Generative engine optimisation for AI chat visibility

Yes, Google is still the dominant search engine, holding 85%-90% share of the total global search market, according to Statcounter GlobalStats.

Users rely on Google for finding brand platforms, navigating to specific websites, and making purchases. These most commercially-valuable, bottom-of-funnel searches with high intent include:

• Navigational searches: users looking for a specific brand or website.
• Commercial searches: users researching brands and services.
• Transactional queries: people ready to purchase.

Meanwhile, generative AI platforms are growing in popularity for informational and research-focused queries. They excel at top-of-funnel experiences where users are exploring and learning rather than transacting immediately. In Q2 2025, 49% of searches on Google were navigational, compared to 34% on ChatGPT. Meanwhile, 52% of searches on ChatGPT were informational, compared to 36% in Google, showing a shift in user behaviour.

Regardless of this shift, Google is still by far the leading search engine across all query categories. With AI Overviews and AI Mode built directly into their search experience, Google are capturing the entire search funnel.

From 2015 through 2022, Google’s share of the global search market never fell below 90%—but that streak ended when ChatGPT exploded onto the scene in late 2022. After falling to 85% it has since recovered back to 90% in mid-2025. Despite this recovery, the emergence of generative AI platforms represents a genuine inflection point in how people find information – the first genuine, sustained erosion in two decades.

Conversational AI tools like ChatGPT, Claude, Perplexity, DeepSeek and Grok—not to mention Google's own Gemini—are carving out a niche for top-of-funnel research. Users value their instant, conversational answers and are increasingly kicking off informational searches there rather than in a traditional search bar. As generative AI continues to improve, that shift will likely accelerate; but for now, Google’s dominance remains largely intact, and there is a strong likelihood that Google will continue to evolve its search experience to incorporate more AI-led features.

Instead of asking whether AI platforms are taking search traffic away from Google, the more pertinent questions explore how Google search traffic is evolving as AI becomes more deeply embedded. User behaviours have already shifted and Google is increasingly building AI search into their platform as the default for certain. query types.

Unlike traditional search algorithms that lean on signals such as domain authority, backlinks, and click‑through data to create a ranked list of relevant webpages from a large index, generative AI chatbots craft their answers to queries by synthesising information they have already learned. Their sense of what counts as “reliable” or “relevant” is largely based on consensus signals in their training datasets. These training backbones include public web crawls, licensed datasets, and proprietary training materials.

Depending on their design, generative AI platforms fall into two broad categories:

• Pure language models: Generate free‑form text from internal training data knowledge without live browsing. No citations are provided.
• Retrieval-augmented systems: Run live queries against an index of the web (or other data stores), augment responses with the data retreived, and return answers with citations and links.

Contextual relevance and content quality have been important SEO signals for many years, alongside authority and other SEO metrics. There is substantial overlap between high‑ranking Google results and the websites cited and mentioned by AI. This is partly because of the shared foundations in assessing content quality and relevance, but also partly because authoritative domains feature heavily in the datasets that language models learn from and in the indices that retrieval‑augmented systems search. The fastest shortcut to AI visibility is having great traditional SEO.

Estimates vary across studies and the landscape is constantly evolving. As of Q2 2025, ChatGPT accounts for about 80% of the generative AI search market, according to SE Journal. However, Google Search still handles roughly 350 times more queries than all generative AI tools combined, making it the primary search destination overall.

It’s important to remember that many people who search on Google have already conducted initial research using generative AI. These users often arrive more informed and are primed to engage with specific brands, unique selling points (USPs), or solutions they’ve discovered earlier in their journey.

It’s important to remember that Google searches lead to engagement with AI Overviews and AI Mode. The adoption of AI search result interfaces is happening in-platform.

AI Overviews are Google’s proprietary generative AI snapshots. They are a 'SERP Feature' appearing at (or near) the top of the traditional search results for most informational queries. AI Mode is an expanded, conversational, fully AI-native search experience based on the same underlying technology as AI Overviews.

Powered by Google's large language models (LLMs), including Gemini, these AI answers synthesise information drawn from multiple sources across the web to produce a cohesive summary that directly answers the user’s query. The feature was formerly referred to as the Search Generative Experience (SGE) during its experimental rollout phase.

UX and Presentation

Visually, AI Overviews appear as a highlighted box at or near the top of the Search Engine Results Page (SERP). AI Mode has its own tab, just like News, Images, Video, and other search experiences—except quite tellingly, it is the only one that appears to the left of the traditional "Web" search tab.

The content may include:

• A short paragraph summarising the answer.
• Bulleted lists or step-by-step instructions.
• Suggested follow-up questions.
• Links to relevant sources.
• Sometimes images videos, products, or visual cards extracted from web pages.

We are increasingly also seeing AI-generated snippets appearing in features like People Also Ask.

AI Overviews, AI Mode and AI-generated snippets are designed to help users get quick, multi-faceted answers without needing to click through multiple pages. As a result, they often reduce clickthrough rates, but educate searchers and prime them to convert when they do click.

From a technical perspective, Google's AI Overviews and AI Mode are based on the same query rewriting and multi-step reasoning system. When a user searches Google, here's a simplified overview of what happens under the hood:

1. Analyse intent: Google parses the query (breaks it down), identifies entities, and classifies the likely intent (e.g. informational, commercial, navigational). This process uses a combination of foundational algorithms like RankBrain and Neural Matching (introduced in 2015 and 2018) together with more recent models such as BERT, MUM, and Gemini, which enhance semantic understanding and contextual awareness. In other words, they use advanced machine learning and AI systems to understand the meaning behind the user input.
2. Sub-questions & grounding: For complex queries, or for queries where the system has low confidence in its ability to provide a great answer without looking for external sources, the engine will break the user's query into sub-queries, known as 'fan-out' queries. It will then retrieve content from pages surfaced for those keywords using a system called FastSearch, which is a slimmed-down version of the full search algorithm.
3. Retrieval Augmented Generation (RAG): Using generative AI, Google composes a concise natural-language answer, blending Knowledge Graph data with the grounding content. Unlike traditional featured snippets, AI answers can combine details from multiple documents and weave them into a unified narrative, underpinned by multi-step reasoning.
4. Provide source links: Where grounding was used, the AI Overview includes a panel of source links (or "citations") adjacent to the summary. However, the presence and format of these links vary depending on confidence scores and content policy constraints.

In short, Google's AI search experiences are an embedded AI chat interface that uses “retrieval-augmented generation” (RAG) to deliver tailored, up-to-date, and verifiable answers designed to address the user’s precise intent, while remaining closely aligned with the traditional organic results for the same query. It can issue dozens of searches behind-the-scenes, reason across disparate pieces of information, and create an expert-level, fully-cited report.

A 2025 study by Ahrefs reported an average 34.5% drop in clickthrough rates for the #1 organic result when AI Overviews were shown. This means fewer people click on individual organic website links. The actual links in AI Overviews, including the citations, also do not get clocked as frequently as traditional organic results. Despite this, appearing in AI Overviews still helps brands gain visibility while users are researching a topic and can often improve conversion rates for users who do click.

No, brands should not ignore Google Search. Google is still crucial for brand visibility and high-intent searches. However, within their SEO strategy, brands now also need to optimise for generative AI platforms to stay visible where users are increasingly searching. Fortunately, there is a huge overlap between GEO and traditional SEO.

Brands should think about GEO the way they think about any other niche area of optimisation... it's simply an additional consideration within an already multi-faceted seamless search strategy.