How to stand out in an ocean of AI content

Most content today is arbitrage, simply moving information from one place to another.

Very few blog posts create new information. Most serve to remix, curate and copy existing content, transferring the same core information from one website to another.

If all your content does is stir up common knowledge, then I have bad news: bots will eat your lunch. Generative AI is the ultimate arbitrage machine, capable of churning out thousands of copycat articles faster than you ever could.

To stand out in a sea of ​​basic content, you need to go beyond simply copying/pasting information and find other ways to add value.

Luckily, there are three ways you and your fragile human brain are uniquely qualified to add value beyond AI: experimentation, experienceAND effort.

The best way to add value beyond AI content is to experiment: go out into the world, test ideas, and gather new insights that have never existed before.

LLMs are trained on an incredibly large data set and continue to consume new information on a daily basis. But they are not omniscient. They have gaps in their knowledge: information they haven’t been trained on, or more importantly, information that doesn’t exist yet.

When you experiment, you create something new and proprietary, unique to you and never seen before. If someone wants the information you have to offer, there’s only one place they can get it. It does not exist in the data available to LLMs (at least, not yet). This is something that you, and only you, can do.

How to do it

This might sound intimidating, but experiments can be large or small, substantial projects in their own right or quick value-adds to otherwise mundane topics.

You can conduct extensive sector investigationslike Aira’s state of linkbuilding report:

Analyze the data generated by your company and its productslike the benchmark report I co-authored using 150 million page views of Google Analytics data:

Run tests to understand how things workas Patrick Stox did to explore the impact of high-level page blocking with robots.txt:

Collect data to prove (or disprove) well-known ideaslike Rand from SparkToro who confirms the idea that email is the most reliable marketing channel:

This has always been a great marketing strategy (and a great link building tactic – everyone wants to link to the original data, as the backlink data for Aira’s report shows).

But it becomes more effective in an age of near-perfect information, when the marginal cost of content creation is virtually zero and the answer to any common problem can be found in an instant.

There is no longer any lasting value in sharing basic information – the days of getting huge results from being the first brand to share a basic “how to” or tutorial are numbered. Today you have to do it create information and share it.

Anything created solely by generative AI is trapped in the realm of theory. It will always be less valuable than the same advice from an authoritative source, someone with clear and relevant experience.

In a world where it’s easy to get answers to questions, readers will care more about the answers source of the answer. You can stand out from faceless AI content by showing the reader that you’ve gotten your hands dirty, and have expert the thing you are writing about.

If there are fifty websites—or five hundred-By offering an answer to their question, readers can afford to be choosy about the source they choose. If they want to learn more about budgeting, they will probably choose the expert financial advisor rather than the anonymous CRM solution and a blog post written by “Content Team”.

If they want to buy a new camera, they will prefer the reviewer who has bought, used and compared real cameras:

Build credibility through first-person anecdotes, original product photos, and a documented testing methodology.

On any brand that has taken product descriptions from popular e-commerce stores or written in theoretical statements:

No credibility in sight: just regurgitated product features without any first-hand experience.

The more crowded a topic becomes, the more important direct experience becomes as a method of differentiation. Your job is to demonstrate where your advice comes from.

How to do it

This is something we try to do regularly on the Ahrefs blog.

You can write about topics you have first-hand experience withlike Chris, an experienced SEO agency, who writes our beginner’s guide to SEO reporting:

Interview people about topics that don’t interest youlike Mateusz interviewing real-life marketers about their favorite metrics:

Provide concrete evidence of your experience, whether it’s taking a screenshot of the tool, filming the interview, or sharing a photo of the book you referenced:

Share anecdotes and stories who provide context to the information, such as SQ who reflects on his experience writing over 100 articles:

Get skin in the game, like my attempt to read and evaluate every SEO newsletter out there:

The opposite is also true: You should avoid writing about topics in which you have no experience and can’t justify gaining it.

Most companies I see scaling AI content are motivated by cost. They’re not using generative AI to create new, innovative experiences – they’re trying to save money and are willing to sacrifice quality for speed of delivery and reduced headcount.

This provides a clear path to differentiation: do better things, expend more energy and create content that is more than just words on a page.

How to do it

Many of the brands I follow (and products I pay for) have caught my attention through great, effective content campaigns.

There are webcomicslike Postmark’s email deliverability guide (with Dunning the super-owl):

Video serieslike Paddle’s Netflix-style documentary series about taking over a company:

Bookslike Ahrefs’ beautifully illustrated children’s book:

Free toolslike Veed’s TikTok downloader:

Unique on-page experienceslike the one from Typeform The Star Wars Guide to Net Promoter Scorecomplete with hand-drawn AT-ATs:

This type of content is rare. It is expensive and difficult to create and requires specialized skills and collaboration between different departments. But difficulty is a moat: if it’s hard to create, it can’t be immediately pumped out by any old company with any old AI tool.

While it’s often difficult to justify the effort and expense of these projects, it gets easier with each passing day. Thanks to generative AI, serving functional, vanilla content – ​​words on a page with one or two stock images – is more than just a differentiator.

The more effort you put into building tools, publishing books, or creating unique experiences, the more likely real people will remember your brand, care about your company, and ultimately buy something from you.

Final thoughts

Generative AI makes it very easy to share fairly well-written, fairly accurate information, on a bewildering array of topics. Humans will never beat AI at this game, and frankly, we shouldn’t try.

We must accept the growing bifurcation of content. Let AI handle the low end of content (basic information content, definitions, summaries and synopses, lists) and focus skilled human energy on the high end.

In the era of generative AI, no benefit can be found by simply mixing common knowledge from one place to another. We must find new dimensions of differentiation and lean into our unique strengths: creating new insights through experimentation, getting our hands dirty and sharing firsthand experiences, and practicing to create what others won’t.

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