Why You Shouldn't Blindly Follow Google's Advice On AI Search

Google has been increasingly vocal about AI search.

The company is publishing guidance, discussing how websites should prepare for AI-powered search experiences, and reassuring businesses that many of the same principles that worked in traditional SEO still apply in the AI era.

On the surface, that sounds perfectly reasonable.

After all, Google has spent more than two decades shaping how businesses think about online visibility. If anyone understands search, surely it's Google.

The problem is that many businesses are making a dangerous assumption:

They're treating Google's advice as if it represents the entire future of AI search.

It doesn't.

In fact, if your AI visibility strategy begins and ends with Google's recommendations, there's a good chance you'll miss some of the biggest opportunities emerging across the broader AI ecosystem.

Before I explain why, here's a video I recorded on this exact topic:

The Biggest Mistake Businesses Are Making

Many businesses still view AI search through a Google lens.

That's understandable.

For most of the modern internet, discoverability has effectively meant Google.

If you wanted more leads, more traffic or more customers, you optimised for Google.

If you wanted visibility, you optimised for Google.

If you wanted growth, you optimised for Google.

The challenge is that AI search is fundamentally changing how people discover information.

Today, users are increasingly asking questions directly to:

• ChatGPT
• Gemini
• Claude
• Perplexity
• Microsoft Copilot
• Industry-specific AI assistants

Rather than searching for information, they're asking for recommendations.

Rather than comparing ten websites, they're receiving summaries.

Rather than clicking through multiple pages, they're getting direct answers.

This is a very different user experience.

More importantly, it's a very different discovery experience.

The businesses that understand this shift early have an opportunity to gain a significant advantage.

The businesses that assume Google still controls the entire conversation may find themselves reacting too slowly.

Google Only Controls One Piece Of The Puzzle

One of the biggest misconceptions in AI search is that there is a single set of rules.

There isn't.

Google controls Gemini.

OpenAI controls ChatGPT.

Anthropic controls Claude.

Perplexity controls Perplexity.

Each platform has different models, different retrieval methods, different training approaches and different ways of surfacing information.

This matters more than many businesses realise.

Imagine for a moment that Google published guidance saying:

"Focus on creating helpful content."

That's perfectly sensible advice.

But what does "helpful" mean to ChatGPT?

What does it mean to Claude?

What does it mean to Perplexity?

While there is overlap, there are also meaningful differences.

Some systems lean heavily on live web retrieval.

Others rely more heavily on model knowledge.

Some cite sources aggressively.

Others summarise information more freely.

Some place greater emphasis on authority and reputation signals.

Others focus more heavily on answering the user's question directly.

The reality is that nobody outside these companies fully understands every weighting, signal and decision-making process being used.

Which means businesses should be extremely cautious about assuming that guidance from one platform applies universally across all platforms.

AI Search Is Not Just Search

Another reason businesses should be careful about relying exclusively on Google's guidance is that AI search is no longer purely a search problem.

It's becoming a recommendation problem.

This distinction is incredibly important.

Traditional SEO was largely focused on ranking.

Could you appear on page one?

Could you secure position one?

Could you attract the click?

AI search changes the objective.

The question is no longer:

"Can you rank?"

The question increasingly becomes:

"Will the AI recommend you?"

That requires a different way of thinking.

Recommendation systems care deeply about trust.

They care about confidence.

They care about consistency.

They care about understanding.

If an AI system is going to recommend a law firm, a software platform, an accounting firm or a healthcare provider, it needs confidence in what that business does and who it serves.

That's why we're seeing increasing importance placed on:

• Brand authority
• Entity understanding
• Consistent information
• Trusted citations
• Reviews
• Reputation
• Subject matter expertise

These are not purely SEO concepts.

They're trust concepts.

And trust is becoming one of the most valuable assets a business can build in the AI era.

Understanding Incentives Matters

Whenever any major platform publishes advice, it's worth asking a simple question:

What incentives are driving that advice?

This isn't about conspiracy theories.

It's about understanding business models.

Google remains one of the most successful companies in history because of search.

More specifically, because of advertising connected to search.

For over twenty years, Google's business has benefited from users clicking links, visiting websites and interacting with search results.

AI changes that dynamic.

AI creates summaries.

AI creates recommendations.

AI reduces clicks.

AI compresses research.

AI changes attribution.

None of this means Google is acting in bad faith.

Far from it.

Google is doing what every company does: protecting and evolving its business model.

The important thing for businesses is recognising that Google's priorities may not always perfectly align with their own priorities.

Google's goal is building the best possible Google experience.

Your goal is maximising visibility wherever your customers are looking.

Those are not necessarily the same thing.

That's why businesses need to think beyond any single platform when developing their AI visibility strategy.

Why Google Doesn't Want AI Search To Be Manipulated

One of the reasons Google's guidance can sometimes feel conservative is because Google has spent decades fighting manipulation.

Every major update in Google's history has largely been designed to improve search quality and reduce attempts to artificially influence rankings.

That's understandable.

Nobody wants a search engine filled with spam, low-quality content or manipulated results.

But AI search introduces a new challenge.

Businesses naturally want to understand how recommendation systems work.

They want to know:

• Why certain brands are recommended
• Why competitors appear in answers
• How trust is established
• What influences visibility

Google's instinct is often to downplay tactical optimisation and focus on broad principles.

Again, that's not necessarily wrong.

But businesses should recognise that understanding how recommendation systems operate is a legitimate business objective.

Every major technological shift creates a period where early adopters gain an advantage.

The companies that learned SEO early gained an advantage.

The companies that embraced content marketing early gained an advantage.

The companies that understood social media early gained an advantage.

AI visibility will be no different.

Understanding how AI systems interpret, trust and recommend businesses is not manipulation.

It's adaptation.

The Opportunity Most Businesses Are Missing

Most organisations haven't started thinking seriously about AI visibility yet.

Many are still debating whether AI search matters.

Others are waiting for Google to publish more guidance.

Others assume AI visibility will simply take care of itself.

That's rarely how major shifts work.

The companies that benefit most from change are often the ones that start before everyone else.

Today, there is still a relatively small group of businesses actively investing in:

• AI visibility
• Answer Engine Optimization (AEO)
• Generative Engine Optimization (GEO)
• Brand authority
• Machine-readable websites
• AI-friendly content structures
• Entity development

That creates an opportunity.

Because AI systems are still learning.

Recommendation patterns are still developing.

Consumer behaviour is still evolving.

The businesses that establish authority, trust and visibility now are likely to benefit as adoption continues to accelerate.

So What Should Businesses Focus On?

Rather than obsessing over any single platform's guidance, I believe businesses should focus on becoming easier for AI systems to understand and trust.

That means investing in the fundamentals.

Build Clear Entity Understanding

AI systems need clarity.

They need to understand:

• Who you are
• What you do
• Where you operate
• Who you help
• Why you're different

Many websites are surprisingly poor at communicating these basics.

Create Consistent Information

Conflicting information creates uncertainty.

Your positioning, services, locations, expertise and company information should be consistent across:

• Your website
• Review platforms
• Business directories
• Social media profiles
• Third-party mentions

Strengthen Authority Signals

Authority increasingly matters.

That means investing in:

• Thought leadership
• Expert content
• Industry recognition
• Media mentions
• Reviews
• Trusted citations

Improve Machine Readability

AI systems process information differently from humans.

The easier you make it for machines to understand your business, the better.

Examples include:

• Structured data
• FAQ content
• Clear content architecture
• llms.txt files
• agents.md files
• Logical site structures

Focus On Trust

Ultimately, recommendation systems are trust systems.

The more confidence an AI has in your expertise and credibility, the more likely it is to surface your business in relevant conversations.

The Future Is Recommendation, Not Ranking

Perhaps the biggest mistake businesses make is assuming AI search is simply another version of Google.

It isn't.

Google's search results were designed around links.

AI systems are increasingly designed around recommendations.

That changes everything.

When someone asks:

• "Who is the best law firm for personal injury?"
• "Which software should I use for inventory planning?"
• "What is the best rewards platform for employee incentives?"

The AI isn't simply returning links.

It's making judgement calls.

It's building shortlists.

It's creating recommendations.

That means the future of visibility may depend less on where you rank and more on whether you're included in the answer.

Frequently Asked Questions

Should businesses ignore Google's AI advice?

No.

Google's advice remains valuable and many of its recommendations around quality, expertise and helpful content are sensible.

The mistake is assuming Google's guidance represents the entire AI ecosystem.

Is SEO still important?

Absolutely.

SEO remains one of the foundations of digital visibility.

The difference is that businesses increasingly need to think beyond rankings and consider how AI systems understand and recommend them.

What is Answer Engine Optimization (AEO)?

AEO focuses on helping businesses become visible within AI-generated answers and recommendations.

Rather than optimising exclusively for rankings, AEO focuses on discoverability within conversational AI platforms.

Does AI visibility only matter for large companies?

No.

In many cases, smaller businesses have an opportunity to move faster than larger organisations because they can adapt more quickly.

Which AI platforms should businesses focus on?

The major platforms currently include:

• ChatGPT
• Gemini
• Claude
• Perplexity
• Microsoft Copilot

However, the best approach is usually to build authority and trust broadly rather than chasing individual platforms.

Is AI visibility a replacement for SEO?

No.

AI visibility and SEO are closely connected.

Strong SEO foundations often support strong AI visibility.

The difference is that AI introduces new considerations around trust, authority, recommendation and machine understanding.

Final Thoughts

Google remains one of the most important companies in the search industry.

Its guidance deserves attention.

But businesses should be careful not to mistake Google's perspective for the entire future of AI search.

The AI ecosystem is bigger than Google.

The future of visibility is bigger than rankings.

And the businesses that thrive over the next decade will likely be the ones that focus on becoming trusted, understood and recommended across the entire AI landscape.

If you'd like to understand how visible your business currently is across ChatGPT, Gemini, Claude and Perplexity, or you'd like a practical roadmap for improving your AI visibility, get in touch with the team at LLM Listed.

We help businesses understand how AI systems perceive their brand, identify visibility gaps, and build the authority signals needed to become trusted recommendations in the AI era.