How ‘GEO’ and AI Optimisation Are Shaping the Future of SEO

When we talk about SEO, it’s easy to picture the classic search results page: blue links, ranking battles, incremental gains. Whether you’re a CMO or an SEO though, we’re sure you know that that landscape is shifting quickly, with generative LLMs like ChatGPT, Gemini and Perplexity providing increasingly convenient ways to retrieve information – fast.

And yet their potential goes far beyond boosting your productivity at work. They’re also gateways for audiences to research and discover brands and products, and they’re sending highly qualified traffic to the websites lucky enough to be cited by them. But this has left lots of brand stakeholders with one two three endless questions. How do I make sure my product appears in relevant AI content when my audience is reading it? Will I ‘rank’ well in AI search if I rank well in traditional search? And how on earth do I update my SEO strategy to include ‘GEO’?

The answer: ask your friendly local Data Scientist, and hook them up with a team of excited, seasoned SEO experts to analyse the results. Let’s get into it.

How we tackled the challenge

As always at Jaywing, we started by interrogating the data. Our Data Science and SEO teams paired up to analyse over 38k keywords and 200k AI prompts to determine just how organic search rankings influence citation frequency and position in AI-generated results. All this to futureproof our clients’ SEO strategies – without falling victim to the hype.

Check out our research paper for full insights on how SEO performance is already shaping AI visibility or keep reading for a sneak preview, with some strategic ‘GEO’ optimisation tips included for good measure.

If you want more expertise straight from the horse’s mouth, sign up for our webinar: Adapting for LLMs: How our research is driving client strategy on Thursday 4^th December 2025 – 1.00pm - 1.45pm, where we dig into the detail on AI citations and how data-driven optimisation can keep your brand visible and relevant in this (relatively) new space, and keep your performance measurable.

SEO Still Matters - But the Rules Are Changing

Our study revealed a strong connection between organic search performance and visibility in AI-generated results:

But we also found some surprising exceptions to the rule, confirming that top performance in traditional search doesn’t automatically translate to equal prominence in generative search. While strong rankings certainly influence AI visibility, many brands that dominate page one of Google are underrepresented in AI answers - a signal that LLMs weigh context, authority and content clarity in ways that extend beyond traditional ranking factors.

In fact, there was enough deviation to prove that this is a new optimisation frontier.

How Our Approach to Optimisation Is Evolving for the Age of AI Search

We all know how traditional search engines work: they retrieve and surface content that already exists, ranked by perceived quality and relevance to the user’s query. LLMs on the other hand interpret and reconstruct content to generate new answers, using signals of relevance, accuracy, and context from trusted sources to craft original answers that feel personalised and credible to the user.

In terms of tactics then, traditional SEO focuses on optimising for specific queries and onsite user experience, while GEO involves optimising for topics and long-tail prompts that LLMs can use within their systems and generative content.

Our approach to the latter fuses our expertise in data science and search strategy to help brands remain discoverable as the boundaries between ‘search’ and ‘recommendation’ blur. By merging proven SEO strategy with data-led tactics shown to improve visibility in AI models, we’re adapting our approach to meet the changing landscape:

Moving towards a topical approach to content building

ensuring every piece of content strengthens authority around a topic, not just a target keyword, relying less on volume led-optimisation.

Analysing how content structure, trust signals, and user experience influence citation probability

helping us identify the attributes that increase a brand’s likelihood of being referenced within AI-generated results.

Optimising metadata, schema, and language clarity

with semantic understanding to improve how content is interpreted between algorithmic and generative retrieval models.

Incorporating multi-modal signals

integrating imagery, video, and engagement metrics into our optimisation strategy to strengthen perceived authority within AI and search ecosystems.

Connecting on-site and off-site presence

ensuring that brand mentions, PR coverage, and social visibility reinforce credibility and context across the wider web.

Evolving our measurement framework

developing a proprietary approach that integrates external intelligence and our own analytics to measure how brands are cited, surfaced and prioritised across multiple generative search environments.