical article. It becomes much more useful when the company explains what happened during a real implementation, where the process failed, what customers misunderstood or which assumption turned out to be wrong.

That is the difference between describing a topic and contributing to it.

Google also specifically warns against producing large volumes of content across many topics in the hope that some of it will perform. It asks businesses to consider whether they are primarily summarising what others have said without adding value and whether automation is being used to produce content at scale.

None of this means Google is opposed to AI. It means AI does not remove the need for a useful reason to create the content in the first place.

If every platform wants originality, why is content becoming more generic?

The obvious answer is AI, but I do not think AI is the entire problem.

AI has dramatically reduced the effort required to produce something that looks like finished content. A marketing team can now move from idea to article, social post, email and video script in a fraction of the time it previously took.

That is enormously useful, but it has also encouraged businesses to confuse production with thinking.

The brief often starts with "write a post about this topic" rather than "what do we genuinely think about this topic?" The tool is asked to generate an opinion before the business has formed one.

Because generative AI works from patterns in existing information, a broad prompt usually produces a broad and familiar response. If every business asks the same tools similar questions about the same trending topic, it is hardly surprising that their content begins to sound alike.

The problem becomes worse when content production is measured primarily by quantity. Teams have calendars to fill, publishing targets to meet and an increasing number of channels to feed. AI makes it possible to satisfy that demand without increasing the budget or the size of the team.

What it does not guarantee is that anyone will care about the result.

Brands are optimising the visible parts of content

A lot of content now appears to have been created from the outside in.

The team starts with the platform format. They need three LinkedIn posts, two Reels, an article and an email. The content is then generated to fill those spaces.

This approach prioritises the visible outputs: the hook, the carousel, the video, the headline and the publishing schedule. Much less time is spent developing the substance underneath them.

What does the company know that its audience would find useful? What has the team learned from its customers? Where does its experience contradict the accepted advice? What is changing in the market that customers may not have noticed yet?

These questions take longer to answer because they usually require input from people outside the marketing team. Good content may need a conversation with sales, product, customer service, operations or the founder. It may involve reviewing customer questions, analysing CRM data or examining why a campaign did not perform as expected.

AI can help organise and communicate those insights, but it cannot invent the underlying experience without producing something generic or, worse, inaccurate.

The sameness is not limited to the writing

The problem is increasingly visible in creative, websites and wider brand presentation too.

We are starting to see exact replicas of cheaply built AI websites using the same page structures, oversized headlines, gradients, rounded cards, generic icons and predictable sections. Replace the logo and brand colours and one site could easily belong to hundreds of different businesses.

The same thing is happening with visual content. AI-generated images often share a recognisable aesthetic: overly polished lighting, smooth textures, artificial expressions and compositions that look impressive at first glance but reveal very little about the company behind them.

Across social media, brands use the same stock footage, Canva templates, carousel layouts, trending audio and editing styles. As soon as one format performs well, countless variations appear across unrelated accounts.

Templates, trends and AI tools are useful because they reduce production time and make professional-looking creative more accessible. The problem begins when the tool or template starts making the creative decisions for the brand.

A website can be produced more quickly than ever, but speed does not create positioning. An AI image can look technically impressive, but that does not make it meaningful. A polished carousel may communicate information clearly, but it will not build recognition if it looks like everything else in the feed.

Strong creative should do more than package a message attractively. It should reinforce what the brand believes, express its personality and help people recognise who is speaking. It should also support the strategy. The words, visuals and experience should work together to create a consistent impression of the business.

If the website, image or social post could be transferred to five competitors without anyone noticing, it is not building much brand distinction.

AI is making polished creative easier and cheaper to produce, just as it has made written content easier to produce. That creates a genuine opportunity for smaller businesses that previously could not afford sophisticated production. It also raises the standard because looking professional is rapidly becoming the baseline rather than the differentiator.

The brands that stand out will be the ones with a recognisable visual and verbal point of view. Their content will feel connected through the ideas they explore, the way they speak and the way those ideas are expressed creatively.

Originality is not only about what a brand says. It is also about whether people can recognise that the brand said it before they see the logo.

Original content does not require a completely new idea

The word "original" can make content creation sound more intimidating than it needs to be. Most businesses are not going to discover an entirely new marketing concept every week, and audiences do not necessarily expect them to.

Originality can come from the evidence, example, execution or perspective rather than the topic itself.

A company could write about customer retention, a subject that has been covered endlessly, but make it useful by showing where customers actually drop out of its process. A business could discuss AI adoption but explain which parts of implementation consumed more time than expected. A marketing team could comment on a platform update and show how it changes a real campaign or reporting decision.

The same principle applies to creative. A brand does not need to invent an entirely new type of website or social post. It does need to make deliberate decisions about how its strategy, personality and value should be expressed rather than accepting the first template or AI-generated concept it is given.

The subject or format may be familiar, but the experience behind it is not.

This is also why two experts can discuss exactly the same event and both produce valuable content. Each person notices different implications because they bring different experience to the issue.

The goal is not to find a topic or format that nobody has used. It is to avoid saying and showing exactly what everybody else already has.

A point of view requires some risk

Generic content is often safe because it avoids saying anything that could be challenged. It summarises the accepted position, offers balanced advice and concludes with a statement almost everyone can agree with.

That safety is also what makes it forgettable.

A genuine point of view requires a decision about what the business believes. It may mean arguing that a popular metric is misleading, questioning a common industry practice or explaining why the company takes a different approach.

It also requires creative decisions. Distinctive brands are rarely built by choosing the safest visual option available. They make choices about how they look, sound and behave, knowing that not every person will respond in the same way.

This does not mean creating controversy or visual noise for attention. Provocation without substance is just another form of engagement bait. It means being specific enough that the audience understands how the business thinks and confident enough to express that thinking consistently.

That is what allows content to build trust. Prospective customers are not only evaluating what a company knows. They are deciding whether they agree with its judgment and whether the business feels meaningfully different from its alternatives.

AI should improve the expression, not replace the idea

There is nothing inherently wrong with using AI to produce content or creative. It can help research a subject, identify gaps in an argument, test alternative headlines, improve structure, explore visual directions and turn a detailed idea into different formats.

The risk begins when the process starts and ends with the tool.

A better workflow begins with human input. Start with an observation, a customer conversation, a result, a disagreement or something the business has learned through experience. Decide what the point is before asking AI to write it.

The same applies to design. Begin with the positioning, the audience and the impression the brand needs to create. Decide what should feel distinctive before asking a tool to produce the website, image or campaign.

AI can then help make that thinking clearer, faster and more useful. It should not be asked to manufacture the perspective, strategy or identity that the brand was unwilling to develop.

This also requires a different review process. Instead of only checking grammar, visual polish, tone and brand compliance, ask more demanding questions. Could a competitor publish this without changing anything? Could another company replace our logo on this website? Does the creative reinforce the idea, or does it simply look current? Does the content contain an example that belongs specifically to us? Has it taught the reader something useful? Is there an identifiable point of view?

If the company name or logo can be replaced without changing the meaning or impression, the work probably is not distinctive enough.

More content is no longer the obvious answer

For years, the response to declining organic reach has often been to increase output. Publish more frequently, distribute across more formats and create more opportunities for the algorithm to pick something up.

That approach becomes less effective when every other brand has access to the same production tools.

As the volume of content increases, the value shifts towards elements that are harder to reproduce: real experience, first-party data, informed analysis, credible expertise, distinctive creative and a perspective shaped by actual work.

LinkedIn wants real voices and lived expertise. Meta is prioritising original creators. Google is asking whether content adds substantial value beyond what already exists. The terminology differs, but the direction is remarkably consistent.

The platforms do not need more technically competent content. They need content people find worth consuming.

Customers do not need more websites that look professional but say nothing distinctive. They need enough clarity and confidence to understand why one business is more relevant to them than another.

Brands now have access to tools capable of producing more content and creative than ever before. The real competitive advantage will come from knowing what is worth saying, developing a recognisable way to say it and resisting the temptation to look and sound like everybody else.