AI SEO Strategy: Planning for Search Engines and LLMs

An AI SEO strategy plans for two kinds of readers at once: classic search engines that rank pages, and AI systems that retrieve passages and assemble answers from them. Building an SEO strategy with AI in mind does not mean abandoning what works. It means understanding how answers are put together, where your brand needs to be present and how to measure visibility that does not always end in a click.

Why an AI SEO strategy is not just traditional SEO

The foundations are the same: crawlable pages, useful content, trust. What changes is the output. AI features answer the question directly, cite several sources and may be read without a click, so visibility, citations and brand mentions matter alongside rankings.

Google is clear that, from its point of view, optimising for generative AI search is still SEO: its guide to generative AI features says they are rooted in the core ranking and quality systems. Other assistants, such as ChatGPT, Perplexity and Copilot, use their own retrieval and crawlers. A practical strategy therefore keeps classic SEO as the base and adds three layers: presence in the sources assistants trust, content shaped for extraction and new ways of measuring.

Key aspects of developing an AI SEO strategy for 2026

A sound plan answers four questions: how AI systems choose sources, which questions your audience asks them, what evidence about your brand exists outside your site and how you will track visibility. The sections below take them in turn.

How LLMs retrieve data and generate responses

Modern AI search mostly works through retrieval-augmented generation, also called grounding. The system turns the user's question into search queries, retrieves current pages through a search index, selects relevant passages and asks the language model to write an answer based on them, with links to the sources. Without retrieval the model relies only on what it learned in training, which may be outdated.

1. The user asks a question, often long and conversational.
2. The system generates one or many related search queries.
3. A search index returns candidate pages, which pass quality and spam filters.
4. Relevant passages are selected and passed to the model.
5. The model writes the answer and attaches source links.

Trusted sources and their impact on SEO

Because retrieval runs through search systems, pages that rank well and are judged reliable are the ones most likely to be used. Assistants also lean on sources that look independent: reviews, media coverage, expert communities, reference sites. Your own site states your position; third-party sources confirm it.

Technical access for AI crawlers

None of this works if the systems cannot reach your pages. For Google's AI features, a page must be indexed and eligible to show a snippet; the Google-Extended token governs use in some of Google's other AI systems, not Search. OpenAI separates OAI-SearchBot, which surfaces sites in ChatGPT search, from GPTBot, which collects training data, so blocking one does not block the other. Review robots.txt, firewall rules and JavaScript rendering as part of a technical SEO check before judging AI visibility.

Query fan-out in content planning

Query fan-out means the AI system splits one question into many related sub-queries and searches them in parallel. For content planning, it means covering a topic's natural sub-questions well, not producing a separate page for each variation.

Google described the technique when it introduced AI Mode and later in its documentation: the system issues several related searches across subtopics and data sources, then combines the results. A question like "which CRM suits a small agency" may fan out into pricing, integrations, ease of setup, reviews and alternatives.

How to use this in planning:

• For each core topic, list the sub-questions a careful buyer would ask, using sales calls, support tickets and People also ask results.
• Answer the most important ones on the main page, and give deep sub-topics their own pages linked together.
• Check that each answer can stand alone: a passage lifted out of the page should still make sense.

Avoid the shortcut of mass-producing pages for every fan-out query. Google's guide states that this can fall under its scaled content abuse policy.

A new approach to content planning and keyword research

Keyword research still matters, but planning shifts from single phrases to questions, contexts and comparisons. AI tools can speed up research and clustering; the substance has to come from your expertise.

Content that AI systems tend to use

Google's guide contrasts commodity content that restates what already exists with non-commodity content based on first-hand experience. In practice, the pages that get cited tend to contain something specific: original data, clear definitions, step-by-step methods, comparisons with criteria, prices and conditions stated plainly, and named authors with real experience.

Analysing cited brands and segmenting queries

Run your key questions through the assistants your audience uses and note which brands and sources appear. Segment queries by stage: learning, comparing, choosing a supplier. Gaps where competitors are cited and you are not become priorities, either for new content or for presence on the sources being cited.

Where AI tools and agents help

An AI agent for SEO strategy work can cluster thousands of queries, draft outlines, summarise competitor pages and spot missing sub-topics. It should not publish on its own. Google allows AI-assisted content when it meets its quality standards, but large volumes of unreviewed text are a quality risk.

Building brand trust beyond your site

AI systems compare what you say about yourself with what others say about you. Consistent facts across directories, reviews, media and communities make your brand easier to describe correctly and more likely to be recommended.

External signals: profiles, reviews and mentions

Keep business profiles, industry directories and structured data consistent: name, address, services, prices where public. Collect genuine reviews and answer them; this overlaps with reputation management, because assistants summarise what customers write. Google notes that seeking inauthentic mentions is not as helpful as it may seem, so planted posts are a risk rather than a tactic.

Digital PR, communities and video

Expert comment in industry media, useful answers in professional communities and conference talks create the independent references assistants rely on. Video helps too: Google says its generative features can bring in relevant images and video, and video platforms are themselves widely cited sources.

Content structure for search engines and LLMs

Write for people first, with a structure that makes each part easy to find and quote: descriptive headings, a direct answer at the start of each section, then details, lists and tables where they genuinely help.

Google explicitly says there is no need to chop content into tiny pieces or to add special AI files and markup. Clear organisation simply helps everyone, including models.

Updating content and working with Search Console

An AI-aware strategy needs a measurement loop: track AI impressions alongside classic search data, refresh pages that lose visibility and check what assistants say after each update.

Search Console now includes a Generative AI performance report that shows impressions of your pages in AI Overviews and AI Mode by page, country, device and date. Combine it with the regular Performance report for clicks and queries, Bing's AI Performance report for Copilot citations and your own prompt tracking for other assistants. Review core pages at least quarterly: update facts, prices and examples, and make the change real rather than just changing a date.

For a Google AI Mode and SEO strategy that fits your market, QIO's GEO service starts with an audit of where your brand appears in AI answers today.

Sources

• Google's Guide to Optimizing for Generative AI Features on Google Search | Google Search Central
• AI Features and Your Website | Google Search Central
• AI Mode in Google Search: Updates from Google I/O 2025 | Google
• Introducing Search Generative AI performance reports in Search Console | Google Search Central Blog
• Overview of OpenAI Crawlers | OpenAI