AI SEO Strategy: How to Build One That Covers Google and AI Answers

1. Define the question set

Start with the questions buyers ask when they are choosing: category questions ("best payroll software for restaurants"), comparisons, alternatives and direct requests for advice. Fifty to a hundred is enough to see patterns. This list is the unit everything else is measured against.

2. Measure each surface separately

Run the questions in Google and in each AI surface that matters to you, and record three things: whether you are named, whether you are recommended, and which sources are cited. Keep the surfaces apart, because they behave differently. Our guide to measuring AI visibility covers the metrics.

3. Map the sources

For each surface, list the domains that get cited for your questions. On the same 700 software questions, ChatGPT took about half its citations from vendor sites and never cited YouTube, while YouTube was the most-linked site in Google's AI Overviews (the data). The source map tells you where to work.

4. Fix the foundation

Make sure the search crawlers can reach you, including OAI-SearchBot for ChatGPT, which OpenAI says sites should not block if they want to appear in ChatGPT search. Then make your own pages the clearest answer: specific pricing, use cases and comparisons.

5. Work the sources you do not own

Across seven software categories, between 46 and 83 percent of ChatGPT's recommended brand mentions went to brands whose own site did not rank in Google's top ten for the question. Recommendations are shaped by review sites, comparison pages and video as much as by your rankings. Earning accurate coverage there is the slow, valuable part.

6. Track and adjust

Rerun the same questions on a schedule. Answers vary between runs, so judge by frequencies across the whole set, not single answers. Report presence, recommendation share and citation share by surface.

• Week one: crawler access, broken or out-of-date pages about your product, and a baseline measurement.
• First month: the pages that answer your highest-value questions, and your entity facts across major profiles. See entity SEO.
• First quarter: the third-party sources that shape answers in your category, starting with the ones cited most often.

This is the program we run for clients as an AI SEO agency, starting from a measured baseline rather than a checklist. If you are doing it yourself, the AI search engine optimization guide explains how each surface builds its answers.

What is an AI SEO strategy?

A plan for how a brand gets found and recommended across Google and AI answer engines together: which questions matter, which surfaces answer them, which sources those surfaces read, and what to change first.

How is it different from an SEO strategy?

The foundation is the same: crawlable, useful pages that answer real questions. The difference is measurement and sources. AI answers recommend brands rather than rank pages, and they draw on third-party sources you do not control, so the strategy has to cover both.

Which AI platforms should I focus on?

The ones your buyers use. For most companies that means Google, including AI Overviews and AI Mode, and ChatGPT, then Perplexity, Gemini, Copilot and Claude where they matter to your audience. Measure before you choose.

How long does AI SEO take to work?

Fixes to crawler access and your own pages can affect live-search answers once the pages are recrawled. Changing how third-party sources describe you takes longer. Measure against a fixed set of questions so you can tell real movement from normal variation.

• OpenAI Help Center: Publishers and Developers FAQ
• Google Search Central: AI features and your website

Every High Salience engagement starts with the Category Salience Brief: your commercial questions run across Google and the AI surfaces, competitors side by side, and a ranked list of what to fix first.