AI Search vs Traditional SEO

Introduction: A Shift in How People Find Information

Search has changed more in the past two years than in the previous two decades. The rise of AI search — powered by tools like ChatGPT, Google Gemini, and Perplexity AI — is rewriting the rules of visibility online.
Where traditional SEO relied on optimising for keywords and backlinks, AI search is built on semantic understanding, entity recognition, and brand credibility signals.

If SEO was about ranking, AI search is about being referenced, cited, and trusted.

In this article, we’ll unpack what makes AI search different from traditional SEO, why the shift matters, and how brands can adapt.

1. From Keywords to Knowledge Graphs

Traditional SEO was built on keywords. The goal was to match the words people typed into Google with words on your web pages. Search engines used indexing and link authority to decide which page best fit the query.

AI search engines work differently. They use Large Language Models (LLMs) that don’t just read words — they interpret meaning. Instead of returning a list of links, AI engines generate answers, summaries, or citations, often pulling from multiple trusted sources.

This means your brand’s presence in structured data, knowledge graphs, and AI training sources matters more than ever.

In short: SEO asked, “Which page ranks highest?”
AI search asks, “Which brands and entities are most trusted to answer this question?”

2. From Optimising Pages to Training Models

SEO traditionally meant optimising web pages: improving meta tags, content, internal linking, and site speed.

AI search shifts the goal from page optimisation to model influence — ensuring AI systems can understand your brand, not just crawl your content.

This includes:

• Adding schema markup and structured data to clarify meaning.

• Publishing authoritative, well-cited content aligned with E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness).

• Creating clear entity relationships (brand, people, products, places) across your digital ecosystem.

A 2024 study by BrightEdge found that 84% of generative search answers cite brands with verified schema and consistent entity data across multiple platforms — showing how AI discoverability now depends on structured credibility.

3. From Click-Throughs to Citations

In the SEO era, visibility was measured by impressions and clicks. But in AI search, visibility takes a new form: being cited in the output of AI answers.

When Perplexity AI or ChatGPT lists your domain as a source, that’s the equivalent of ranking #1 — but with more authority attached.

Generative Engine Optimisation (GEO) is emerging as the new playbook for this environment. GEO focuses on:

• Being referenced by AI systems.

• Appearing in summaries or answer citations.

• Building brand signals that models recognise and trust.

Brands are already treating GEO as the “next frontier” — not replacing SEO, but extending it into the AI era.

4. From Search Results to Knowledge Responses

Traditional search engines display ranked results you can click. AI search generates knowledge responses — natural-language answers that synthesise information.

For example:

• Google’s AI Overviews (rolling out across multiple countries in 2025) integrate generative summaries directly into search results.

• ChatGPT and Copilot deliver conversational answers with embedded citations.

• Perplexity AI pulls from verified sources and presents them as a single, contextualised narrative.

This means your brand’s content clarity, semantic consistency, and source credibility directly influence whether it’s included in those AI summaries.

In practice, AI search rewards meaning, not manipulation. Keyword stuffing, thin content, or irrelevant backlinks no longer move the needle.

5. From SEO Metrics to Brand Intelligence

Metrics in SEO — traffic, keyword rankings, backlinks — are being replaced with AI visibility metrics, such as:

• How often your brand appears in generative results.

• Whether your domain is cited by LLMs.

• How accurately AI describes your brand or products.

Some forward-thinking brands are already auditing how AI systems “see” them — using tools that simulate ChatGPT or Gemini queries to test brand discoverability.

At Brand Strategy AI, we call this “brand intelligence”: the process of ensuring AI systems understand, trust, and recommend your brand in the generative era.

6. Why This Matters for Brand Strategy

Traditional SEO treated content as a technical asset. AI search turns your brand into a data entity within the broader web of knowledge.

That means:

• Your brand voice, mission, and values become data points.

• Your leadership team, products, and expertise must be defined and linked in structured data.

• Your social profiles, citations, and publications contribute to how AI perceives authority.

In short, brand strategy is no longer just creative — it’s computable.

This is why forward-looking organisations are integrating AI Search Strategy Sprints into their digital roadmap: aligning brand language, governance, and schema so that both humans and machines understand them.

7. The Coexistence of SEO and AI Search

It’s important to note that AI search doesn’t replace SEO — it expands it.
Traditional search engines still drive the majority of web traffic, and optimised web pages remain essential.

However, the two now work in parallel:

• SEO keeps your brand visible in search results.

• AI search optimisation ensures your brand is included in AI-generated answers.

Together, they form a dual-visibility strategy: one for search engines, one for AI systems.

The most successful brands will master both.

8. How to Prepare Your Brand for AI Search

To future-proof your online visibility:

1. Audit your brand entities — ensure your company, people, and products are consistently defined online.

2. Add schema markup — clarify meaning for AI crawlers.

3. Create E-E-A-T-aligned content — demonstrate experience, expertise, authority, and trust.

4. Earn citations — contribute original insights to high-authority sites and journals.

5. Monitor AI visibility — regularly test how your brand appears in generative search responses.

AI search rewards clarity, credibility, and consistency — not shortcuts.

Conclusion: From Optimisation to Understanding

The shift from traditional SEO to AI search marks a deeper transformation in how brands communicate online.

We’re moving from optimising for algorithms to being understood by intelligence systems.

Brands that embrace this change — by structuring their knowledge, defining their entities, and investing in trust signals — will not only rank, but resonate in the AI search era.

At Brand Strategy AI, we help organisations navigate this transition — aligning strategy, structure, and authority to make your brand discoverable by AI.

FAQ

What is AI search?
AI search uses artificial intelligence to generate conversational answers instead of ranked links. It relies on entity understanding and trusted sources to provide contextual results.

How is AI search different from traditional SEO?
Traditional SEO focuses on ranking web pages for keywords. AI search focuses on trusted entities, structured data, and semantic accuracy.

Will SEO still matter?
Yes — SEO remains essential, but must now integrate with Generative Engine Optimisation (GEO) to maintain visibility in AI-driven search environments.

Best Regards,

David.

© David R. Durham, All rights reserved, 2025.