Why optimising for AI is making every website sound the same

TLDR: GEO best practices make content easier for AI to read, extract, and cite. That part is useful. The problem is what happens next: when every business in a category follows the same advice, the content starts to converge. AI can only distinguish you from competitors if your content gives it something distinct to work with. If your unique selling point is not built into the content from the start, AI cannot make the case for you when it matters most.

Ask AI to recommend a service in almost any category and the results start to blur together. The names change, the prices change, and the team pages change, but the content itself feels eerily similar. The problem is that everything reads the same: the structure, the claims, the tone, all polished to the point of being forgettable.

The businesses differ, but they are following the same playbook.

Why this is happening

GEO best practices do make content more legible to AI. Structured headings help AI navigate the page. FAQ sections make it easier to extract direct answers. Declarative language gives AI something clear to cite. Clean entity signals tell AI exactly who you are and what you do. That is useful. It is also not enough.

A structured content framework gives you a way to organise your pages so AI can understand them. The Xyra content journey framework is built for exactly that purpose. But a framework is a structural guide, not a source of differentiation. It can tell you how to arrange the content. It cannot tell you what makes your business worth choosing over the competitor two results above you.

And this is where the problem starts.

When a framework becomes a cookie-cutter template, filled with generic claims that any business in your category could make, AI ends up with a set of pages that are structurally sound and substantively identical. An Ahrefs study of 900,000 web pages found that 74.2% of newly created pages now contain AI-generated content, and that number is still rising. When those pages are all built from the same templates and the same optimisation advice, convergence becomes inevitable.

What the actual problem is

The cost shows up at a very specific moment: when someone asks AI to compare options.

"Who is the best aesthetic clinic in London for lip fillers?"

"Compare Salesforce and HubSpot for a small sales team."

"Which home care provider in Bristol specialises in dementia care?"

"Which cosmetic dentist is known for natural-looking veneers?"

These are not exploratory searches. The person asking already knows the category. They want AI to shortlist. And AI can only shortlist using the content it can access.

If your content contains no genuine USP, no specific methodology, no point of view, and no claim a competitor could not comfortably copy and paste onto their own site, AI has nothing specific to surface about you. At best, you become one interchangeable option among several. At worst, you get passed over entirely for a competitor whose content gave AI something more concrete to work with.

Being cited is not the same as being chosen.

And being cited as generic is barely better than not being cited at all, because the user who clicks through arrives expecting a reason to choose you and finds a page that could belong to anyone in your category.

Who this affects

Any business that can be reduced to a "who is best for X" query is exposed to this problem.

That includes:

• SaaS products being compared side by side.

• Ecommerce brands judged on value, quality, or fit.

• Aesthetic clinics, cosmetic dentists, med spas, and longevity clinics.

• Home care providers and other healthcare services.

• Legal, financial, and professional services.

This is happening across sectors, including markets that are not obviously competitive. People are already asking AI to compare businesses; the question is whether your content gives AI enough to say something specific about you when they do.

The problem also affects strong websites with substantial content. Some of the most technically well-optimised sites score well on discoverability and entity clarity but still fail here because the content AI would extract gives the user no real reason to choose that business over the next result on the list.

How to fix it

Most businesses still treat content strategy and GEO strategy as separate workstreams: GEO for extraction and content for brand. Both need to answer the question that matters most in an AI-first search environment: does this content give AI something specific and distinct enough to surface when someone is actively comparing options?

That is the question you have to answer first.

Your unique selling point needs to come before the structure, not after it.

What is it that your business does, believes, or delivers that a competitor cannot credibly claim?

That answer has to be the foundation. The structure should then make it easy for AI to extract and easy for humans to trust.

A cosmetic dentist with a specific approach to natural-looking results needs content that explains exactly what that approach is and why it produces different outcomes, rather than merely stating that they offer cosmetic dentistry. A SaaS business with a genuine integration advantage needs content that explains the commercial impact of that advantage in plain terms, rather than a feature list that looks exactly like everyone else’s.

Your USP, made explicit and structured for extraction, is what gives AI the material to differentiate you.

Generic reassurance signals such as experienced team, client-focused approach, and proven results exist on every competitor site. They are table stakes rather than differentiators.

For a deeper look at how to structure content so it both converts AI-referred visitors and supports a coherent decision journey, the content journey framework covers exactly that. The two questions are connected: getting cited for the right reasons, and then converting visitors after the click, both depend on the same discipline, which is knowing what makes you distinct and making that legible at every stage.

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If you want to see where your site stands, the AI Visibility Scan is a useful starting point. If you want to understand the gap between visibility and conversion, the ROI calculator puts a number on it. And if you want to go deeper, get in touch.

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Frequently asked questions

Why does AI content sound the same across different websites?

Most AI writing tools draw from similar training data and default to common patterns in professional writing. When businesses also apply the same GEO optimisation techniques, the result is content that is easy for AI to read but hard to distinguish.

Why does it matter if my content sounds like my competitors?

Because in comparison and recommendation searches, AI can only differentiate between businesses using what your content gives it to work with. If your content has no real USP, AI has nothing specific to say about you.

Which industries are most affected by AI content convergence?

Any sector where someone can ask AI "who is best for X" is affected. That includes SaaS, ecommerce, aesthetics, dentistry, med spas, home care, legal, financial, and professional services.

What does good content differentiation look like in a GEO context?

It is specific, not just structured. It includes real claims, actual experience, a point of view competitors cannot easily copy, or a way of framing your expertise that is genuinely distinct.

How do content strategy and GEO strategy need to work together?

They need to start from the same foundation: your USP. Structure should support differentiation, not hide the fact that it is missing.

How do I know if my content is too generic to perform well in AI search?

Remove your business name and replace it with a competitor’s. If the content still reads credibly, it is too generic. If it could sit on any competitor’s website without raising questions, it is not differentiated enough.