The direct answer

The most reliable way to identify AI search queries your audience uses is to directly observe AI assistant behavior — searching your topics in Perplexity and ChatGPT, reading the follow-up questions and related query suggestions those platforms show, and asking the AI assistants themselves what questions people commonly ask about your subject. These direct observation methods reveal the actual conversational queries your audience uses, which are often dramatically different from the keyword data your SEO tools report.

Method 1: Direct AI platform observation (highest value)

Open Perplexity and search your main topic. Note: the exact query you use, any follow-up questions the interface suggests, the “Related” queries shown at the bottom, and the phrasing used in the AI-generated answer itself. The answer phrasing often mirrors the phrasing of common queries on that topic. Repeat this with ChatGPT. The queries that appear across both platforms are the highest-priority content targets for your ASI strategy.

Method 2: Ask AI assistants what questions people ask

Ask ChatGPT or Claude directly: “What are the 15 most common questions people ask you about [your topic]?” The AI’s answer reflects the actual query patterns it encounters most frequently on your subject — it is trained on patterns of human conversation and can reliably report what it has been asked most often. This method takes 5 minutes and produces a list of conversational query patterns you can use as direct content targets.

Method 3: People Also Ask and autocomplete analysis

Google’s People Also Ask boxes and autocomplete suggestions reflect real user questions, including questions that are phrased conversationally. Open Google in incognito mode and type your main topic slowly — the autocomplete suggestions that appear are real searches. Hit enter and examine the People Also Ask questions. These are not identical to AI queries but they are much closer in phrasing than pure keyword research tools, and they reveal the natural language patterns your audience uses when they have a question.

Method 4: Email list replies and customer questions

Every reply to your email welcome sequence — particularly the email that asks “what is your biggest challenge?” — is a direct window into how your audience phrases their questions in natural language. These are the same phrasings they use when asking AI assistants. A question like “I’ve been trying to figure out why my site ranks in Google but never shows up in ChatGPT” is a direct content brief for an ASI page. Building the habit of reviewing email replies as content research produces a steady stream of real conversational queries validated by your actual audience.

Method 5: Reddit, forums, and community platforms

Search your topic on Reddit, relevant Facebook groups, LinkedIn, and industry forums. Post titles and opening sentences are typically written the way people would phrase the question to an AI — they include situational context, constraints, and specific problems. “I run a local plumbing business and I keep seeing my competitor show up in AI answers but I don’t — what am I missing?” is a Reddit post title that is also a direct AI query pattern. Tools like Also Asked (alsoasked.com) aggregate PAA data and can reveal conversational question clusters quickly.

Building your AI query tracking spreadsheet

Create a Google Sheet with columns for: the AI query (written exactly as a user would phrase it), the platform(s) where you observed it, the content page that should address it (existing or planned), and whether your site currently appears in the AI answer for that query. This spreadsheet serves as both a content roadmap and a monthly citation audit tool. Review it monthly — the queries where you are not cited are your highest-priority ASI content gaps.

How this connects to the other five disciplines

ASI is a writing discipline applied to every piece of content you publish — it works in combination with AEO (which structures pages for extraction), GEO (which builds topical authority), ANI (which ensures AI crawlers can access and read your content), and SEO (which handles keyword rankings and technical health). Content that is well-structured for AEO extraction, lives on a topically authoritative GEO site, is accessible to AI crawlers via ANI, and is written conversationally for ASI matching consistently outperforms content that only addresses one or two of these disciplines.

The ASI implementation habit

Unlike ANI (largely a one-time technical setup) or GEO (a content architecture project), ASI is a continuous writing practice. Every piece of content you publish should pass the read-aloud test, include a Who This Is For section, use second person throughout, and have a TL;DR box if it is over 1,000 words. Building these habits into your standard writing process takes about two weeks of conscious practice before they become automatic.

For existing content, prioritize your top 10 pages by traffic and do a full ASI retrofit on each — adding the TL;DR box, Who This Is For section, and voice pass. These pages already have traffic and topical authority signals working in their favor. Adding ASI improvements on top of existing content that is already being crawled produces the fastest citation rate improvements of any single optimization action available.

Related ASI guides

How to write a Who This Is For section · TL;DR boxes for AI citation · The full ASI checklist

The complete ASI guide library at teachmeoptimization.com/asi covers all 10 topics — from understanding how AI users phrase questions to the writing techniques that generate the most citations.

Building your ongoing AI query research habit

AI query patterns evolve as new AI systems launch and user behavior matures. A research approach that worked six months ago may miss query patterns that have emerged since. Build a monthly AI query research habit into your content process: 15 minutes searching your main topics in Perplexity and ChatGPT, noting any new question patterns that appear, and adding them to your content tracking spreadsheet. Over 12 months this builds a comprehensive picture of how your audience talks to AI assistants about your subject area — the most accurate and current data available for ASI content planning.