As Mark highlighted in his presentation, AI search still depends heavily on Google's results and data. AI tools are not operating in a completely separate search environment, and many of them continue to rely on Google’s indexed content when retrieving live and up-to-date information.
This is also reflected in brand citations within AI-generated answers. Brands that are cited or recommended typically have strong Google rankings, established authority, and solid technical SEO foundations. As a result, businesses that want to improve their visibility in AI search still need to perform well in traditional search. Strong organic rankings remain an important factor in whether a brand is discovered, cited, or recommended by AI tools.
AI optimisation is an extension of SEO
There has been a lot of discussion around GEO, AEO, and AI optimisation. While these are useful ways to describe new search behaviours, they should not be treated as completely separate from SEO.
AI tools are still looking for information that is accessible, relevant, trustworthy, and easy to understand. These are the same principles that have always supported strong organic search performance.
However, one thing has changed: search has become much more conversational and personal.
Instead of users typing short queries, they are asking detailed, specific, and personalised questions. For example, instead of searching:
"Things to do in Athens"
a user may ask:
"I'm in Athens for a business trip and have Sunday afternoon free. What should I do if I want something relaxed and not too touristy?"
This shift means brands need to create content that answers more specific use cases, not just broad keyword themes.
What are the challenges of AI visibility tracking?
AI tracking is still immature
Many brands are now exploring AI visibility tracking tools. These tools can help identify whether a brand appears in AI-generated answers, which competitors are being cited, and how visibility changes over time.
However, AI visibility tracking is still far from perfect, as Aleyda Solis and several other speakers highlighted throughout the conference.
Prompts are highly personalised and almost infinite in variation. AI models are also updated regularly, which can affect the links, citations, and brand mentions they generate. As a result, AI-generated recommendations are often inconsistent.
This means brands should not treat AI visibility data as absolute truth. Instead, it should be used directionally. A more effective approach is to track a focused set of representative prompts based on real customer behaviour, priority personas, key products, target markets, and high-value use cases.
Generic content is becoming weaker because AI can generate it
For years, many SEO strategies relied on broad, generic content such as "Top 10 things to do" or "5 tips for..." articles. While this type of content can still work in some cases, the bar is now much higher. AI-powered search experiences, such as AI Overviews, make it easier for users to get generic information instantly. This means brands need to create content that offers something AI cannot easily replicate from existing search results.
This is why E-E-A-T signals are more important than ever. Strong content should include real value, such as:
- First-hand experience
- Original insights
- Expert commentary
- Real examples
- Customer questions
- Unique data
- Helpful images or videos
- Clear recommendations
- Brand-specific knowledge
The aim should not be to publish content just because a keyword has search volume. The aim should be to create content that genuinely helps the user and gives them something they would not get from a generic AI answer.
Do authors need to use their real names?
An interesting question raised during the panel was whether content authors need to use their real names to be considered authoritative. The answer was no.
Authority is not necessarily tied to a real name or even to a recognised industry expert. Instead, it comes from building a consistent identity and credible digital reputation over time.
The panel used ‘the man in Seat 61’ as an example. It has become one of the world's most trusted sources of information about train travel, despite many readers not knowing the creator's real name. What matters is not whether the author uses their legal name, but whether they have consistently demonstrated expertise and earned users' trust.
Learn more about E-E-A-T and why it matters.
How should content be created in the age of AI?
In the age of AI, content creation should no longer follow a simple “find a keyword, write a blog, publish it” approach. To understand what users are genuinely interested in, sources such as:
- Reddit
- YouTube
- Customer reviews
- Sales team insights
- Q&A data
should also be included in the research process.
This approach also aligns with how we, as an agency, approach user interest journey research. As Charlie also highlighted in his article on how Reddit can be used for SEO and audience research, platforms like Reddit offer valuable insights into users’ real questions, pain points and barriers within the decision-making journey.
Therefore, content should no longer be created only for search engines, but to answer the questions people are genuinely asking.
Brand consistency across the web matters more than ever
AI tools do not just learn from a brand's website. They also build an understanding of a brand from third-party sources, reviews, social profiles, Google Business Profiles, product feeds, news articles, and other mentions across the web.