TLDR: AI tools like ChatGPT, Google AI Overviews, and Perplexity are changing how some consumers discover brands and products. But traditional search still dominates, Google holds 91.4% of the global search market, processes 8.5 billion searches a day, and AI chatbots account for just 2-3% of search-like queries. Generative Engine Optimisation (GEO) is a worthwhile part of your search strategy, but it works best as an extension of strong SEO foundations, not a replacement for them. Think of it as a layer within search, not a discipline on its own.
The search landscape in 2026: evolution, not revolution
There’s a lot of noise right now about AI changing search forever. And while AI-powered tools are genuinely reshaping parts of the discovery journey, it’s important to look at the numbers before overhauling your strategy.
As of early 2026, Google still commands 91.4% of the global search market and processes around 8.5 billion searches per day. AI chatbots, ChatGPT, Perplexity, Claude and others, account for an estimated 2–3% of search-like queries. That’s a meaningful and growing segment, but it’s still a small fraction of overall search behaviour.
What this tells us is that the customer journey hasn’t been rewritten, it’s being gradually extended. A growing number of consumers are using AI tools at some point in their research, particularly for conversational, exploratory queries. But the majority are still heading to Google. A comprehensive search strategy needs to serve both audiences. And crucially, the foundations that make you strong in traditional SEO will also make you more visible in AI-generated answers.
Understanding the relationship: Search strategy, SEO, and GEO
It helps to think of these three things as nested layers, not separate activities: Search strategy is the top level, your overall approach to being found by the right people, across all search touchpoints. Traditional SEO sits within that strategy, the discipline of optimising your content, technical foundations, and authority to rank well in search engines like Google. GEO sits within SEO, an evolution of the same principles, applied to AI-powered search experiences like ChatGPT, Google AI Overviews, and Perplexity
GEO is not a separate channel. It is not a replacement for SEO. It is SEO, done well, extended into a new context. The brands that treat it as a bolt-on or a separate workstream will struggle to get traction. The brands that weave GEO thinking into their existing search practice will compound their gains across both traditional and AI-powered discovery.
So what is GEO, exactly?
Generative Engine Optimisation is the practice of optimising your brand’s visibility within AI-powered search experiences. Where traditional SEO focuses on ranking in a list of links, GEO focuses on being included in the AI-generated answer itself.
The distinction is worth understanding. In a traditional search result, a user sees your brand and chooses whether to click. In an AI-generated response, the AI may cite your brand, your data, or your expertise directly as part of its answer. The user absorbs that information and associates it with your brand, whether or not they visit your site.
But the underlying logic is the same as SEO: be authoritative, be clear, be structured, be trusted by third parties. GEO doesn’t require a separate strategy. It requires your existing strategy to be executed with AI visibility in mind alongside traditional rankings.
Where GEO adds something new within your SEO practice
There are areas where GEO thinking extends or sharpens traditional SEO practice. These are not new disciplines; they’re refinements worth prioritising.
Answer-first content structure
AI engines break content into individual passages and evaluate each for relevance and clarity. Content that leads with a direct answer, rather than building to a conclusion, is more likely to be surfaced. FAQ sections are particularly powerful, as AI systems rely heavily on well-structured question-and-answer pairs. This is also good SEO practice for featured snippets.
Entity authority
GEO places greater emphasis on entities, your brand, your people, your products, not just individual pages. Strengthening those entity signals across the web, through consistent mentions, structured data, and third-party references, increases the likelihood that AI systems recognise and confidently cite your brand. Again, this overlaps directly with strong SEO practice.
Earned mentions and third-party signals
Customer reviews on G2, Trustpilot, or Capterra, press coverage, community discussions on Reddit and LinkedIn, these independent references give AI systems the signals they need to assess your credibility. AI models consistently favour sources that have been independently cited and validated. Building these signals is a long-standing SEO best practice, and it matters even more for GEO.
Technical foundations for AI crawlers
Ensure AI crawlers like GPTBot and PerplexityBot are not blocked in your robots.txt. Implement schema markup, particularly Article, Organisation, FAQ, and HowTo types. Consider adding an llms.txt file to guide AI systems in how to interpret your site. Keep content fresh and datestamped, AI engines weight recency when selecting sources.
Why measurement matters more than ever
Whether a customer finds you through Google, an AI overview, or a ChatGPT recommendation, the challenge for brands is understanding what’s actually driving results and that’s becoming harder.
A customer might discover your brand through an AI-generated answer, visit your site directly, and convert, leaving no attributable trail back to the touchpoint that started the journey. Traditional last-click or multi-touch attribution models aren’t built to capture this. Add in privacy changes, ad blockers, and cookie deprecation, and the measurement environment becomes increasingly incomplete.
This is where Marketing Mix Modelling (MMM) earns its place. Unlike attribution models that depend on tracking individual user journeys, MMM takes a statistical, top-down view of how each channel, including emerging ones like AI-driven discovery, contributes to overall business outcomes. It is privacy-safe by design and robust to the kind of signal loss that is making conventional measurement less reliable.
For brands building GEO into their search strategy, this creates a clear imperative: invest in the visibility, and invest equally in the measurement infrastructure that lets you understand what that visibility is actually worth.
What a strong, GEO-aware search strategy looks like in practice
Brands navigating this well are doing several things consistently:
- Leading with strong SEO foundations. Traditional search still drives the vast majority of discovery. GEO builds on top of this, not instead of it.
- Publishing original research. Proprietary data and original insight create citation magnets for both journalists and AI systems. Compounding authority builds over time and benefits every piece of content on your domain.
- Building presence beyond their own website. Thought leadership on LinkedIn, contributions to industry forums, and review generation on third-party platforms all feed the independent signal pool that AI systems draw from.
- Keeping content fresh. AI engines weight recency. Refreshing cornerstone content with updated data, new insights, and clear timestamps is now a strategic priority, not a housekeeping task.
- Measuring AI visibility alongside traditional metrics. Share of voice in AI-generated answers and brand mention frequency are useful additional indicators, not replacements for traditional performance metrics, but signals worth tracking alongside them.
- Integrating search performance into a broader measurement framework. Understanding the interplay between AI visibility, brand search volume, direct traffic, and conversion rates requires joined-up, channel-agnostic measurement.
The opportunity: get the balance right now
GEO is real, and it’s growing. But it represents a small fraction of the current search landscape, and brands that deprioritise their SEO foundations to chase AI visibility are making a strategic error. The smarter move is to treat GEO as a natural layer within good search practice and to build the measurement infrastructure that lets you understand performance across both.
The brands that act now aren’t betting everything on AI search. They’re making sure that as AI search grows, they’re already positioned to benefit, because their content is authoritative, their technical foundations are solid, and their measurement frameworks can account for how discovery is evolving.
How Modo25 can help
At Modo25, we help brands build data-led, channel-intelligent search strategies that account for where search is today and where it’s heading. From Marketing Mix Modelling that captures the full picture of channel performance, to content and measurement strategies built for both traditional and AI search, we take a joined-up approach.
If rising media costs, fragmented attribution, and AI-driven discovery are creating blind spots in your marketing strategy, we’d love to talk. Get in touch with our team. You can also explore our thinking on Marketing Mix Modelling and Paid Social to understand how we approach measurement and channel strategy for brands.
