What AI Search Gets Wrong

One thing AI does exceptionally well is aggregation.

Large language models can rapidly process vast amounts of information and generate coherent summaries.

For users seeking quick answers, this is incredibly useful.

Questions such as:

Can often be answered effectively within an AI-generated response.

This creates obvious efficiency benefits.

Users receive answers faster.

Search journeys become shorter.

Information becomes more accessible.

But this strength also creates one of AI's biggest weaknesses.

Because summarising information is not the same as understanding it.

One of the biggest misconceptions surrounding AI search is the assumption that information and expertise are interchangeable.

They are not.

AI can explain what something is.

It often struggles to explain why something matters.

More importantly, it struggles to understand nuance.

Take a simple SEO question.

Two businesses may ask:

On the surface, the question appears identical.

In reality, the answer depends on:

And countless other variables.

The correct answer for a financial services business may be entirely different from the correct answer for an eCommerce retailer or iGaming operator.

AI often treats these scenarios as variations of the same problem.

Experienced consultants recognise they are fundamentally different.

Another challenge involves how AI systems gather information.

Most models are designed to identify common patterns across existing content.

In simple terms, AI frequently tells users what most people are saying.

The problem is that popularity and accuracy are not always the same thing.

Within digital marketing, countless outdated assumptions continue to circulate despite being inaccurate.

Examples include:

Because AI often relies on consensus, it can unintentionally reinforce ideas that no longer reflect how search actually works.

This becomes particularly problematic in industries where search evolves rapidly.

The information may be widely repeated.

That does not automatically make it correct.

Businesses rarely invest in SEO, PPC or digital marketing because they want rankings.

They invest because they want growth.

This distinction matters.

A search engine can tell you how to optimise a page.

A consultant should help determine whether optimising that page is commercially worthwhile in the first place.

This is where AI often falls short.

AI can identify opportunities.

It struggles to prioritise them.

For example, a business may have hundreds of keyword opportunities.

Not all opportunities deserve investment.

The challenge is determining:

Commercial decision making requires judgement.

Judgement remains one of the most difficult things for AI to replicate.

Modern search behaviour rarely follows a straight line.

Users move between:

Before making decisions.

This behaviour creates layers of context that AI frequently struggles to interpret.

For example, a user searching for a gambling brand may not simply be seeking information.

They may be evaluating trust.

Comparing alternatives.

Assessing credibility.

Seeking reassurance.

The search itself only reveals a fraction of the decision-making process.

The broader behaviour tells a much richer story.

Understanding that behaviour remains critical for effective digital strategy.

One of the most interesting aspects of modern search is the growing importance of brand authority.

Search engines increasingly evaluate:

When determining visibility.

Strong brands often outperform weaker competitors even when content quality appears similar.

AI systems frequently underestimate these signals.

This happens because authority extends beyond individual pieces of content.

It exists across:

These factors are difficult to summarise within a single response.

Yet they play a significant role in how visibility is earned.

Perhaps the biggest issue with AI-generated search experiences is the tendency towards average answers.

AI is remarkably effective at generating reasonable responses.

The problem is that reasonable rarely creates competitive advantage.

Businesses rarely achieve growth by doing what everyone else is doing.

The strongest strategies often emerge from:

These are areas where human experience remains incredibly valuable.

AI can support strategy.

It cannot replace strategic thinking.

AI will undoubtedly transform search.

The businesses that succeed over the next decade will be those that embrace these changes.

But success is unlikely to come from chasing every new technology.

Instead, it will come from understanding something far more enduring — people.

Search has always been about connecting people with information.

AI changes how that information is delivered.

It does not change why people search.

Users still want:

The platforms may evolve.

The technology may improve.

But human behaviour remains remarkably consistent.